Frontiers In Education Computer Science And Computer Engineering 1st Edition Hamid R Arabnia Leonidas Deligiannidis Fernando G Tinetti Quocnam Tran
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May 18, 2025
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Frontiers In Education Computer Science And Computer Engineering 1st Edition Hamid R Arabnia Leonidas Deligiannidis Fernando G Tinetti Quocnam Tran
Frontiers In Education Computer Science And Computer Engineering 1st Edition Hamid R Arabnia Leonidas Deligiannidis Fernando G Tinetti Quocnam Tran
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Frontiers In Education Computer Science And
Computer Engineering 1st Edition Hamid R Arabnia
Leonidas Deligiannidis Fernando G Tinetti
Quocnam Tran download
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FECS |)
Editors
Hamid R. Arabia
'ernando G. Tineti
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Ashu M.G. Solo
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Computer Engineering 1st Edition Hamid R Arabnia
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FECS |)
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'ernando G. Tineti
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Frontiers
in Pen and
PROCEEDINGS OF THE 2019 INTERNATIONAL CONFEREN
FRONTIERS IN EDUCATION: COMPUTER SCIENCE &
'MPUTER ENGINEERING
FECS’19
Editors
Hamid R. Arabnia
Leonidas Deligiannidis, Fernando G. Tinetti
Quoc-Nam Tran
Associate Editor
Ashu M. G. Solo
Tight 2019 CSREA Press
FRONTIERS IN EDUCATION: COMPUTER SCIENCE &
'MPUTER ENGINEERING
FECS’19
Editors
Hamid R. Arabnia
Leonidas Deligiannidis, Fernando G. Tinetti
Quoc-Nam Tran
Associate Editor
Ashu M. G. Solo
Tight 2019 CSREA Press
‘This volume contains papers presented atthe 2019 International Conference on Frontiers in Education:
Computer Science & Computer Engineering. Their inclusion in this publication does not necessarily constitute
‘endorsements by editors or by the publisher.
Copyright and Reprint Permission
Copying without a fee is permitted provided that the copies are not made or distributed for direct
commercial advantage, and credit to source is given. Abstracting is permitted with credit to the source.
Please contact the publisher for other copying, reprit or republication permission.
American Council on Science and Education (ACSE)
Copyright 2019 CSREA Press
ISBN: 1-60132-498-7
Printed inthe United States of America
‘mep:/amertcancseorg/events/esce2019/proceedings
Computer Science & Computer Engineering. Their inclusion in this publication does not necessarily constitute
‘endorsements by editors or by the publisher.
Copyright and Reprint Permission
Copying without a fee is permitted provided that the copies are not made or distributed for direct
commercial advantage, and credit to source is given. Abstracting is permitted with credit to the source.
Please contact the publisher for other copying, reprit or republication permission.
American Council on Science and Education (ACSE)
Copyright 2019 CSREA Press
ISBN: 1-60132-498-7
Printed inthe United States of America
‘mep:/amertcancseorg/events/esce2019/proceedings
Foreword
lt gives us great pleasure to introduce this collection of papers tobe presented a the 2019 Iterations
‘Confrence on rois in Education: Computer Science and Computer Engineering (FECS'1) July 29 =
‘August 1, 2019, at Luxor Hotel (a propery of MGM Resor Iternalona), Las Vegas, USA, The
Preliminary edition ofthis book availble in July 2019 for dsibuton on it atthe conference) includes
‘nly à smal subse o the accepted research articles. The final edition (valable in August 2019) will
inche all accepted research ares This duc to deadline extension requests ehe from most amor
ho wished o coming enhancing the write-up of thee papers (by incorporan the eee suggestions).
Te Gil lion ofthe proceedings will de male availble ul
psifamercaneseorgfeventvesce2019 procera
‘An important mission of the World Congress in Computer Science, Computer Engineering. and Applied
Computing CSC (a federated congress t which thn conference i lite wih) includes “Providing a
‘inte platform fora diverse communi of constituents composed of scholars, researchers, developers,
cars, and proitioners. The Congress makes concerted far 1 reach out to participants fu
vs diverse ens (such a: universe, isos, corporations, government agentes, and esearch
‘entersfas) from all ver the world. The congres alo tenus to connect participants fom insano
‘hat have techng as hir main mission with those who are als wi tions tht have research
‘a their main mission. The congre ac a quota system to achieve ls nin and geography diversity
“objectives” By any definition of diversity, ths congress i among the most diverse scientific meeting in
(USA. We are proud 0 report that his federated congress has autho and paricipants rom 57 difieren
rations representing Variety of personal and scie experiences that are fom dierences in culture and
Values As can be seen (se Below), tbe program commite ofthis conference aswell as Ihe program
omite of al ter treks ofthe Fer congress re as dere is authors and para
“The program commie would kt thank ll hose who submited papers for consideration, Aout 435
‘ofthe submissions were from outside the United Stes. Each Submit paper was poersevicwed by tuo.
‘experts in the el fr rial, significance, eat, impact and soundness. In eases of eotalictry
recommendations, a menber ofthe conference program comico was charged to ke the nal decision:
‘en, this involved seeking help from addinal refers. In addition, papers whose auhers included a
member ofthe conference program comme were erased ving the doubl-Dindal review proces.
‘One exception to the above evaluation process was or papers that were submited diet lo
chanoranizer of pre-approved sessionvorkshops: in thse cases, he chusorganizrs were
Tesponible forthe evaluation of sich submission. The overall paper acceptance rue Tor regular papes
as 19% 26% ofthe remaining paper were accepted as poster papers (atthe time of his writing. we had
to yet ceived he ccepanc ae fora couple of individual racks)
We ae very grata tothe many colleagues wh offered thei services in organizing te conference, In
particular, we would like 1 tank the members of Program Commits of FECS 19, members of the
Congress Steering Commits, ad members of the comme of federated congress tks tat hve topics
in he cope of FECS, Many individuals std Below, wil e requested aller the conference 40 provide
thee expertise and services for selecting papers fr publication (extended versions) in joumal poca
‘sues a ell as für publication in a set of esearch books ( he prepared for publishers chiding:
Springer, Elsevier, BMC joumal ad ethers
+ Po font Aga: Diamant of Cope Sec, Wt Cheer Uwe Fumero, Mes
Ghar Pa Oe
+ Pol Abe AL Baby (Congres Seeing Conve); avery Penden, Diner of and
Corner, phan. Pay
+ af mena Nar Aso Congres Seng Cort): rotor and Cua, Beta and
‘Comper Engreemn Experiment ee Cha, ERBEN Compite Char: Ones of Dent Mary,
Deren, Megan US
+ Po Had abrio (Congres tng Conte): radar ogro Deco (PRD. ME MANS:
Te era of ons Ut ator n Gh nara! of aprconpuane pane Flo, Outer ef
cales Teror, enano, bligence& Crpancad Gn Pesar (CENTRO
lt gives us great pleasure to introduce this collection of papers tobe presented a the 2019 Iterations
‘Confrence on rois in Education: Computer Science and Computer Engineering (FECS'1) July 29 =
‘August 1, 2019, at Luxor Hotel (a propery of MGM Resor Iternalona), Las Vegas, USA, The
Preliminary edition ofthis book availble in July 2019 for dsibuton on it atthe conference) includes
‘nly à smal subse o the accepted research articles. The final edition (valable in August 2019) will
inche all accepted research ares This duc to deadline extension requests ehe from most amor
ho wished o coming enhancing the write-up of thee papers (by incorporan the eee suggestions).
Te Gil lion ofthe proceedings will de male availble ul
psifamercaneseorgfeventvesce2019 procera
‘An important mission of the World Congress in Computer Science, Computer Engineering. and Applied
Computing CSC (a federated congress t which thn conference i lite wih) includes “Providing a
‘inte platform fora diverse communi of constituents composed of scholars, researchers, developers,
cars, and proitioners. The Congress makes concerted far 1 reach out to participants fu
vs diverse ens (such a: universe, isos, corporations, government agentes, and esearch
‘entersfas) from all ver the world. The congres alo tenus to connect participants fom insano
‘hat have techng as hir main mission with those who are als wi tions tht have research
‘a their main mission. The congre ac a quota system to achieve ls nin and geography diversity
“objectives” By any definition of diversity, ths congress i among the most diverse scientific meeting in
(USA. We are proud 0 report that his federated congress has autho and paricipants rom 57 difieren
rations representing Variety of personal and scie experiences that are fom dierences in culture and
Values As can be seen (se Below), tbe program commite ofthis conference aswell as Ihe program
omite of al ter treks ofthe Fer congress re as dere is authors and para
“The program commie would kt thank ll hose who submited papers for consideration, Aout 435
‘ofthe submissions were from outside the United Stes. Each Submit paper was poersevicwed by tuo.
‘experts in the el fr rial, significance, eat, impact and soundness. In eases of eotalictry
recommendations, a menber ofthe conference program comico was charged to ke the nal decision:
‘en, this involved seeking help from addinal refers. In addition, papers whose auhers included a
member ofthe conference program comme were erased ving the doubl-Dindal review proces.
‘One exception to the above evaluation process was or papers that were submited diet lo
chanoranizer of pre-approved sessionvorkshops: in thse cases, he chusorganizrs were
Tesponible forthe evaluation of sich submission. The overall paper acceptance rue Tor regular papes
as 19% 26% ofthe remaining paper were accepted as poster papers (atthe time of his writing. we had
to yet ceived he ccepanc ae fora couple of individual racks)
We ae very grata tothe many colleagues wh offered thei services in organizing te conference, In
particular, we would like 1 tank the members of Program Commits of FECS 19, members of the
Congress Steering Commits, ad members of the comme of federated congress tks tat hve topics
in he cope of FECS, Many individuals std Below, wil e requested aller the conference 40 provide
thee expertise and services for selecting papers fr publication (extended versions) in joumal poca
‘sues a ell as für publication in a set of esearch books ( he prepared for publishers chiding:
Springer, Elsevier, BMC joumal ad ethers
+ Po font Aga: Diamant of Cope Sec, Wt Cheer Uwe Fumero, Mes
Ghar Pa Oe
+ Pol Abe AL Baby (Congres Seeing Conve); avery Penden, Diner of and
Corner, phan. Pay
+ af mena Nar Aso Congres Seng Cort): rotor and Cua, Beta and
‘Comper Engreemn Experiment ee Cha, ERBEN Compite Char: Ones of Dent Mary,
Deren, Megan US
+ Po Had abrio (Congres tng Conte): radar ogro Deco (PRD. ME MANS:
Te era of ons Ut ator n Gh nara! of aprconpuane pane Flo, Outer ef
cales Teror, enano, bligence& Crpancad Gn Pesar (CENTRO
+ Po Men det Department of Banc and Bivaproneil Sc, Te non Le
Pema, 4
+ of De dua one Col srande: Verte otc de Flea (UPI), Dearne of
‘Comper mer (SCA) alert, pa
© of duo doe Marne: Cale: actor, The Aco An Tog Moa Tela Pera ep nd
+ Prof. Bmering Kevin Dar (Congress Zee Comte); Director. Computer sence and Sofware
Bngneerng Propane, Department of Madera, Compr See and Sere gee ne
era of De Ney, Data Megan, USA
+ Pol Zange mo Danechenome; herrero ofthe Seco, Con Anon mera, coto,
An epi of Esato: Hee Paden of bu anna ende tratos Lect,
ana apa catan
+ Po Lies Diane (Conc Sung Conte): parten of Computer simon tens,
Menor tt Ted, Boton, Machete, UA Mtg Mofa MIT, USA
+ D Lee Ama Doud (Cha, Doctoral Cloguu & Denos enon: JrctoneTeiologt, France
©. Prof May Mehmch Estghan Mine (Congres Sewing Comite) Profesor of Bienen
Pacte. vera of South Coloma, Coro, USA Agua Par Bea Engneeng.
Diners of Clore Zt Angeles, Ls Angeles (UCLA) Calma, A
+ Bot Gea Greene (Congres Deer Cort): Dre, Pp abort & ea of
Abreco Sete Comp pled Mah & Appears Rech up: Profesor ope
Brie nd Dural Corp and Dap RCE Room Dosen
meat of Trace. on, vee
+ Po cine Ha; parm of Comper Brewing tne Da Pocra and Computers,
Unna Fee de Yalta, an
+ of Gor dont (Congres eng Comite); organ Technical Live, Tan, George:
fie, The Dune of Phares, Gore cade of ence, Gorga: Mar.
Peer foma of crower end Opncl Tolo, The Gpe Amar iene ral,
Anorcan sonal enc Snare, Cora
+ Bor anne Qu fm Congres Sane Conta; Maa Poesung Creations
asec, Dramen o congue Enero an Benson, Cale of Eger, Seon
Diners Such vee
+ of Ta ion Am hoc mation and Copie Bence, Ve Terme Aura
© Bote olor Loca; Chasperzon, Comper Bere Dame, Coge Bree,
Alonso Lavery Male, Phipps Sonor Mer, euro Asccianon of Corpa Seno
Dan Tomo (ACE. pr: ember, eon An fone Dane
+ Prof Dr. Guorang La; Computer Science and Technology, un Ye Sen Unversity, Guang-hu, PR China
© D ande are (Congres Seng Comat); CEO, Ha acm La (alere oer te
Proce Uk: rie Omerl of Word Aal Boedo Since nd mass (AED) a
+ of De, De foto tran Crane (Congres Seg Conte): Deprtent feria &
Becroncs Brgmeurng Pe of Dipnerng and Temolog,anbree al aves, gra
+ Po Jones (one Hk) Prk Congres Seeing Conn): pam of Conquer tence ad
Bigg (DOSE, Souto, Koes: Perdon PTA, BO, AGE PC DI: Had of
DER ona, Kr
+ De Ach gh (Congres Seeing Cem); IBM Coporaton, Sean, Clot, USA;
here Sema, nce Coun UR Pl, ah Corpus Bey; Mb. Soir IEEE AACR,
AAAS nk A IB Corpor, A
Cenar Sta: Aa, Daparmen Copo nc and. Anti Cole, Kran, pal
+ asu O So (Abe) Fallow of nh Concer Si, Pumpe R&D Ber, Marc
Tellier aera be,
+ of bed im ot ee ll, EM Ser Meter, IEEE Fou of Brgnenng ond Ron
trata Unser, ies oe
+ of Ferendo O, mu (Congress Seen Cora); hol of Computer une, Laverda
enana de L lt, a Plat going i Corto Pmestgacoms ect de la Po Be
arena
+ Po Hakan Harr (Congres Seen Cone: es Raco, and Den of Computer
‘Digneenng Foc, sharon Monel Umversty lado Hacroncs, eine and Poe” o/Dangn
tomaron bapa Compu” Exgueenng ac, Karke: 128 Conpuer Sey Glam Coro
‘aber non une e adi Barres Une
Pema, 4
+ of De dua one Col srande: Verte otc de Flea (UPI), Dearne of
‘Comper mer (SCA) alert, pa
© of duo doe Marne: Cale: actor, The Aco An Tog Moa Tela Pera ep nd
+ Prof. Bmering Kevin Dar (Congress Zee Comte); Director. Computer sence and Sofware
Bngneerng Propane, Department of Madera, Compr See and Sere gee ne
era of De Ney, Data Megan, USA
+ Pol Zange mo Danechenome; herrero ofthe Seco, Con Anon mera, coto,
An epi of Esato: Hee Paden of bu anna ende tratos Lect,
ana apa catan
+ Po Lies Diane (Conc Sung Conte): parten of Computer simon tens,
Menor tt Ted, Boton, Machete, UA Mtg Mofa MIT, USA
+ D Lee Ama Doud (Cha, Doctoral Cloguu & Denos enon: JrctoneTeiologt, France
©. Prof May Mehmch Estghan Mine (Congres Sewing Comite) Profesor of Bienen
Pacte. vera of South Coloma, Coro, USA Agua Par Bea Engneeng.
Diners of Clore Zt Angeles, Ls Angeles (UCLA) Calma, A
+ Bot Gea Greene (Congres Deer Cort): Dre, Pp abort & ea of
Abreco Sete Comp pled Mah & Appears Rech up: Profesor ope
Brie nd Dural Corp and Dap RCE Room Dosen
meat of Trace. on, vee
+ Po cine Ha; parm of Comper Brewing tne Da Pocra and Computers,
Unna Fee de Yalta, an
+ of Gor dont (Congres eng Comite); organ Technical Live, Tan, George:
fie, The Dune of Phares, Gore cade of ence, Gorga: Mar.
Peer foma of crower end Opncl Tolo, The Gpe Amar iene ral,
Anorcan sonal enc Snare, Cora
+ Bor anne Qu fm Congres Sane Conta; Maa Poesung Creations
asec, Dramen o congue Enero an Benson, Cale of Eger, Seon
Diners Such vee
+ of Ta ion Am hoc mation and Copie Bence, Ve Terme Aura
© Bote olor Loca; Chasperzon, Comper Bere Dame, Coge Bree,
Alonso Lavery Male, Phipps Sonor Mer, euro Asccianon of Corpa Seno
Dan Tomo (ACE. pr: ember, eon An fone Dane
+ Prof Dr. Guorang La; Computer Science and Technology, un Ye Sen Unversity, Guang-hu, PR China
© D ande are (Congres Seng Comat); CEO, Ha acm La (alere oer te
Proce Uk: rie Omerl of Word Aal Boedo Since nd mass (AED) a
+ of De, De foto tran Crane (Congres Seg Conte): Deprtent feria &
Becroncs Brgmeurng Pe of Dipnerng and Temolog,anbree al aves, gra
+ Po Jones (one Hk) Prk Congres Seeing Conn): pam of Conquer tence ad
Bigg (DOSE, Souto, Koes: Perdon PTA, BO, AGE PC DI: Had of
DER ona, Kr
+ De Ach gh (Congres Seeing Cem); IBM Coporaton, Sean, Clot, USA;
here Sema, nce Coun UR Pl, ah Corpus Bey; Mb. Soir IEEE AACR,
AAAS nk A IB Corpor, A
Cenar Sta: Aa, Daparmen Copo nc and. Anti Cole, Kran, pal
+ asu O So (Abe) Fallow of nh Concer Si, Pumpe R&D Ber, Marc
Tellier aera be,
+ of bed im ot ee ll, EM Ser Meter, IEEE Fou of Brgnenng ond Ron
trata Unser, ies oe
+ of Ferendo O, mu (Congress Seen Cora); hol of Computer une, Laverda
enana de L lt, a Plat going i Corto Pmestgacoms ect de la Po Be
arena
+ Po Hakan Harr (Congres Seen Cone: es Raco, and Den of Computer
‘Digneenng Foc, sharon Monel Umversty lado Hacroncs, eine and Poe” o/Dangn
tomaron bapa Compu” Exgueenng ac, Karke: 128 Conpuer Sey Glam Coro
‘aber non une e adi Barres Une
+ Po Side Wane (Congres Stern Connie) ctor of formation Oypilay and
ton torso (SEL) and retro nes pla and Mme Sa Aston
(CC Dparmen of meno Mage, Cowal ole Dave, Ta, Tran: Que 4.
(EEE sural on Sled ono Corema
+ Po lame Mos (Congres Sue Corton): Pl of IRE: allow of The Neon! Bete of
Arpa: Profesor o Corps? Sone, etna, nd draps on Gen Brea, ree
pero puso San Ouen ocio Diga, OSA
+ Po Jon Yau (Congres Bern Coma asta ad, permet of Computing, The Hong ong
apace Dera, Klon, Hong Kong
We would like © extend our appreciation o the refres, the members of the program commits of
individual sessions, racks, and workshops heir names do ot appear In ths document; they ae std om
ie web sites of individual uch
As Spomsorsatlarge, partes, andlor organizers each of the followings (scparued by semicolons)
provided help for af east ane track of the Congress: Computer Science Research, Easton, and
Applications Pres (CSREAY; US Chapter of World Academy of Science; American Council on Science &
Educaion & Federated Research Council (hipilwwwamericanseorg). In addition, à number of
nivesäy faclly members and the sl names appear on the cover othe se of proceedings) several
publishers ol computer science nd computer engineering boss and journals chape anor ak locos of
Computer science asscitomrganzations rom 3 regions and developers of high-performance machines
and Stems provided significant hep in organizing the conference a wel as proving some resources.
‘We are grateful to them ll
We express our grade o hey, invite, and individual carences and tutorial speakers - e
ls or speaker appear an Ah conference web She. We would alo lke to thank the followings: UCMSS
(Universal Conference Management Systems & Support Califia, USA) for managing all aspects ofthe
conference: Dr. Tim Field of APC for coordinating and managing the pening of the proceedings ad he
Sf of Lunor Hoc (Convention depart) a Las Vegas fo the professional service they provide, Last
ut ot eas we woul ke wo hank the Co-Eior of FECS'I9: Pro Hamid R. Aaa. Po. Leonidas
Deligianni, Pro, Ferando G. Tei, Prol. Quoe-Nam Tran, and Associate Edie, Ad MG Solo.
We preste proceedings of FECS'19,
‘Steering Commitee, 2019
Tap: aierieanese cg!
ton torso (SEL) and retro nes pla and Mme Sa Aston
(CC Dparmen of meno Mage, Cowal ole Dave, Ta, Tran: Que 4.
(EEE sural on Sled ono Corema
+ Po lame Mos (Congres Sue Corton): Pl of IRE: allow of The Neon! Bete of
Arpa: Profesor o Corps? Sone, etna, nd draps on Gen Brea, ree
pero puso San Ouen ocio Diga, OSA
+ Po Jon Yau (Congres Bern Coma asta ad, permet of Computing, The Hong ong
apace Dera, Klon, Hong Kong
We would like © extend our appreciation o the refres, the members of the program commits of
individual sessions, racks, and workshops heir names do ot appear In ths document; they ae std om
ie web sites of individual uch
As Spomsorsatlarge, partes, andlor organizers each of the followings (scparued by semicolons)
provided help for af east ane track of the Congress: Computer Science Research, Easton, and
Applications Pres (CSREAY; US Chapter of World Academy of Science; American Council on Science &
Educaion & Federated Research Council (hipilwwwamericanseorg). In addition, à number of
nivesäy faclly members and the sl names appear on the cover othe se of proceedings) several
publishers ol computer science nd computer engineering boss and journals chape anor ak locos of
Computer science asscitomrganzations rom 3 regions and developers of high-performance machines
and Stems provided significant hep in organizing the conference a wel as proving some resources.
‘We are grateful to them ll
We express our grade o hey, invite, and individual carences and tutorial speakers - e
ls or speaker appear an Ah conference web She. We would alo lke to thank the followings: UCMSS
(Universal Conference Management Systems & Support Califia, USA) for managing all aspects ofthe
conference: Dr. Tim Field of APC for coordinating and managing the pening of the proceedings ad he
Sf of Lunor Hoc (Convention depart) a Las Vegas fo the professional service they provide, Last
ut ot eas we woul ke wo hank the Co-Eior of FECS'I9: Pro Hamid R. Aaa. Po. Leonidas
Deligianni, Pro, Ferando G. Tei, Prol. Quoe-Nam Tran, and Associate Edie, Ad MG Solo.
We preste proceedings of FECS'19,
‘Steering Commitee, 2019
Tap: aierieanese cg!
Contents
‘SESSION: FRONTIERS IN EDUCATION: TEACHING METHODOLOGIES AND
STRATEGIES, ADVISING METHODS, TOOLS AND RELATED STUDIES
Data-Driven Models to Predict Student Performance and Improve Advising in Computer 3
Science
Varick L Erikson
An Introductory Visualization Aid for Cybersecurity Education 10
Gabriel Castro Aguayo, Ulises Morales, Xiaoyu Long, Quamar Nive, Xiao Yang Alma Y Javad
Using a Telepresence Robot in an Educational Context 16
Laurent Gallon, Angel Abenia, Francoise Dubergey, Maite Negui
A Hands-on Oriented Cyber-Learning Curriculum for Undergraduate Cybersecurity 23
Education
Yasranih Koll, Almad Y Javaid
Cognitive Training 3
Mauro Pueblo-Alvare, Daniel Carrillo, Xiao Yang.
Co-construction of Computer Science Knowledge-t-be-taught in a French Context 5
Timothee Duron, Vanea Chiprianen, Laurent Gallon
An Assessment Study on the Teaching of Critical Thinking and Mathematical Proof ina 40
Discrete Structures Course
Hang Dinh
Living with Digital Education: The Impact and Power (or Otherwise) of Information and 47
Communication Technology (ICT) and Internet inthe life of Norfolk State University
Community-An Exploratory Study
Samuel BO Olatuboun Victoria Y. Olanınbasun
Data Manipulation and Visualization (DMV): A Case Study 3
Mudasser . ne, Anshu Chaudhary, Divvanı Doshi, Manjusha Gusain
Preliminary Review - Universities’ Open Source Academic Integrity Poliiesin the UAE 59
Zeenath Reza Khan, Halim Khelalfa Jerahitha Sarabdeen, Prinayka Harish, Sanjana Raheja
‘The Development and Deployment ofa Mobile Music Application for Literacy Enhancement 65
(APPLE)
{Amal Babangida Sabo, Mathias Fonkam, Abubakar Sadiq Hussaini Charles Nche
Collaboration: Key to Student Success in Computing and other STEM Fields in Hispanic 71
‘Serving Institutions
Meline Kevorkian, Greg Sineo
‘SESSION: FRONTIERS IN EDUCATION: TEACHING METHODOLOGIES AND
STRATEGIES, ADVISING METHODS, TOOLS AND RELATED STUDIES
Data-Driven Models to Predict Student Performance and Improve Advising in Computer 3
Science
Varick L Erikson
An Introductory Visualization Aid for Cybersecurity Education 10
Gabriel Castro Aguayo, Ulises Morales, Xiaoyu Long, Quamar Nive, Xiao Yang Alma Y Javad
Using a Telepresence Robot in an Educational Context 16
Laurent Gallon, Angel Abenia, Francoise Dubergey, Maite Negui
A Hands-on Oriented Cyber-Learning Curriculum for Undergraduate Cybersecurity 23
Education
Yasranih Koll, Almad Y Javaid
Cognitive Training 3
Mauro Pueblo-Alvare, Daniel Carrillo, Xiao Yang.
Co-construction of Computer Science Knowledge-t-be-taught in a French Context 5
Timothee Duron, Vanea Chiprianen, Laurent Gallon
An Assessment Study on the Teaching of Critical Thinking and Mathematical Proof ina 40
Discrete Structures Course
Hang Dinh
Living with Digital Education: The Impact and Power (or Otherwise) of Information and 47
Communication Technology (ICT) and Internet inthe life of Norfolk State University
Community-An Exploratory Study
Samuel BO Olatuboun Victoria Y. Olanınbasun
Data Manipulation and Visualization (DMV): A Case Study 3
Mudasser . ne, Anshu Chaudhary, Divvanı Doshi, Manjusha Gusain
Preliminary Review - Universities’ Open Source Academic Integrity Poliiesin the UAE 59
Zeenath Reza Khan, Halim Khelalfa Jerahitha Sarabdeen, Prinayka Harish, Sanjana Raheja
‘The Development and Deployment ofa Mobile Music Application for Literacy Enhancement 65
(APPLE)
{Amal Babangida Sabo, Mathias Fonkam, Abubakar Sadiq Hussaini Charles Nche
Collaboration: Key to Student Success in Computing and other STEM Fields in Hispanic 71
‘Serving Institutions
Meline Kevorkian, Greg Sineo
SESSION: ACCREDITATION, ASSESSMENT METHODS AND STRATEGIES +
CURRICULUM DESIGN AND RELATED ISSUES
Design and Development of a Modular K12 Cybersecurity Curriculum nm
Gin Jai, Ehsan Sheyban, Zachara Pieri
‘Seeking ABET Accreditation: A Case Study in Outcome Assessment a
John Carell
Continuous Improvement Model to Systematize Curricular Processes in the Context of ABET 88
Accreditation
Carolina Zambrano
SESSION: RESEARCH PROJECTS AND CAPSTONE DESIGN PROJECTS
An Internet of Things Drone Data Mule ”
Drew Cochrane, Nolan Evans, Michael Lane, Grant Woodbury Xi Yin, Corey Zrobek, Marcia Friesen,
Ken Ferens
Capstone - Introducing Students to Research through Application Development in Teams 108
Katia Mayfield Mathew Perry, Christopher Pounders, Lucas Prat, Ory Wigingion
Involving Multiple Levels of Students in Software Capstone Project - A Case Study us
Robert Hatch Nicholas Seif
SESSION: COMPUTER SCIENCE AND COMPUTER PROGRAMMING,
‘SOFTWARE ENGINEERING, AND WORK PRACTICES,
Coding VR Games. 13
Jigving Chen, Mehdi R. Zargham, Manibharathi Rajendran, Jie Cheng.
Increasing Student Engagement by Having Them Run Your Test Data Through Their ns
Programs
Donald Selnrart:
Entry-Level Data Science Work Practices and Environments 14
Bill Hefe, Jason Parker, Sourav Chatterjee
‘To GUI or Not to GUE: On How We Teach Introduction to Programming 10
Antonio Sanchez, Bo Mei
CURRICULUM DESIGN AND RELATED ISSUES
Design and Development of a Modular K12 Cybersecurity Curriculum nm
Gin Jai, Ehsan Sheyban, Zachara Pieri
‘Seeking ABET Accreditation: A Case Study in Outcome Assessment a
John Carell
Continuous Improvement Model to Systematize Curricular Processes in the Context of ABET 88
Accreditation
Carolina Zambrano
SESSION: RESEARCH PROJECTS AND CAPSTONE DESIGN PROJECTS
An Internet of Things Drone Data Mule ”
Drew Cochrane, Nolan Evans, Michael Lane, Grant Woodbury Xi Yin, Corey Zrobek, Marcia Friesen,
Ken Ferens
Capstone - Introducing Students to Research through Application Development in Teams 108
Katia Mayfield Mathew Perry, Christopher Pounders, Lucas Prat, Ory Wigingion
Involving Multiple Levels of Students in Software Capstone Project - A Case Study us
Robert Hatch Nicholas Seif
SESSION: COMPUTER SCIENCE AND COMPUTER PROGRAMMING,
‘SOFTWARE ENGINEERING, AND WORK PRACTICES,
Coding VR Games. 13
Jigving Chen, Mehdi R. Zargham, Manibharathi Rajendran, Jie Cheng.
Increasing Student Engagement by Having Them Run Your Test Data Through Their ns
Programs
Donald Selnrart:
Entry-Level Data Science Work Practices and Environments 14
Bill Hefe, Jason Parker, Sourav Chatterjee
‘To GUI or Not to GUE: On How We Teach Introduction to Programming 10
Antonio Sanchez, Bo Mei
SESSION: LEARNING METHODOLOGIES AND COGNITION + DISTANCE
LEARNING, ON-LINE EDUCATION, AND RELATED ISSUES
‘Teaching an International Distributed Discussion-Based Course 19
Jef Off, Birgitta Lindsrom, Kesina Baral
A Hypothetical Model toward Establishing a Relationship between Cognition and 155
“Metacognition in Technology-Enhanced Self-Regulated Learning
‘Mink-Tuen Tran, Shnobu Hasegawa
Finding Big Liars: A Computational Laboratory Challenge 159
Robert D. MeLeod, ue I. Lvols-Merria, Marcia R. Friesen
Developing a Recipe Planning Board Game by Design Thinking Approach 163
‘Shian-Shyong Tzeng, Tng-Yu Yang, ACH Lu
SESSION: POSTER PAPERS AND EXTENDED ABSTRACTS
‘The Considerations for Training Computer Science Chinese International Students in Acadia 171
University
Haiyi Zhang
Active Learning in Computer Networking m
Wendung Hain
‘Outcome and Satisfaction Analysis for Online Exams in an E-learning Class 1
Neflal Watkinson, Lubomir Bic
SESSION: LATE BREAKING PAPERS: STEM EDUCATION, LEARNING
STRATEGIES AND CAPSTONE PROJECTS
Effective Use of Slack and Short Video to Scale Online Learning Communities m
Alexandra Mehlhase, Robert Heinrich, Kevin. Gary
Cybersecurity Capstone Case Study: Closing the Loop on Technology Competency Literacy 186
Lethia Jackson, Velma Latson, Haydar Teymourlouei
BATTLE 2018: Preparation of Future Cyber Technologists ws
Clarence Ray, Jesse Bemley
Investigating Team Etfectiveness Using Discord: A Case Study Using a Gaming Collaboration 199
Tool for the CS Classroom
Lisa L Lacher, Cydnee Biehl
Improving STEM Performance by Leveraging Machine Learning Models 205
Mohamed Aly; Mohammad Rashedul Hasan
LEARNING, ON-LINE EDUCATION, AND RELATED ISSUES
‘Teaching an International Distributed Discussion-Based Course 19
Jef Off, Birgitta Lindsrom, Kesina Baral
A Hypothetical Model toward Establishing a Relationship between Cognition and 155
“Metacognition in Technology-Enhanced Self-Regulated Learning
‘Mink-Tuen Tran, Shnobu Hasegawa
Finding Big Liars: A Computational Laboratory Challenge 159
Robert D. MeLeod, ue I. Lvols-Merria, Marcia R. Friesen
Developing a Recipe Planning Board Game by Design Thinking Approach 163
‘Shian-Shyong Tzeng, Tng-Yu Yang, ACH Lu
SESSION: POSTER PAPERS AND EXTENDED ABSTRACTS
‘The Considerations for Training Computer Science Chinese International Students in Acadia 171
University
Haiyi Zhang
Active Learning in Computer Networking m
Wendung Hain
‘Outcome and Satisfaction Analysis for Online Exams in an E-learning Class 1
Neflal Watkinson, Lubomir Bic
SESSION: LATE BREAKING PAPERS: STEM EDUCATION, LEARNING
STRATEGIES AND CAPSTONE PROJECTS
Effective Use of Slack and Short Video to Scale Online Learning Communities m
Alexandra Mehlhase, Robert Heinrich, Kevin. Gary
Cybersecurity Capstone Case Study: Closing the Loop on Technology Competency Literacy 186
Lethia Jackson, Velma Latson, Haydar Teymourlouei
BATTLE 2018: Preparation of Future Cyber Technologists ws
Clarence Ray, Jesse Bemley
Investigating Team Etfectiveness Using Discord: A Case Study Using a Gaming Collaboration 199
Tool for the CS Classroom
Lisa L Lacher, Cydnee Biehl
Improving STEM Performance by Leveraging Machine Learning Models 205
Mohamed Aly; Mohammad Rashedul Hasan
VRSafe with Augmented and Virtual Reality: Toolkit for Harassment Prevention and. a
Deescalation - Sensitivity, Training and Best Practices
Lamia A. Djoud nu M. Anand, Amoine Lun, Diego Gale, Ana Samedo, Linda Maisano
Deescalation - Sensitivity, Training and Best Practices
Lamia A. Djoud nu M. Anand, Amoine Lun, Diego Gale, Ana Samedo, Linda Maisano
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
SESSION
FRONTIERS IN EDUCATION: TEACHING.
METHODOLOGIES AND STRATEGIES, ADVISING.
METHODS, TOOLS AND RELATED STUDIES
Chair(s)
TBA
ISBN: 1-00132-4987, CSREA Prose ©
SESSION
FRONTIERS IN EDUCATION: TEACHING.
METHODOLOGIES AND STRATEGIES, ADVISING.
METHODS, TOOLS AND RELATED STUDIES
Chair(s)
TBA
ISBN: 1-00132-4987, CSREA Prose ©
Int Cont. Frontier in Education: CS and CE | FECS'9 |
ISBN: 1-00132-4987, CSREA Press ©
ISBN: 1-00132-4987, CSREA Press ©
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
Data-Driven Models to Predict Student Performance
and Improve Advising in Computer Science
Varick L.
Erickson
Computer Science
California Save University, Eau Bay
varient sveastayedy
Abstract As enlinnt in computer. scence (CS) majors
‘omnes to es CS departs ae acing res rere
da scie lager number, «student, improve student
Frio rates and reduce tim o grate, Ne a rev,
tin ten min eral to ear the CS major he
Fit fr student and Yo hb students compete the degree
Ira ina and suce manner Adna, der pay à
rial role en ri students and mara
Students er improe or ql transom 1 ferent major
faving veses fal lesen nd ere depart)
onen iis caning for CS avers tently string
‘Stents crs Oten by thee zer sant ar nti,
those sents have expended a conerable amano tne
‘rat money nthe major when they could hae be
Ping a major mate sae the strengths e present
‘ork ne anale acta emo data ad develop aber
Predicting student perfrmance Blain Ihe dt bad
Ses we cam enya rk dens with up 97% accra
Ise an these made, me also propose upprnches lo improve
‘Maden avis CS andere programe:
Inder emm Ecos Sacer, Role Clason,
Aline Medal
1. ixrmonenon
From 2010-2017, the number of computer science (CS) de
res comer has increased 50.7% [1] While many ses
ase interested in pursuing à CS degree, nt all students re
Prepared or suited othe degree In et 28% of students who
arin CS wil change majo wii he fist tree years [I
Since CS programs are increasingly verre, is cuca
to help students suceed and gradual in à tiely manner.
Silay stents eho are having difhely with he computer
science dore nec to be offered support in oder o quickly
improve or be advised And another major before imesing
100 avi ino the degree, The sooner a student relies that
(CS is mot the ight i the sooner the student can anion 10
à beter Haj, andthe sones the CS department can ree
‘plied space and resources o help aon CS stants
‘Given the increasing enollment and high siden tumorer
in CS dee program ein an aise seine
Many CS stent filo rai that CS the wrong major for
"hem il several semester or even year hve passed. Then
these student fel they ae "10 far lang” 1 change mon
‘While some sugglig dents ao ultimatly ale o complete
the dere, ten takes far moe time and repeating clases
Several ties to complete the depres. Wi low GAS, these
sente may abo have dificult suseeing afer gradation,
roer common rasen for tying in the CS major wo long
IS an ie called identity forests. Identity foreclose
‘fer to stuns whee stadensesalish goals witout es
Sing thorough exploration of options and self election 3)-
Is} Students expenencing entity (oeosure can identify so
Song as CS majo that they rfi o consider aerate
major, even if hese Students are failing CS cours or not
the git Bt forthe program. À eal entity foreclosure
‘nines some denis to view the CS major as their only
‘pion ven if ey ae strong.
Having an academie adviser objcetvely examine cach st
ent performance and advise appropistly has ben shown
to make significant positive impact. Fr example, advising
has bee shown to enable pertence rates (tenon rates) of
53% among underpeeseted students [6 (7. Deel, it
is crea to flag atric students as cay as posible. Once
these stants ar denied, an adviser can lok mare closely
aa stdent’, situation and provide beter guidance. Tiny
and lectivo ads support ean make he difference beeen
Being a sruggling stent stayin he program and ulimaley
Hal cr drop cut helping a sudent By providing access 10
suppor and resources. e helping a student move toa diferent
major
“There ar numerous advantages o an culy major change
Arguably the most important advantage is deceasing de
umber of repstd classes, Stadens who stay 10 ong in the
(CS major often need to repeat course. This means alloted
students face a longer tine required before graduation and
potential financial clleges that could ultimately ead 10
Abandoning an undergraduate degree. Stems who repet
‘source also ted to have lower GPAs even i they replace
à rade or repeat a coure, Based on our data the average CS
(GPA of stents who needed to repeat à CS course one or
oe mes 2.4 (u a 40 scale) In contrast, lens who
‘only needed to take CS courses once ad an average GPA of
sm.
Having sevgglin students repeat courses lo negative af:
Tests CS deparumens and sucessful stants, When signe
Students repeat a cour, fewer seats are aile foe those
taking the couse forthe is ine. Again, having fewer seats
‘avalible an ead oa longer amount of tne spent in school
“and increased financial harden on successful CS student ho
ant lo ein the progam. Thus, when advises are able 10
ISBN: 1-00132-4987, CSREA Press ©
Data-Driven Models to Predict Student Performance
and Improve Advising in Computer Science
Varick L.
Erickson
Computer Science
California Save University, Eau Bay
varient sveastayedy
Abstract As enlinnt in computer. scence (CS) majors
‘omnes to es CS departs ae acing res rere
da scie lager number, «student, improve student
Frio rates and reduce tim o grate, Ne a rev,
tin ten min eral to ear the CS major he
Fit fr student and Yo hb students compete the degree
Ira ina and suce manner Adna, der pay à
rial role en ri students and mara
Students er improe or ql transom 1 ferent major
faving veses fal lesen nd ere depart)
onen iis caning for CS avers tently string
‘Stents crs Oten by thee zer sant ar nti,
those sents have expended a conerable amano tne
‘rat money nthe major when they could hae be
Ping a major mate sae the strengths e present
‘ork ne anale acta emo data ad develop aber
Predicting student perfrmance Blain Ihe dt bad
Ses we cam enya rk dens with up 97% accra
Ise an these made, me also propose upprnches lo improve
‘Maden avis CS andere programe:
Inder emm Ecos Sacer, Role Clason,
Aline Medal
1. ixrmonenon
From 2010-2017, the number of computer science (CS) de
res comer has increased 50.7% [1] While many ses
ase interested in pursuing à CS degree, nt all students re
Prepared or suited othe degree In et 28% of students who
arin CS wil change majo wii he fist tree years [I
Since CS programs are increasingly verre, is cuca
to help students suceed and gradual in à tiely manner.
Silay stents eho are having difhely with he computer
science dore nec to be offered support in oder o quickly
improve or be advised And another major before imesing
100 avi ino the degree, The sooner a student relies that
(CS is mot the ight i the sooner the student can anion 10
à beter Haj, andthe sones the CS department can ree
‘plied space and resources o help aon CS stants
‘Given the increasing enollment and high siden tumorer
in CS dee program ein an aise seine
Many CS stent filo rai that CS the wrong major for
"hem il several semester or even year hve passed. Then
these student fel they ae "10 far lang” 1 change mon
‘While some sugglig dents ao ultimatly ale o complete
the dere, ten takes far moe time and repeating clases
Several ties to complete the depres. Wi low GAS, these
sente may abo have dificult suseeing afer gradation,
roer common rasen for tying in the CS major wo long
IS an ie called identity forests. Identity foreclose
‘fer to stuns whee stadensesalish goals witout es
Sing thorough exploration of options and self election 3)-
Is} Students expenencing entity (oeosure can identify so
Song as CS majo that they rfi o consider aerate
major, even if hese Students are failing CS cours or not
the git Bt forthe program. À eal entity foreclosure
‘nines some denis to view the CS major as their only
‘pion ven if ey ae strong.
Having an academie adviser objcetvely examine cach st
ent performance and advise appropistly has ben shown
to make significant positive impact. Fr example, advising
has bee shown to enable pertence rates (tenon rates) of
53% among underpeeseted students [6 (7. Deel, it
is crea to flag atric students as cay as posible. Once
these stants ar denied, an adviser can lok mare closely
aa stdent’, situation and provide beter guidance. Tiny
and lectivo ads support ean make he difference beeen
Being a sruggling stent stayin he program and ulimaley
Hal cr drop cut helping a sudent By providing access 10
suppor and resources. e helping a student move toa diferent
major
“There ar numerous advantages o an culy major change
Arguably the most important advantage is deceasing de
umber of repstd classes, Stadens who stay 10 ong in the
(CS major often need to repeat course. This means alloted
students face a longer tine required before graduation and
potential financial clleges that could ultimately ead 10
Abandoning an undergraduate degree. Stems who repet
‘source also ted to have lower GPAs even i they replace
à rade or repeat a coure, Based on our data the average CS
(GPA of stents who needed to repeat à CS course one or
oe mes 2.4 (u a 40 scale) In contrast, lens who
‘only needed to take CS courses once ad an average GPA of
sm.
Having sevgglin students repeat courses lo negative af:
Tests CS deparumens and sucessful stants, When signe
Students repeat a cour, fewer seats are aile foe those
taking the couse forthe is ine. Again, having fewer seats
‘avalible an ead oa longer amount of tne spent in school
“and increased financial harden on successful CS student ho
ant lo ein the progam. Thus, when advises are able 10
ISBN: 1-00132-4987, CSREA Press ©
dent and beter sopor ask stent, ll sets and
the department an benef as wel
Inthe present work, we am to improve tent advising by
amazing CS stolen dat, developing predice modes für
student performance, and propsing approsches to improve
aime. Fist. the academic data foe students at California
Sut University, East Bay was compiled and analyzed. Various
modes were applied 1 Keni and predict atrisk students.
Bae on these model, we ar bl o en tk tots
with upto 77% accuracy. Based an these result and di
in the dt, we as propose din approaches to help CS
‘partments ter advise and support ask student
‘We start with a survey of related work in Section I. We
then discuss the chic of variable in Sesion I followed by
ets of dats clin in Scion IV. À preliminary data
alysis is performed in Section V that mothats our model
clin deserve in Sections VI IL and VIL We compare
these modes in Section IX and then show how these model
can he tse in an advisory seing in Section X. Finally, we
‘ican ure workin Section X and summarize ur findings
in Seton XI
ll. RELATED Work
Researchers have studied police modes for succeeding
in CS für over 30 years. Many of thse papers focus on
predicting CS perfomance pir to entering a unver [SJ
[Ho] Authors of (8) temp 10 predict perfomance as he high
School level before emein a university program. Similarly
shor of [10] 100% at tad inde of 62 ems to determine
Tearing writs described by Kolb and Pask [11] in oder 10
predict how igh school stents will perform. Unlike these
Papers, our gal Is o help advisers and cumen CS students
predio sores based on resent performance in CS coun,
In 12) authors use a Tinea repression approach o predict.
ow well students will peu based on pst performance
However, there ae notable differences as compared with our
approach. The author found that a linear regression model
as able to describe hir population, which was CS majors
the US. Al Face Academy. In our case, we determined
à linear regression approach was ot sulble based on our
residual Tis ely that hidden actos ae nar being captured
your dat. Additionally, the authors of [12] se à some
‘cumbersome approach, generating 99 model to capture cach
valid combination of previously taken clases. Our single
‘mode sable 1 cape al combination of clases ten by
treating variables as categorical data rather thn continous
‘dat In the present work; we ao intra à "Wid ot ake”
lake 0 more accurately modal cases where stants did not
‘complete a given course
"The author of [13] have a similar sim as our paper
and focus on ientlying tugging students cuy. To pre
‘it student performance, they use an integrated development
‘envionment (IDE) extension tht continuously logs stan
Coding activities. This IDE clases each students sucess
nd files and ses his data 0 dynamically reine à pre
‘ton model The authors also compare thie approche 10
Int Cont. Frontier in Education: CS and CE | FECS'9 |
os D Sus sd ee
ise sven
TABLE 1; The courses used to pri student sucess. The
Fighimost column i he course name we by the univer
[Noe thatthe courses inthe dase sed the quater sytem,
à similar method described in [14), which aso ules a
Similar dynamically adaptive casier In the presen work.
‘ur approach is simple, oly rein data already collected
by universos and registrars without the use of specialized
plugins Despite the added comple, bth methods examined
fave a maximum of 75% accuracy. ln conta, the models
proposed in Ihe present work achive up o 77% ctucy for
enuying ash students
II. INDICATOR AND RESPONSE VARIABLES
In this seston, we discuss our cheice of indicator and
response variables. Our goal is o be able o predict Student
sees in he major cry sing a model To dine response
Variable, we must Rist at ih our definition of succes
‘There ae many dien posible meics for success. One
posible met is overall GPA for CS course. Another cold
be te time o complet the dere For this paper, we decide
to examine clases mot clos associated wih CS interviews.
In pacar, we wish vo use student perfomance in the Data
‘Stretres couse as our response variable sine interviews
‘olen un comeps fom this course [IS]. Also, Data Sustares
Isa hey prrequis 10 many courses required by th majo.
‘Owe approach is also applicable to measuring acces or
Analysis of Algorithms, which anche popular pie fr CS
Imeriews. However, sine ou gal sto Mag ari students
as cry as publ, we define success in Dt Structure 1 be
ur response variable since Data Stnstures is spa taken
air (uring a students second year
From an alviry perpecive, our aim i o be able to
predica Dat Sıuctures performance a cal as posible, so We
fre able to def and dvi stent ar in the program,
‘Tha, oil choice fr indicate variables would he collected
from required lower division courses that are taken price 40
data cures. Table shows these courses: for cart, we
(fine simplified couse labels rather than we the oil
hey course numbers. Ou pothesis that performance
in these ear class will be bl o predict performance in
Data Statues,
IV. Dara Cotto
‘To measure student succes in these couse, anonymous
regir data was collected rom 924 CS undergraduates
ent as Cao Stat Universi, East Bay (CSUEB) The
‘source were taken between 2012-2018 and used the quer
System, Table I shows the demographics of CS students at
SUE. It important to noe that many of the talents
ISBN: 1-60132-498-7, CSREA Press ©
the department an benef as wel
Inthe present work, we am to improve tent advising by
amazing CS stolen dat, developing predice modes für
student performance, and propsing approsches to improve
aime. Fist. the academic data foe students at California
Sut University, East Bay was compiled and analyzed. Various
modes were applied 1 Keni and predict atrisk students.
Bae on these model, we ar bl o en tk tots
with upto 77% accuracy. Based an these result and di
in the dt, we as propose din approaches to help CS
‘partments ter advise and support ask student
‘We start with a survey of related work in Section I. We
then discuss the chic of variable in Sesion I followed by
ets of dats clin in Scion IV. À preliminary data
alysis is performed in Section V that mothats our model
clin deserve in Sections VI IL and VIL We compare
these modes in Section IX and then show how these model
can he tse in an advisory seing in Section X. Finally, we
‘ican ure workin Section X and summarize ur findings
in Seton XI
ll. RELATED Work
Researchers have studied police modes for succeeding
in CS für over 30 years. Many of thse papers focus on
predicting CS perfomance pir to entering a unver [SJ
[Ho] Authors of (8) temp 10 predict perfomance as he high
School level before emein a university program. Similarly
shor of [10] 100% at tad inde of 62 ems to determine
Tearing writs described by Kolb and Pask [11] in oder 10
predict how igh school stents will perform. Unlike these
Papers, our gal Is o help advisers and cumen CS students
predio sores based on resent performance in CS coun,
In 12) authors use a Tinea repression approach o predict.
ow well students will peu based on pst performance
However, there ae notable differences as compared with our
approach. The author found that a linear regression model
as able to describe hir population, which was CS majors
the US. Al Face Academy. In our case, we determined
à linear regression approach was ot sulble based on our
residual Tis ely that hidden actos ae nar being captured
your dat. Additionally, the authors of [12] se à some
‘cumbersome approach, generating 99 model to capture cach
valid combination of previously taken clases. Our single
‘mode sable 1 cape al combination of clases ten by
treating variables as categorical data rather thn continous
‘dat In the present work; we ao intra à "Wid ot ake”
lake 0 more accurately modal cases where stants did not
‘complete a given course
"The author of [13] have a similar sim as our paper
and focus on ientlying tugging students cuy. To pre
‘it student performance, they use an integrated development
‘envionment (IDE) extension tht continuously logs stan
Coding activities. This IDE clases each students sucess
nd files and ses his data 0 dynamically reine à pre
‘ton model The authors also compare thie approche 10
Int Cont. Frontier in Education: CS and CE | FECS'9 |
os D Sus sd ee
ise sven
TABLE 1; The courses used to pri student sucess. The
Fighimost column i he course name we by the univer
[Noe thatthe courses inthe dase sed the quater sytem,
à similar method described in [14), which aso ules a
Similar dynamically adaptive casier In the presen work.
‘ur approach is simple, oly rein data already collected
by universos and registrars without the use of specialized
plugins Despite the added comple, bth methods examined
fave a maximum of 75% accuracy. ln conta, the models
proposed in Ihe present work achive up o 77% ctucy for
enuying ash students
II. INDICATOR AND RESPONSE VARIABLES
In this seston, we discuss our cheice of indicator and
response variables. Our goal is o be able o predict Student
sees in he major cry sing a model To dine response
Variable, we must Rist at ih our definition of succes
‘There ae many dien posible meics for success. One
posible met is overall GPA for CS course. Another cold
be te time o complet the dere For this paper, we decide
to examine clases mot clos associated wih CS interviews.
In pacar, we wish vo use student perfomance in the Data
‘Stretres couse as our response variable sine interviews
‘olen un comeps fom this course [IS]. Also, Data Sustares
Isa hey prrequis 10 many courses required by th majo.
‘Owe approach is also applicable to measuring acces or
Analysis of Algorithms, which anche popular pie fr CS
Imeriews. However, sine ou gal sto Mag ari students
as cry as publ, we define success in Dt Structure 1 be
ur response variable since Data Stnstures is spa taken
air (uring a students second year
From an alviry perpecive, our aim i o be able to
predica Dat Sıuctures performance a cal as posible, so We
fre able to def and dvi stent ar in the program,
‘Tha, oil choice fr indicate variables would he collected
from required lower division courses that are taken price 40
data cures. Table shows these courses: for cart, we
(fine simplified couse labels rather than we the oil
hey course numbers. Ou pothesis that performance
in these ear class will be bl o predict performance in
Data Statues,
IV. Dara Cotto
‘To measure student succes in these couse, anonymous
regir data was collected rom 924 CS undergraduates
ent as Cao Stat Universi, East Bay (CSUEB) The
‘source were taken between 2012-2018 and used the quer
System, Table I shows the demographics of CS students at
SUE. It important to noe that many of the talents
ISBN: 1-60132-498-7, CSREA Press ©
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
Student Demographics [16] for CS Deparment
TABLE
2017-2018,
ai CSUER ar first geneson college stuns and many of
them also work full or prime while atending univer
While the data in the pesen work captures student courses
taken grs, and GPA the dat se wed in the presen work
‘oes no include any data fr factors such as wheter stat
as working fall or parttime, or weer the stom was a
Fit generation college salen,
Vo PRELIMINARY DATA ANALYSIS
We start the analysis by examining the perfomance cor.
relations among the Tower division courses. Figure 1, shows
the colton mars or the Bet step grades for Data
Statues (Dat), CSL. C92, Calculus 1 (Cal), Calculus 2
(Caled). and Discrete Math (Mat, The diagonal shows the
Pig ofthe grade for he given comme, Itregl, ely
à weak comen l cn between CS! and Data Ststres
(009), However. we d see a stonger coreltion between
Data Structure and C82 (027) A Suprisin observation is
that Callas 2 has a stronger coeation to Dat Structures
than CSI or CS2. Perhaps most notable is that even the
strongest relations are fairly weak Different combinations
Of interactions were alo examined and alo showed sey
‘weak conlatons.
‘While these colon ae weaker than one might expe
there are some posible explanations for this sl. AS men
Rond eri, he dla st used nthe present work copes
‘only sde academic data and docs ot capi extra
actors auch as whether a iden! vas working (llame while
taking cases. Songer colons my be posible if more
ata were avilable,
For cur fit model, we examine a linear regression model
withthe Data trates grado 3 ih esp variable and
the indicator variables rom Table Il using only performance
from CSI and CS2, Nate that he coune ¡rad represented
by a umber fom 104, wih being an "A" or LO grade and
Fig. 1: Comeltion Matis of Data Sinus (Dat). CSI
(C82, Cast 1 (Cake), Callas 2 (Cale). and Discrete
Math (DM) with respect to ist attempt grados. Hee, the
fist atempt grado is plot as a number ranging fom 0
CF) to 4 CAT. Based on this matrix, we see relatively
‘ea creation. There is a maximum of colton of 037
teen Cale? and Dats anda minimum correlation of 009
een CSI and Daa,
‘TABLE Il Perfomance indicators examined for cach class.
O being an Unsupisingly, one ofthe variables showed
ociciens that were statstillysigniean In addition, à
plo ofthe residuals (ce Figure 2) idiats that there is key
fre one or more hidden indieatrvaribls por hing capte
that re needed o acutely pre Data Statues grades.
“This cou include variables such as how many hours the
student works er week ho fa he suden has to commute
or oler actors not present or easily determined wäh he
existing data. These ress show at à sear made is ot
Suitable for predicting Teter grades in the data structures
Sour feast not wih the current data se
Inch, we expect pat perfomance in clases o offer
some prie measures, Rater than predict gras, we
instead ook at the probaly o passing (aching à grade af
{Cor bete, Table IV shows Several conditional probabilities
‘of posin Data Stuctures given the students performance in
past clases, For example, a tuent als CSL in the pas.
ISBN: 1-60132-498-7, CSREA Press ©
Student Demographics [16] for CS Deparment
TABLE
2017-2018,
ai CSUER ar first geneson college stuns and many of
them also work full or prime while atending univer
While the data in the pesen work captures student courses
taken grs, and GPA the dat se wed in the presen work
‘oes no include any data fr factors such as wheter stat
as working fall or parttime, or weer the stom was a
Fit generation college salen,
Vo PRELIMINARY DATA ANALYSIS
We start the analysis by examining the perfomance cor.
relations among the Tower division courses. Figure 1, shows
the colton mars or the Bet step grades for Data
Statues (Dat), CSL. C92, Calculus 1 (Cal), Calculus 2
(Caled). and Discrete Math (Mat, The diagonal shows the
Pig ofthe grade for he given comme, Itregl, ely
à weak comen l cn between CS! and Data Ststres
(009), However. we d see a stonger coreltion between
Data Structure and C82 (027) A Suprisin observation is
that Callas 2 has a stronger coeation to Dat Structures
than CSI or CS2. Perhaps most notable is that even the
strongest relations are fairly weak Different combinations
Of interactions were alo examined and alo showed sey
‘weak conlatons.
‘While these colon ae weaker than one might expe
there are some posible explanations for this sl. AS men
Rond eri, he dla st used nthe present work copes
‘only sde academic data and docs ot capi extra
actors auch as whether a iden! vas working (llame while
taking cases. Songer colons my be posible if more
ata were avilable,
For cur fit model, we examine a linear regression model
withthe Data trates grado 3 ih esp variable and
the indicator variables rom Table Il using only performance
from CSI and CS2, Nate that he coune ¡rad represented
by a umber fom 104, wih being an "A" or LO grade and
Fig. 1: Comeltion Matis of Data Sinus (Dat). CSI
(C82, Cast 1 (Cake), Callas 2 (Cale). and Discrete
Math (DM) with respect to ist attempt grados. Hee, the
fist atempt grado is plot as a number ranging fom 0
CF) to 4 CAT. Based on this matrix, we see relatively
‘ea creation. There is a maximum of colton of 037
teen Cale? and Dats anda minimum correlation of 009
een CSI and Daa,
‘TABLE Il Perfomance indicators examined for cach class.
O being an Unsupisingly, one ofthe variables showed
ociciens that were statstillysigniean In addition, à
plo ofthe residuals (ce Figure 2) idiats that there is key
fre one or more hidden indieatrvaribls por hing capte
that re needed o acutely pre Data Statues grades.
“This cou include variables such as how many hours the
student works er week ho fa he suden has to commute
or oler actors not present or easily determined wäh he
existing data. These ress show at à sear made is ot
Suitable for predicting Teter grades in the data structures
Sour feast not wih the current data se
Inch, we expect pat perfomance in clases o offer
some prie measures, Rater than predict gras, we
instead ook at the probaly o passing (aching à grade af
{Cor bete, Table IV shows Several conditional probabilities
‘of posin Data Stuctures given the students performance in
past clases, For example, a tuent als CSL in the pas.
ISBN: 1-60132-498-7, CSREA Press ©
PDC Sas)
Pia Es)
Diamar hd CS)
aa Cala = 20%
ra Cat) = 03210
Pa] ét
TABLE IV: Calculated conditional probables of passing.
Data Stoctures given fret scenarios,
Fig. 2: The resis plot shows violation of nca. The
linear rend of residuals indicates there are likely hidden
variables ot accounted fr by the linear regression model
e see thatthe student has a pobuiliy of 02768 (about
28% chance) of pasing Data Strocures We see a similar
Sats foe C52 wih 0.2656 probability about 27% chance)
of passing Data Sites if the student previously fled
SÍ. Unsuvisingly. à student who Fale bath CSI and C82
in the past has an even lower probability 0.1667 (about
17% chance) of pasing Daa Sete. Iteresingy. Cle]
and Cale2 courses show similar condiona probabiiis as
‘compared wäh the CSI and CS2 condiioal probabil,
Stade who al Cale! have 402676 probity about 27%
chance) of passing Data Structures. Given a student fled
Cale, the student has a 0.3219 probability of pasung Di
Saut. Y the student fal ath Cale] and Cal, then
the student has a 01951 probably (about 20% chance) of
passing Data Sectores. This nil result shows that cry
rade can indeed be a sel predictor of dent performance
In une courses
Vi. Mopet SELECTION
Rather than predic student grades or dla sites, we
instead chooe o preci whether deis ar abe o pas
Data Stctue. Since we ae atempüng to pri ia student
will pas Data Status based on pas as performance, we
con formule this à lesion problem a this sein,
e examine two diferent strategies for reiting whether à
Student wil pass hos onthe grades of tee previ ten
ou. In particular, we examine logit epesion (LR) and
Support vector machine (SVM) clasieaton models. For our
indir variables, we we the ntl grades for CSI, CS:
Cscals 1, Calculus 2, and Linear Algebra. Our response
Int Cont. Frontier in Education: CS and CE | FECS'9 |
variables binary indicator wheter or not he student would
pass Data Stctres given thei inal gras.
‘One iste 10 consider is he diferem combinations of
cases that students can take. Depending on the order that
the clases ae taken, we would need a model specie 1 the
ven permutation. For example. i student takes CSI on,
then the mode predicting the performance of Daa Sites
woul be the single indicator variable using the CSI grade
Simla, ia student has taken Call and CSI bat none of
the other courses, then we need a model with Cael and CSI
indicator variables for prediction. While class preroquisites
o reduce the number ol possible permutations, this multiple
mode approach would rege numerous modas 0 cate
‘ich station. To avoid this ise, we instead tet cach
Variable as a ctegorcal table wäh each grade being à
ern classifi label
VIL. Looisttc Reoressiow:
‘Tae fist model we will examine ia logistic represion
mode, which wes loge function o predict a binary sale
For this model, we dee the loss function 110 be,
Te yt Br + + Bat o
Where ae bela clients or te parameters ofthe mode
and 2 isthe vale of the indicator variable j Yor 1< ©
Using. we ca calculate the probability» o binary value of
response variable by calling
» a
re
As previously discussed, instead of wating the css grade
a à comimos variable and hve a different mols or cach
Permutation. we instead interpret the grade as à categorical
Variable with 13 dire tego: F Ds. D, Ds, CC,
Ce, B, Bs, A, A, and "de not ll”, The advantage ol
this aproue is that alows Fr diferent combinations of
clases 10 be capred by à Single model. To const this
model, we cree 12 "day" variables fo ech class. Ta,
tte deine the model La
Tot
POSI + CH
BisCS2p + PCSI +
BaCalely + BuCalel- +
Cal + BaCaledn +
abs + ob. +
Sp ++ Chr
+ BC+
+ BaGalela+
+ BaCaleat
o
+ Baba
Where are bela octets for te parameter ofthe made
and À the root C1, CS2,, Calely, Caley, and
TL are Vi they reed grade y 0 Oi they did mt the
‘ident di no take the clas a al, then, cach ae 0. For
sample, à student did not ake Call, then for each vale
OF Caley BO for g = BDA
ISBN: 1-60132-498-7, CSREA Press ©
Pia Es)
Diamar hd CS)
aa Cala = 20%
ra Cat) = 03210
Pa] ét
TABLE IV: Calculated conditional probables of passing.
Data Stoctures given fret scenarios,
Fig. 2: The resis plot shows violation of nca. The
linear rend of residuals indicates there are likely hidden
variables ot accounted fr by the linear regression model
e see thatthe student has a pobuiliy of 02768 (about
28% chance) of pasing Data Strocures We see a similar
Sats foe C52 wih 0.2656 probability about 27% chance)
of passing Data Sites if the student previously fled
SÍ. Unsuvisingly. à student who Fale bath CSI and C82
in the past has an even lower probability 0.1667 (about
17% chance) of pasing Daa Sete. Iteresingy. Cle]
and Cale2 courses show similar condiona probabiiis as
‘compared wäh the CSI and CS2 condiioal probabil,
Stade who al Cale! have 402676 probity about 27%
chance) of passing Data Structures. Given a student fled
Cale, the student has a 0.3219 probability of pasung Di
Saut. Y the student fal ath Cale] and Cal, then
the student has a 01951 probably (about 20% chance) of
passing Data Sectores. This nil result shows that cry
rade can indeed be a sel predictor of dent performance
In une courses
Vi. Mopet SELECTION
Rather than predic student grades or dla sites, we
instead chooe o preci whether deis ar abe o pas
Data Stctue. Since we ae atempüng to pri ia student
will pas Data Status based on pas as performance, we
con formule this à lesion problem a this sein,
e examine two diferent strategies for reiting whether à
Student wil pass hos onthe grades of tee previ ten
ou. In particular, we examine logit epesion (LR) and
Support vector machine (SVM) clasieaton models. For our
indir variables, we we the ntl grades for CSI, CS:
Cscals 1, Calculus 2, and Linear Algebra. Our response
Int Cont. Frontier in Education: CS and CE | FECS'9 |
variables binary indicator wheter or not he student would
pass Data Stctres given thei inal gras.
‘One iste 10 consider is he diferem combinations of
cases that students can take. Depending on the order that
the clases ae taken, we would need a model specie 1 the
ven permutation. For example. i student takes CSI on,
then the mode predicting the performance of Daa Sites
woul be the single indicator variable using the CSI grade
Simla, ia student has taken Call and CSI bat none of
the other courses, then we need a model with Cael and CSI
indicator variables for prediction. While class preroquisites
o reduce the number ol possible permutations, this multiple
mode approach would rege numerous modas 0 cate
‘ich station. To avoid this ise, we instead tet cach
Variable as a ctegorcal table wäh each grade being à
ern classifi label
VIL. Looisttc Reoressiow:
‘Tae fist model we will examine ia logistic represion
mode, which wes loge function o predict a binary sale
For this model, we dee the loss function 110 be,
Te yt Br + + Bat o
Where ae bela clients or te parameters ofthe mode
and 2 isthe vale of the indicator variable j Yor 1< ©
Using. we ca calculate the probability» o binary value of
response variable by calling
» a
re
As previously discussed, instead of wating the css grade
a à comimos variable and hve a different mols or cach
Permutation. we instead interpret the grade as à categorical
Variable with 13 dire tego: F Ds. D, Ds, CC,
Ce, B, Bs, A, A, and "de not ll”, The advantage ol
this aproue is that alows Fr diferent combinations of
clases 10 be capred by à Single model. To const this
model, we cree 12 "day" variables fo ech class. Ta,
tte deine the model La
Tot
POSI + CH
BisCS2p + PCSI +
BaCalely + BuCalel- +
Cal + BaCaledn +
abs + ob. +
Sp ++ Chr
+ BC+
+ BaGalela+
+ BaCaleat
o
+ Baba
Where are bela octets for te parameter ofthe made
and À the root C1, CS2,, Calely, Caley, and
TL are Vi they reed grade y 0 Oi they did mt the
‘ident di no take the clas a al, then, cach ae 0. For
sample, à student did not ake Call, then for each vale
OF Caley BO for g = BDA
ISBN: 1-60132-498-7, CSREA Press ©
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
Vin. SumoRr VECTOR MACHINE
‘The nex clasiistion model tested is a Linear Support
Vector Machine (SVM). This mode isa supervised Teaming
method that a to make a lassen to specie group
ven an np vor. Une the logit repression moda, e
IS a non-probsbilisic and doesnot atch a probably 1 a
lation. Fo nis model we deine cu ning data as
) o
zu (td
where 2 sa veto of categorical inputs
(CSI CS,
CS2r 052
Caletps.--,CaleLa,
Cale, Cals,
Lor La)
with cach positon in vector zu a WI indicator whether the
Student received a given grade for a ess This i essentially
the same input vector usd by the previous LR model For
‘example, if he siden received an À for CSI, then the aloe
OF CSI 4 is and all er values of CSI, is 0 for 9
FL... A. Again if the stent did ost e cas ar al
then ll te values for that particular class are O. y, ia 1
‘or label specfying what clas belongs for data pont i,
Using the wining data in equation d we finda houndar Tine
satistying
usb o
Where w is vector normal lo the ie, This boundary line
“ln by equation $ allows us 10 classify new daa points,
1x. Monet Comparison
In this seston, we examine and compare cach model In
parol we will be examining the ROC (Receiver Opening
‘Chuacteritis) curve, the AUC (area under the curv). and
the confusion matrix. The AUC and ROC curve ae Gal
Performance measurements for classifies as ey show how
‘ell he mode is capable of distinguishing the diferent classes
Li Ei or case, we are dtemining howell the model can
‘etemine ia student will pss o al Data Sites. An
[AUC value of 1 indicates perfect classification. This metic
is particle sea for comparing two dient class.
‘The otter merc we us is posive price vals and fase
discovery ft, which can be derived fom à confusion mat.
“The postive predictive value (PPV) isthe probability that he
Student who i predicted to al data tre does ined fail.
the clas The fae discover rte (FDR) isthe complement
of the PPV (DR = 12 PPV),
Figure Su shows the results of the LR model. We see
thatthe AUC is 0.67 andthe PPV is 77% for failing and
51% foe passing. This inies ha à soe predicted o
Fai daa etre wil with 77% probably hil he couse
Similarly. show a student predicted to pas wil pus with
51% probability. Fiure show the resul of the SVM
mode. For this model we see the AUC is sil higher
with an AUC of 0.78 as compare with the LR model: this
Indices the SVM a beter las Interestingly, the SVM.
model shows the same PPV asthe LR model, The SVM is
able o pret with 77% probably if stadens will indeed
Fal dat metres. However. the SVM is beter abet rect.
students passing data structures with 87% PPV for preci
¡Etude wil pass data suture.
‘As our amis to identify dents He} fi, we sos that
both LR and SVM have the same predicon probability for
reiting à sten ling data Srcturs. A the SVM does
“hey beter clsiying students who pass and also has à
higher AUC, we consider the SVM à beter rotin model
x. Monet Uniizanion
In his section, we explore how the SVM peeicion model
is ble o be uted fr advising. We fst examine the impact.
‘ofcourse repeats on GPA ad the sels sll for sont
‘Table V shows several statin of interest. The fist color
shows the average number of ines stent tempt à pat
bar cos. We sce that on average stants ke CSI 1143
times, This is significant since st means that apprximstely
14.3% ofthe seas in a given semesters ecupied by someone
repeating the cours, We find similar rus for CS2 where
the average number of repeats 1149, Data tracts, Linear
Algebra, and Cale? have average repeats of 1.16, 1.160, and
1.17 respectively. The highest average for couse repeat s
for Call with an average of 1207. These sais support
tha a mon via number of coune repeats ae occuring und
‘fore the need ooo: the number o tdens repeating à
‘course though advising. The second column of Table V shows
the average GPA ofa coune ale epeting the couse, This
is calculated by fading the maximum grade fom all temps
“and verging this aros al stant The hid column shows
the aterage GPA o stants who only take the course à single
time. We sce across a courses that sten who need 10
repeat the coune on average will cam a homer grade that
Stents who oly tke the coune once Tis implies tha even
ita student repeats a cours, iis Hey they will cam a lower
‘rade compared toa student who only need to ae the course
Our next anis examines sever ferent strategies for
vaca the modes. We alo examine how beter alvsing
TABLE V This table shows the average number of repeats
and the impact repeating cases Ras on student GPA. The
Fir column shows the average number of repeats per one.
‘The second ola shows the average GPA of students they
choose o repeat couse. The hil column shows the average
{GPA of students when they ned 10 a the course only one
ISBN: 1-60132-498-7, CSREA Press ©
Vin. SumoRr VECTOR MACHINE
‘The nex clasiistion model tested is a Linear Support
Vector Machine (SVM). This mode isa supervised Teaming
method that a to make a lassen to specie group
ven an np vor. Une the logit repression moda, e
IS a non-probsbilisic and doesnot atch a probably 1 a
lation. Fo nis model we deine cu ning data as
) o
zu (td
where 2 sa veto of categorical inputs
(CSI CS,
CS2r 052
Caletps.--,CaleLa,
Cale, Cals,
Lor La)
with cach positon in vector zu a WI indicator whether the
Student received a given grade for a ess This i essentially
the same input vector usd by the previous LR model For
‘example, if he siden received an À for CSI, then the aloe
OF CSI 4 is and all er values of CSI, is 0 for 9
FL... A. Again if the stent did ost e cas ar al
then ll te values for that particular class are O. y, ia 1
‘or label specfying what clas belongs for data pont i,
Using the wining data in equation d we finda houndar Tine
satistying
usb o
Where w is vector normal lo the ie, This boundary line
“ln by equation $ allows us 10 classify new daa points,
1x. Monet Comparison
In this seston, we examine and compare cach model In
parol we will be examining the ROC (Receiver Opening
‘Chuacteritis) curve, the AUC (area under the curv). and
the confusion matrix. The AUC and ROC curve ae Gal
Performance measurements for classifies as ey show how
‘ell he mode is capable of distinguishing the diferent classes
Li Ei or case, we are dtemining howell the model can
‘etemine ia student will pss o al Data Sites. An
[AUC value of 1 indicates perfect classification. This metic
is particle sea for comparing two dient class.
‘The otter merc we us is posive price vals and fase
discovery ft, which can be derived fom à confusion mat.
“The postive predictive value (PPV) isthe probability that he
Student who i predicted to al data tre does ined fail.
the clas The fae discover rte (FDR) isthe complement
of the PPV (DR = 12 PPV),
Figure Su shows the results of the LR model. We see
thatthe AUC is 0.67 andthe PPV is 77% for failing and
51% foe passing. This inies ha à soe predicted o
Fai daa etre wil with 77% probably hil he couse
Similarly. show a student predicted to pas wil pus with
51% probability. Fiure show the resul of the SVM
mode. For this model we see the AUC is sil higher
with an AUC of 0.78 as compare with the LR model: this
Indices the SVM a beter las Interestingly, the SVM.
model shows the same PPV asthe LR model, The SVM is
able o pret with 77% probably if stadens will indeed
Fal dat metres. However. the SVM is beter abet rect.
students passing data structures with 87% PPV for preci
¡Etude wil pass data suture.
‘As our amis to identify dents He} fi, we sos that
both LR and SVM have the same predicon probability for
reiting à sten ling data Srcturs. A the SVM does
“hey beter clsiying students who pass and also has à
higher AUC, we consider the SVM à beter rotin model
x. Monet Uniizanion
In his section, we explore how the SVM peeicion model
is ble o be uted fr advising. We fst examine the impact.
‘ofcourse repeats on GPA ad the sels sll for sont
‘Table V shows several statin of interest. The fist color
shows the average number of ines stent tempt à pat
bar cos. We sce that on average stants ke CSI 1143
times, This is significant since st means that apprximstely
14.3% ofthe seas in a given semesters ecupied by someone
repeating the cours, We find similar rus for CS2 where
the average number of repeats 1149, Data tracts, Linear
Algebra, and Cale? have average repeats of 1.16, 1.160, and
1.17 respectively. The highest average for couse repeat s
for Call with an average of 1207. These sais support
tha a mon via number of coune repeats ae occuring und
‘fore the need ooo: the number o tdens repeating à
‘course though advising. The second column of Table V shows
the average GPA ofa coune ale epeting the couse, This
is calculated by fading the maximum grade fom all temps
“and verging this aros al stant The hid column shows
the aterage GPA o stants who only take the course à single
time. We sce across a courses that sten who need 10
repeat the coune on average will cam a homer grade that
Stents who oly tke the coune once Tis implies tha even
ita student repeats a cours, iis Hey they will cam a lower
‘rade compared toa student who only need to ae the course
Our next anis examines sever ferent strategies for
vaca the modes. We alo examine how beter alvsing
TABLE V This table shows the average number of repeats
and the impact repeating cases Ras on student GPA. The
Fir column shows the average number of repeats per one.
‘The second ola shows the average GPA of students they
choose o repeat couse. The hil column shows the average
{GPA of students when they ned 10 a the course only one
ISBN: 1-60132-498-7, CSREA Press ©
Int Cont. Frontier in Education: CS and CE | FECS'9 |
F
qu 1.
1 is 1 ax
‘rat E ‘pai Ebro
one Pee Ve CETTE) Poe Pete Vale (SET TIE]
Fate Dice Rate IMEI] Fake Diner Rate CRETE
(a) Te fs pa sow the ROC plot and AUC ae forte logic
‘reson mos The sco sows the nf mas fre
An repr moll and the psi pede ve
ould affect the average pass rte of dat strates and
the numberof seas that woul become availble. The int
proposed strategy is initing à ele allowing students 10
Fepeat inodacio courses a maximum o two times. In her
words, ia student did no pas an intoducor cone aer
180 atempi, they would Be advised lo pursue à dile
major or not to conime the program. Table VI shows the
‘eat sed nd potently saved applying this resol. The
Fit column shows the number of penal save sets The
second column shows he ia number of st cup or a
parol cls. For CSI, we found 7 students who took CSI
{wo mare or more mes meaning 7 seats would be saved in
ths sio. We found roughly twice as many potential seats
in CS2 with 5 saved, Data care we found 17 potently
saved seas. Cale, we found the most number of potently
‘ved seat we fund 18 CS stents repeating the ss more
than twice. For Cale? and linear alga. we fund 12 and
13 potentially sve eats respectively. The nexo as rom
‘of Table VI shows that the maximum number of sved sexs
in total 153 (or 33% of the Wal number of sets). Note
that the maximum number of saved seats is higher than dhe
sum ofthe lasses individually. This is Because stents ho
repeat an care clas would no ake subsequent clases, For
‘example, à student who unsucesfaly attempt CSI twice
‘woul not aemp any other prerequisite courses. The ist
Sows à potential savings of 8244,00 dollars in ion cost
‘over SK years assuming an ost of $1,600 per class. which
(9) THe fst pot sons the ROC plot and AUC vale fo the
‘Svat moda, e std shows the conf mari fr he SUM
ape mols and he poe peste al
isa savings of approximately 40K per year. While this ist,
Ace) docs improve the number of potential sea, alo
‘Goes not ales students who conser repeat vue. For
example, a who routinely takes courses tie also indices à
red for visi
‘Our second ste is expands the fist stay by alo
taking imo account ota number of repeated courses. able
VIT shows the resul of imposing diferent thresholds allowed
for musimum number of repeated courses wile il imposing
a 000 atempL maximum for any Tower division course. The
Fist row shows 137 stent a to repeat 2 or mor comes
YE is es were applied, hen 137 students would eed
‘alvising and we would potatally save 369 seas (8% of
the tou sets) poil sing $590.40 this is arguably 00
aggressive a esol and nt practical. The second row shows
40 stems had 1 repeat 3 0e mare courses. Applying this
"testo would lead to potentially saving 18 seats (40% of
the ttl cas) ad ving potentially S204A00: his rule as
31 aldol sas as compared wih the two amp strategy
“Thin resold soem to be the mos reasonable, Thess
‘of only shows 8 students meting thn thesold. We ako
See in his rule only ads 2 addtional seats over the o mi
ae and saving only $3,200 additional dolar. Similar
‘nly 2 udn meet the $ repeat threshold and no atonal
Seas were panedas opposed lo he uo temp strategy alone.
‘Therefor, based on thi data, we find that imposing init of
two repeats pr course and hre epeats animus across ll
ISBN: 1-60132-498-7, CSREA Press ©
F
qu 1.
1 is 1 ax
‘rat E ‘pai Ebro
one Pee Ve CETTE) Poe Pete Vale (SET TIE]
Fate Dice Rate IMEI] Fake Diner Rate CRETE
(a) Te fs pa sow the ROC plot and AUC ae forte logic
‘reson mos The sco sows the nf mas fre
An repr moll and the psi pede ve
ould affect the average pass rte of dat strates and
the numberof seas that woul become availble. The int
proposed strategy is initing à ele allowing students 10
Fepeat inodacio courses a maximum o two times. In her
words, ia student did no pas an intoducor cone aer
180 atempi, they would Be advised lo pursue à dile
major or not to conime the program. Table VI shows the
‘eat sed nd potently saved applying this resol. The
Fit column shows the number of penal save sets The
second column shows he ia number of st cup or a
parol cls. For CSI, we found 7 students who took CSI
{wo mare or more mes meaning 7 seats would be saved in
ths sio. We found roughly twice as many potential seats
in CS2 with 5 saved, Data care we found 17 potently
saved seas. Cale, we found the most number of potently
‘ved seat we fund 18 CS stents repeating the ss more
than twice. For Cale? and linear alga. we fund 12 and
13 potentially sve eats respectively. The nexo as rom
‘of Table VI shows that the maximum number of sved sexs
in total 153 (or 33% of the Wal number of sets). Note
that the maximum number of saved seats is higher than dhe
sum ofthe lasses individually. This is Because stents ho
repeat an care clas would no ake subsequent clases, For
‘example, à student who unsucesfaly attempt CSI twice
‘woul not aemp any other prerequisite courses. The ist
Sows à potential savings of 8244,00 dollars in ion cost
‘over SK years assuming an ost of $1,600 per class. which
(9) THe fst pot sons the ROC plot and AUC vale fo the
‘Svat moda, e std shows the conf mari fr he SUM
ape mols and he poe peste al
isa savings of approximately 40K per year. While this ist,
Ace) docs improve the number of potential sea, alo
‘Goes not ales students who conser repeat vue. For
example, a who routinely takes courses tie also indices à
red for visi
‘Our second ste is expands the fist stay by alo
taking imo account ota number of repeated courses. able
VIT shows the resul of imposing diferent thresholds allowed
for musimum number of repeated courses wile il imposing
a 000 atempL maximum for any Tower division course. The
Fist row shows 137 stent a to repeat 2 or mor comes
YE is es were applied, hen 137 students would eed
‘alvising and we would potatally save 369 seas (8% of
the tou sets) poil sing $590.40 this is arguably 00
aggressive a esol and nt practical. The second row shows
40 stems had 1 repeat 3 0e mare courses. Applying this
"testo would lead to potentially saving 18 seats (40% of
the ttl cas) ad ving potentially S204A00: his rule as
31 aldol sas as compared wih the two amp strategy
“Thin resold soem to be the mos reasonable, Thess
‘of only shows 8 students meting thn thesold. We ako
See in his rule only ads 2 addtional seats over the o mi
ae and saving only $3,200 additional dolar. Similar
‘nly 2 udn meet the $ repeat threshold and no atonal
Seas were panedas opposed lo he uo temp strategy alone.
‘Therefor, based on thi data, we find that imposing init of
two repeats pr course and hre epeats animus across ll
ISBN: 1-60132-498-7, CSREA Press ©
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
Pe
TABLE Vi: This able shows how many potential ets can be
saved sing limi of (no atempis fr a las. Compound,
this would sive 153 sets (33% ofthe ta eat) In clases al
dents who would otherwise would be atemping a course
Tor a ind or more times, This would sve approximately
$243.00 nto over about sx years
TABLE VI: This table shows how many potent sats can be
saved if we impose rations on course repeats i aon
10.3 two aemp per cou retin. Fach ow shows how
many sents repeated courses a given maximum pest
¡resol and the potential for saving seas, For example,
in row 1, we see 137 students needed lo repeat at least 2
prereqisic courses during tee depor
inrodocoy courses would be a good ist sept help reduce
the numberof repeated courses, Student at A of iting the
limits on repeated cores could he Maggi inthe system and
“leo addtional adviser support
XL FUTURE Work
“Tse predictive model offer a useful means to Mg sm
ling students erie nti academic carers. I is important
to moe that while the models are able o predict whether à
Student wil fail Data Sites wäh upto 77% acurcy the
modes were less acura in predicting whether a toot will
pss Data Shure. These models therfore shou be used as
Fools in combination with cher information in ode o make
the test possible recommendation 10 students Tor advising.
For example, fa Student has a low probably of passing
Data Statues given tee past performance, an ads could
also look at whether the student is also working full-time,
wheter the sent has acess 1 supporting resources and
‘ter factor in oder o provide he Best posible guidance
‘Another interesting observation ss CS students tended to
fai and repeat the cacas and nar algebra courses twice
as olln asthe CS cours. AS mentioned cain, students
‘who fled both calculos 1 and I had only a 20% chance
of passing Data Surturs. Future work could investigate
‘ational ndictos of success ad ety approches o help
Strugaingstdens beer perfor in hese classes
‘While the focus of the coment work was to prod a
Fisk stents early on by focusing on the Data Strtres
‘couse, future work could also examine whether a similar
“approch could be applied o the Analysis of Algoridms
‘course and ther upper division courses. Adina. ould
be interesting o tempt to capture other variables in the data
sa, such as wheher a sun! was working fulsime or was
fin generation nen, o emp to prose Ihe mc
nally, future work should explore actions advisers and
‘parents can take o Beer suppor students based on he
prediction and data inthis paper For example, it could be
beneficial o explore the impact of offering beter acces 10
tutoring or ober suport ro implement patent polices
Lo more si enforce prerequisites and minimum grades for
‘ileal courses in CS. By combining the leaning in be present
ok with improved adas and spot, CS advisers and
department can make significa progres in improving time
to graduate, redacng overroding. and inproning radeon
XII, Coneuuston
In is pope, we explore two diferen clasication based
proton models for predicting CS sucess and ¡defina
dents in need of advising. We show that we are able lo
den students with high sk of Fl with 776% accua
By uilzing these models and the recommended alvsing
approches, we show Ut we could potentially die the
umber of repesed courses by 40% make 184 aon
seats available for other Students, and save approximately
SISOK forthe 924 stant in the sd.
REFERENCES
10 Den Bint Sats.
a xan Na Cen er cae Sa 27.
1 RES oy Sie hs hg
10 tea Hac q ae: Se
ow Bina Mein gm
na Scr eons 2 Be cpu
to PE ero ito Pg
e ar
tio RENT Dean ein “Ping em in
‘ry ce bee og ss
vu BE eligi oman
111 Gt Nebo Can Me Cling haine. Ceo. 288
18 Lt Rei pws coc coca ea
eevee a rd
ER ri OC a
ISBN: 1-60132-498.7, CSREA Press ©
Pe
TABLE Vi: This able shows how many potential ets can be
saved sing limi of (no atempis fr a las. Compound,
this would sive 153 sets (33% ofthe ta eat) In clases al
dents who would otherwise would be atemping a course
Tor a ind or more times, This would sve approximately
$243.00 nto over about sx years
TABLE VI: This table shows how many potent sats can be
saved if we impose rations on course repeats i aon
10.3 two aemp per cou retin. Fach ow shows how
many sents repeated courses a given maximum pest
¡resol and the potential for saving seas, For example,
in row 1, we see 137 students needed lo repeat at least 2
prereqisic courses during tee depor
inrodocoy courses would be a good ist sept help reduce
the numberof repeated courses, Student at A of iting the
limits on repeated cores could he Maggi inthe system and
“leo addtional adviser support
XL FUTURE Work
“Tse predictive model offer a useful means to Mg sm
ling students erie nti academic carers. I is important
to moe that while the models are able o predict whether à
Student wil fail Data Sites wäh upto 77% acurcy the
modes were less acura in predicting whether a toot will
pss Data Shure. These models therfore shou be used as
Fools in combination with cher information in ode o make
the test possible recommendation 10 students Tor advising.
For example, fa Student has a low probably of passing
Data Statues given tee past performance, an ads could
also look at whether the student is also working full-time,
wheter the sent has acess 1 supporting resources and
‘ter factor in oder o provide he Best posible guidance
‘Another interesting observation ss CS students tended to
fai and repeat the cacas and nar algebra courses twice
as olln asthe CS cours. AS mentioned cain, students
‘who fled both calculos 1 and I had only a 20% chance
of passing Data Surturs. Future work could investigate
‘ational ndictos of success ad ety approches o help
Strugaingstdens beer perfor in hese classes
‘While the focus of the coment work was to prod a
Fisk stents early on by focusing on the Data Strtres
‘couse, future work could also examine whether a similar
“approch could be applied o the Analysis of Algoridms
‘course and ther upper division courses. Adina. ould
be interesting o tempt to capture other variables in the data
sa, such as wheher a sun! was working fulsime or was
fin generation nen, o emp to prose Ihe mc
nally, future work should explore actions advisers and
‘parents can take o Beer suppor students based on he
prediction and data inthis paper For example, it could be
beneficial o explore the impact of offering beter acces 10
tutoring or ober suport ro implement patent polices
Lo more si enforce prerequisites and minimum grades for
‘ileal courses in CS. By combining the leaning in be present
ok with improved adas and spot, CS advisers and
department can make significa progres in improving time
to graduate, redacng overroding. and inproning radeon
XII, Coneuuston
In is pope, we explore two diferen clasication based
proton models for predicting CS sucess and ¡defina
dents in need of advising. We show that we are able lo
den students with high sk of Fl with 776% accua
By uilzing these models and the recommended alvsing
approches, we show Ut we could potentially die the
umber of repesed courses by 40% make 184 aon
seats available for other Students, and save approximately
SISOK forthe 924 stant in the sd.
REFERENCES
10 Den Bint Sats.
a xan Na Cen er cae Sa 27.
1 RES oy Sie hs hg
10 tea Hac q ae: Se
ow Bina Mein gm
na Scr eons 2 Be cpu
to PE ero ito Pg
e ar
tio RENT Dean ein “Ping em in
‘ry ce bee og ss
vu BE eligi oman
111 Gt Nebo Can Me Cling haine. Ceo. 288
18 Lt Rei pws coc coca ea
eevee a rd
ER ri OC a
ISBN: 1-60132-498.7, CSREA Press ©
10
Int Cont. Frontier in Education: CS and CE | FECS'9 |
An Introductory Visualization Aid for Cybersecurity Education
riel Castro Aguayo!, Ulises Morales!, Xisoyu Long!, Quamar Niyaz', Xisoli Yang’, Ahmad Y Javaid”
ECE Department, College of Engineering and Sciences, Purdue Universit
Northwest, USA,
FEECS Department, College OF Engineering, The University of Toledo, USA
{geastoa, umorales, long312, qniyaz, yangx} @paviedu, ahmad [email protected]
Abstrac—As the technology keeps overgowing. the Internet
uring becomes more popular A a consequence, es tend 10
tse i for social media shopping. banking or anyother online
senc in which they need to put hir personal information.
These online aces eect mals computer ers o apply
(benamack telniques to steal other ers information. The
ters become ack victims due 10 limited understanding of
(Oberatacks and safety practices In ths paper we propose à
Framework development for interactive and engaing eer
‘iy educan. Wh the Delp a the fameork the wer wl be
able to Tear diferent pes of exbertacks and defenses along
Ith he safe ebersecury practices. We als discuss the euren!
"eof the framework and conclue the paper with discusion
on miras and future work."
Keywords
1. Introduction
With Wis technology boom, most people end o be on their
smariphoe or computer surfing online nowadays. Even though
the Imeret makes cur lives easy by providing online services
uch as allowing customers to make puestas online Fer
‘han actully going lo the sores, some misfortunes can oscar
en we are wing thos series, As more people rely on
the computers, the more vulnerable they become o ay stack
Mais computer wer can find ways to sal cet card or
personal information by using malware or backdoor. According 10
Symantec 2018 report [1], 27% mobile app in Weste category
ere malicious. That is no Uh end, the number of non malware
variant for smartphones ha increased, According o an al
im DI e cyber victims los around $1.5 billion in 2017
nd more an 300K Internet rime complaints were reported to
the ner Crime Complains Center in ne sme year. The same
asilo mentioned la 23% of Americans in a conducted survey
‘Spore that credit card infomation of thee family members
ere stolen by the hackers.
"There re some god paces that one can use Wen these
Indus atacks and be properly secured. One good practice
is hy being observant of any changes on he device or have
scary software o asst wil some automated sean. Another
opera con, visualizan ameno. Unity 3D
Ser ie, pe en er
Re Ta ce Sa D e po
practice is wo observe for any unusual cv in a smanphone.
Sch as obsesine data wage or cven overeating Besides,
Smarphones oso evens such as installation and data usage
that can help nro down the aplication responsible for any
malcious scies Practicing yborccuiy methods can hoj
reduce ie potential of having information Solen from atackers-
However the is ack of eyhersecury safety practices among
the wens, Therefore, i imperativo 1 spread the eybesccun
ares trough ire channels and educate he uses how
to avoid cyber, Having users practice visually can be
Benfica to teach them safe practices of using technology and
Being online. As eybenccurty visualization can be effective for
security analysts lo preven a malicious tack, ican ako be
tpl wo engage ases in the Iain process of berry
heats and defenses (3).
Wi this motion, we propose a visualization based ber
secu cation framework that wil help users especially the
teenagers in middle and igh school, understand the cyber
cary ies ey may run ino. I will allow them to leary
about the aci that they are exposed o when navigaing
Online, so they can present thee misfortunes. Thee are two
main reasons to focus on users from carly ages. Fs they
tend to be the fue of our socia. so they migh be the next
generation of eybercunty specialists who might he able to
Prevent more adtancod eyberatacks, Second, the increased usage
Of smaripones and the Internet by lenges his brought several
Security concerns for them and their ame. With the increas
time spen online, tens frequently encounter cyberbullying or
unpesant experiences. Accoig lo a survey conducted by
Me, 34% tens acknowledged that hy have experien
Syberbuling. The same study mentioned that 39% teens do
not adequately set her privacy stings 4) for different online
applications. The developed framework consis of serie
heal inertes wit diferent cavironments vo pode cyber
“ocur hnowleige and safety practices to mile and high chal
Students. As the primary target is teenagers fo this framework,
the development of the personal computer (PC) a well asthe
Iahesmariphone versions will be aalable 1 fll every wer
neat.
“Tae es ofthe paper is stud as Falls. In Scion 2, we
ri discuss the related work Section 3 discuss the applica
thm design ofthe framework, In Section 4, we disse vaio
visulizaon based eyberecunity education topics implemented
at inrdctory Teel the Framework, Finally we conclad our
paper in Section 8
ISBN: 1-60132-498-7, CSREA Press ©
Int Cont. Frontier in Education: CS and CE | FECS'9 |
An Introductory Visualization Aid for Cybersecurity Education
riel Castro Aguayo!, Ulises Morales!, Xisoyu Long!, Quamar Niyaz', Xisoli Yang’, Ahmad Y Javaid”
ECE Department, College of Engineering and Sciences, Purdue Universit
Northwest, USA,
FEECS Department, College OF Engineering, The University of Toledo, USA
{geastoa, umorales, long312, qniyaz, yangx} @paviedu, ahmad [email protected]
Abstrac—As the technology keeps overgowing. the Internet
uring becomes more popular A a consequence, es tend 10
tse i for social media shopping. banking or anyother online
senc in which they need to put hir personal information.
These online aces eect mals computer ers o apply
(benamack telniques to steal other ers information. The
ters become ack victims due 10 limited understanding of
(Oberatacks and safety practices In ths paper we propose à
Framework development for interactive and engaing eer
‘iy educan. Wh the Delp a the fameork the wer wl be
able to Tear diferent pes of exbertacks and defenses along
Ith he safe ebersecury practices. We als discuss the euren!
"eof the framework and conclue the paper with discusion
on miras and future work."
Keywords
1. Introduction
With Wis technology boom, most people end o be on their
smariphoe or computer surfing online nowadays. Even though
the Imeret makes cur lives easy by providing online services
uch as allowing customers to make puestas online Fer
‘han actully going lo the sores, some misfortunes can oscar
en we are wing thos series, As more people rely on
the computers, the more vulnerable they become o ay stack
Mais computer wer can find ways to sal cet card or
personal information by using malware or backdoor. According 10
Symantec 2018 report [1], 27% mobile app in Weste category
ere malicious. That is no Uh end, the number of non malware
variant for smartphones ha increased, According o an al
im DI e cyber victims los around $1.5 billion in 2017
nd more an 300K Internet rime complaints were reported to
the ner Crime Complains Center in ne sme year. The same
asilo mentioned la 23% of Americans in a conducted survey
‘Spore that credit card infomation of thee family members
ere stolen by the hackers.
"There re some god paces that one can use Wen these
Indus atacks and be properly secured. One good practice
is hy being observant of any changes on he device or have
scary software o asst wil some automated sean. Another
opera con, visualizan ameno. Unity 3D
Ser ie, pe en er
Re Ta ce Sa D e po
practice is wo observe for any unusual cv in a smanphone.
Sch as obsesine data wage or cven overeating Besides,
Smarphones oso evens such as installation and data usage
that can help nro down the aplication responsible for any
malcious scies Practicing yborccuiy methods can hoj
reduce ie potential of having information Solen from atackers-
However the is ack of eyhersecury safety practices among
the wens, Therefore, i imperativo 1 spread the eybesccun
ares trough ire channels and educate he uses how
to avoid cyber, Having users practice visually can be
Benfica to teach them safe practices of using technology and
Being online. As eybenccurty visualization can be effective for
security analysts lo preven a malicious tack, ican ako be
tpl wo engage ases in the Iain process of berry
heats and defenses (3).
Wi this motion, we propose a visualization based ber
secu cation framework that wil help users especially the
teenagers in middle and igh school, understand the cyber
cary ies ey may run ino. I will allow them to leary
about the aci that they are exposed o when navigaing
Online, so they can present thee misfortunes. Thee are two
main reasons to focus on users from carly ages. Fs they
tend to be the fue of our socia. so they migh be the next
generation of eybercunty specialists who might he able to
Prevent more adtancod eyberatacks, Second, the increased usage
Of smaripones and the Internet by lenges his brought several
Security concerns for them and their ame. With the increas
time spen online, tens frequently encounter cyberbullying or
unpesant experiences. Accoig lo a survey conducted by
Me, 34% tens acknowledged that hy have experien
Syberbuling. The same study mentioned that 39% teens do
not adequately set her privacy stings 4) for different online
applications. The developed framework consis of serie
heal inertes wit diferent cavironments vo pode cyber
“ocur hnowleige and safety practices to mile and high chal
Students. As the primary target is teenagers fo this framework,
the development of the personal computer (PC) a well asthe
Iahesmariphone versions will be aalable 1 fll every wer
neat.
“Tae es ofthe paper is stud as Falls. In Scion 2, we
ri discuss the related work Section 3 discuss the applica
thm design ofthe framework, In Section 4, we disse vaio
visulizaon based eyberecunity education topics implemented
at inrdctory Teel the Framework, Finally we conclad our
paper in Section 8
ISBN: 1-60132-498-7, CSREA Press ©
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
2. Related Work.
Learning though visualizan technologies using computers
ae mature and widely usd i various domains. Leming using
CableAmanphone devices is relatively new ara. Thre have
een studies that volved creating Teaming applications for
sariphone devices, especially fer new languages ISI. Apps
Tike Dootingo, Base, and many thers tach new languages 10
‘ny amationeaser who instal and wes the pps. Practically
Sing can be taught sowadays a ong as he tele app is
developed for the common use, Thee area variety of teaching
‘gps fom kaming a new language 10 eam new software
In in, there ae apps tat are being used for distance
canine 6. Wit evry set cing a esta computer eher
Candia smartphone device, any application can be developed
to each the students subj.
‘There sa group ha created popular Capture The ag (CTF)
game for high schoo! students o lean technical concepts by
‘seating compote emironmen [7]. They introduced à in a
GenCyber 18] camp and tis mosivaed te student continue
learning aller the camps because ofthe competition sed game
formt, With inroducing serious game int Teaming. we bing
the concep of vision and interaction ino the design of
our framework, as it actively engages users 1 lea subjects
‘Te Ling tool will teach each topic by involving the wer
in active Tearing hough interactive simulation. la addition, the
framework includes assessments to evaluate what the ur has
kam,
3. Application Design
In order o develop the application framework, various software.
engines were analyzed, an Unity 8D [9] was found as ih best
fi Unity has a vay of tools that offer deselopers à end
mirent to work on. Although the nal dein tends to be
fr smarphooc lar, the pplication will ist be ul for PC
plo o et prior o he Anal delivery. Fortunately, Unity
allow user to change the plform cas natn, the engine
Provides an iterated development environment (IDE) to write
de as wel as high visual and audi eet. Therefore, Unity
À the Best chic 0 develop the application.
AS previously mentioned, the application will be focused
on PCS for this design. It will be modi 10 accommodate
Smartphone devices upon completion. The aplication will have
2 menu, shown in Figure, that will hoj the user to navigate
through diferent topes and be aware of what option they
fc on The mena will be made gerri o mare toi and sub-
topis can be added in the simplest way posible I wil have the
‘fest of shrink and expan isto Up the sub-opks so that
the wseris not verwhclmed Each topic wil consis four stages
forthe users: i) introduction, iteration i) explanation nd
iy) ascsiment. The ow chat can be seen m Figure 2, 8 10
how the Now ofthe Ian module wl be for ih use foreach
topic. These tasks are important fr the user fo understand and
salute what they re leaning
“The introduction will be rs description of what he topic
is about he best way lo gab a users aention ls o haven
"
Fig. 1: Menu screen forthe topics and sections in the framework
(Concept introduction
I
Fig. 2: Stages involved in cach leaming module
animated character with a shot sory or description. sen with
à lite interaction itis enough to keep the usr estate and
Icaming (10). Te animated introduction will be irn for
cach topic 0 thatthe user docs mot become dire wäh
the same animations, The interaction is more ofa sallnge doe
to the ict thatthe technical terms and procedaes have o be
“displayed in away tht the user can understand. The display e
ot the only concer, bu he interaction part as well here the
er can lam fom the sores and eta ete understanding of
the process and concep impli by inracing with the ei
ronment. Moreover the interactive part should ot be lang else
itll crab the user with more detailed information. With
having topos and stops, each interaction will be shoe and
sig othe pin therefore stl giving the students Le ability
to nerac and lam the mai key points. The explanation tsk
il be more in depth where the hey pois ae Bing explica.
“hiss where the user will get a complete understanding of what
they have leaned in de trio tak, Jest the node,
ISBN: 1-60132-498-7, CSREA Press ©
2. Related Work.
Learning though visualizan technologies using computers
ae mature and widely usd i various domains. Leming using
CableAmanphone devices is relatively new ara. Thre have
een studies that volved creating Teaming applications for
sariphone devices, especially fer new languages ISI. Apps
Tike Dootingo, Base, and many thers tach new languages 10
‘ny amationeaser who instal and wes the pps. Practically
Sing can be taught sowadays a ong as he tele app is
developed for the common use, Thee area variety of teaching
‘gps fom kaming a new language 10 eam new software
In in, there ae apps tat are being used for distance
canine 6. Wit evry set cing a esta computer eher
Candia smartphone device, any application can be developed
to each the students subj.
‘There sa group ha created popular Capture The ag (CTF)
game for high schoo! students o lean technical concepts by
‘seating compote emironmen [7]. They introduced à in a
GenCyber 18] camp and tis mosivaed te student continue
learning aller the camps because ofthe competition sed game
formt, With inroducing serious game int Teaming. we bing
the concep of vision and interaction ino the design of
our framework, as it actively engages users 1 lea subjects
‘Te Ling tool will teach each topic by involving the wer
in active Tearing hough interactive simulation. la addition, the
framework includes assessments to evaluate what the ur has
kam,
3. Application Design
In order o develop the application framework, various software.
engines were analyzed, an Unity 8D [9] was found as ih best
fi Unity has a vay of tools that offer deselopers à end
mirent to work on. Although the nal dein tends to be
fr smarphooc lar, the pplication will ist be ul for PC
plo o et prior o he Anal delivery. Fortunately, Unity
allow user to change the plform cas natn, the engine
Provides an iterated development environment (IDE) to write
de as wel as high visual and audi eet. Therefore, Unity
À the Best chic 0 develop the application.
AS previously mentioned, the application will be focused
on PCS for this design. It will be modi 10 accommodate
Smartphone devices upon completion. The aplication will have
2 menu, shown in Figure, that will hoj the user to navigate
through diferent topes and be aware of what option they
fc on The mena will be made gerri o mare toi and sub-
topis can be added in the simplest way posible I wil have the
‘fest of shrink and expan isto Up the sub-opks so that
the wseris not verwhclmed Each topic wil consis four stages
forthe users: i) introduction, iteration i) explanation nd
iy) ascsiment. The ow chat can be seen m Figure 2, 8 10
how the Now ofthe Ian module wl be for ih use foreach
topic. These tasks are important fr the user fo understand and
salute what they re leaning
“The introduction will be rs description of what he topic
is about he best way lo gab a users aention ls o haven
"
Fig. 1: Menu screen forthe topics and sections in the framework
(Concept introduction
I
Fig. 2: Stages involved in cach leaming module
animated character with a shot sory or description. sen with
à lite interaction itis enough to keep the usr estate and
Icaming (10). Te animated introduction will be irn for
cach topic 0 thatthe user docs mot become dire wäh
the same animations, The interaction is more ofa sallnge doe
to the ict thatthe technical terms and procedaes have o be
“displayed in away tht the user can understand. The display e
ot the only concer, bu he interaction part as well here the
er can lam fom the sores and eta ete understanding of
the process and concep impli by inracing with the ei
ronment. Moreover the interactive part should ot be lang else
itll crab the user with more detailed information. With
having topos and stops, each interaction will be shoe and
sig othe pin therefore stl giving the students Le ability
to nerac and lam the mai key points. The explanation tsk
il be more in depth where the hey pois ae Bing explica.
“hiss where the user will get a complete understanding of what
they have leaned in de trio tak, Jest the node,
ISBN: 1-60132-498-7, CSREA Press ©
2
Int Cont. Frontier in Education: CS and CE | FECS'9 |
Fig. 3 Learning modos, infomation (op le intention (o sgh) explanation (hot
wil involve some animation and very minimal nercin in oer
10 have the uses complete tention. The explanation will so 0
‘ver pts tha wll be reviewed in te quiz. I the assessment,
‘completion ofthe quiz willbe recorded in onder lo know the
progres of the ner There wil he à set of questions for each
Topi, however only afew question wil be asked at dom so
the same question are ot repeated each time: When the progress
is recorded thre wl e a progress Dr tha will demonstrate Bow
much he user has completed successfully
Before releasing te nal application, esting will be fundamen
tal o sure tat the sofware can be a grat tool quie the
ested eyberscunty knowledge. Testing wll be performed 1 a
‘erin group of students with basic Anosledge of eybereciy
Who wall analyz he application and provide imporana Fedback
Figure 3 shows an example ofthe four stages of Teaming
modal.
4. Visualization-based Education Topic
‘There are wide range of topics in cytersecuri. To ge tated
with the famenork development. we have considered network
and we security. network secur, we hae state with TCP
and DNS protocols (discussed below) and associated tacks with
them, For eb secu we focused on cose web tacks and
phishing.
e, and assessment (btm ih)
A1 Network Security Vi
AAA DNS station
“me Domain Name System (DNS) i we to resolve domain
ame, eg. vano pr ed o an IP address [II] is request
response protocol tha uns on th application layer of TCPAP
Internet sick, DNS is nanimauly sed for resolving domain
rames due to is diia implementation For DNS vita
thon, following questions had Been considered
“What is DNS and how des it work?
How o make he DNS process ey to explain?
{How to visuals te tacks associated with the DNS?
‘These question are amero in the framework We chose
two ipical DNS ack ampliacion and Mine. In the
DNS amplicaion ac, stcier we open DNS servers o
ood a victim's network with lage number of DNS reply
messages [12]. The stack sends DNS look-up queries toa large
amber of open DNS senc by spooling the IP adress of the
‘tim a source Asa consequence, all DNS responses ae sent
tothe victim. ln DNS hijacking, the atacker sends the domain
resolution query 1 different DNS server instead of the actual
Tr the intdtion stage of DNS module visualization, a
“iy situation has been ten for iluso. How would you
ISBN: 1-00132-4987, CSREA Press ©
Int Cont. Frontier in Education: CS and CE | FECS'9 |
Fig. 3 Learning modos, infomation (op le intention (o sgh) explanation (hot
wil involve some animation and very minimal nercin in oer
10 have the uses complete tention. The explanation will so 0
‘ver pts tha wll be reviewed in te quiz. I the assessment,
‘completion ofthe quiz willbe recorded in onder lo know the
progres of the ner There wil he à set of questions for each
Topi, however only afew question wil be asked at dom so
the same question are ot repeated each time: When the progress
is recorded thre wl e a progress Dr tha will demonstrate Bow
much he user has completed successfully
Before releasing te nal application, esting will be fundamen
tal o sure tat the sofware can be a grat tool quie the
ested eyberscunty knowledge. Testing wll be performed 1 a
‘erin group of students with basic Anosledge of eybereciy
Who wall analyz he application and provide imporana Fedback
Figure 3 shows an example ofthe four stages of Teaming
modal.
4. Visualization-based Education Topic
‘There are wide range of topics in cytersecuri. To ge tated
with the famenork development. we have considered network
and we security. network secur, we hae state with TCP
and DNS protocols (discussed below) and associated tacks with
them, For eb secu we focused on cose web tacks and
phishing.
e, and assessment (btm ih)
A1 Network Security Vi
AAA DNS station
“me Domain Name System (DNS) i we to resolve domain
ame, eg. vano pr ed o an IP address [II] is request
response protocol tha uns on th application layer of TCPAP
Internet sick, DNS is nanimauly sed for resolving domain
rames due to is diia implementation For DNS vita
thon, following questions had Been considered
“What is DNS and how des it work?
How o make he DNS process ey to explain?
{How to visuals te tacks associated with the DNS?
‘These question are amero in the framework We chose
two ipical DNS ack ampliacion and Mine. In the
DNS amplicaion ac, stcier we open DNS servers o
ood a victim's network with lage number of DNS reply
messages [12]. The stack sends DNS look-up queries toa large
amber of open DNS senc by spooling the IP adress of the
‘tim a source Asa consequence, all DNS responses ae sent
tothe victim. ln DNS hijacking, the atacker sends the domain
resolution query 1 different DNS server instead of the actual
Tr the intdtion stage of DNS module visualization, a
“iy situation has been ten for iluso. How would you
ISBN: 1-00132-4987, CSREA Press ©
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
Fig. 4: Introduction and incocio stages for DNS module
find the location of a new adress? À man call Bob has to
find the ables for Google ofic “1400 Amphitheatre Phy,
Mountain View, CA 94083" (in an age with no Google Maps.
To vist Google, he goes to the local community fee lo
chan knowlege of the new addres: the local community ofice
represents the local serve, The local community oiee gives a
an of the adres 10 Bob such as tht the Google's office is
in California site. Then, Bob goes to California and asks the
sate goverment af city af, and Google neightorood as
Shown in Figur 4. These represent rot server TLD (Top Level
Domain) server and domain nameserver, respectively. In he DNS
complican ack the interac ion is Base on the DNS concept
nd developed on tp of in DNS icing interaction, shows
‘hata dishonest Sl will provide wrong information According
tothe imeraction, users can easily understand the DNS process
nd how tacks muy happen trough DNS.
TCP Mastraion
“Transmision Control Protocol (TCP) provides reliable com:
munication between two hosts ati acheved by a"hre-wny
ands” [13]. There are dee ses in this handshake proces.
Fist he client sende a connection request 10 the server using
some iil sequence number, and a window size fo the baler
{ed bythe len lo store the packets coming fom the serve.
[Alter receiving. the rue, the server sends a message o the
ent including is eandomly chosen sequence number and win
‘dow size along wih the confimation of eens sence number,
[Alter receiving the response form the server, the len raum
an aeknosledgement message with the confirmation of server's
Sequence number and then a TCP connection is established,
‘To make thi press more understandable, we made a dialog
game how two canon characte make frends sown in Figure.
In tis game-baed visualization, Pikach represents the client
and Bultsauerepesents the server. In te Degining,Pikachu
il send a fend request (it step. Then, Buasaur replies 10
the request and senda the frend aceptance (second sep. ler
Pic colis he acepance (Nr) the Fendi between
Pitch and Bulbasar wll be establish. We have aso added
à learing module for TCP SYN Flooding ack
#
Pikachu:
Hi, Bulbasuar. Do you want to be my friend?
Fig. 5: Gambas visualization to explain TCP conection
setup
42 Web Security Visualization
421 CSRE Attack
CSRF stands fr rose request forgery. In this attach, an
ook rates a forge request or tuned weit, The request
appears genuine to the sted websie [14] One purpose for
ESKE atck could be modify information in social media or
Banking system,
As many wor ae aia with the socia mai, CSRF vi
alzalon shows the social media website of two users (Sammy
and Aliso), example adopted fom SEED labs [1S]. Sammy e
trying to become friend with Ale, but she does nt accept his
fend request Then, Sammy uses CSRE to generate à request
From Alice" web browser sing which se logged othe tial
media sever. Sammy create à forge request and embeds it an
‘extemal website He sends the ink to Alice o open Alice, hen.
et actu by the request The user wl be al o intra with
tot the characters im oder 0 lam the functional of CSRE
shown in Figure & Ath same time, debmtions and explanations
willbe shown. A quiz afer ever eel wll e popup to measure
whether the usr Understood the topic or not. Fur, the
ser wil ao be able o sce ow the process of CSRE works in
an aut.
422 XSS Attack
XSS atack stands for ernste sep stack, I an
injection attack hat fects web aplication wih lnea
tuer can manipulate and ij malicious code in web pages
‘Once the ser accesses the web age the malicious code executes
in hise system 11)
As mentioned in CSRE visualization, social medias popular.
among the Inert uses around he word. SS visalizaon will
also show how XSS ca e inte in social media website, For
this case, Sammy wil jet malicious code under his profile with
JavaScript language. So every user who visits Sammy profile
Iie poi wil be opted de o the maicou code (17
ISBN: 1-00132-4987, CSREA Press ©
Fig. 4: Introduction and incocio stages for DNS module
find the location of a new adress? À man call Bob has to
find the ables for Google ofic “1400 Amphitheatre Phy,
Mountain View, CA 94083" (in an age with no Google Maps.
To vist Google, he goes to the local community fee lo
chan knowlege of the new addres: the local community ofice
represents the local serve, The local community oiee gives a
an of the adres 10 Bob such as tht the Google's office is
in California site. Then, Bob goes to California and asks the
sate goverment af city af, and Google neightorood as
Shown in Figur 4. These represent rot server TLD (Top Level
Domain) server and domain nameserver, respectively. In he DNS
complican ack the interac ion is Base on the DNS concept
nd developed on tp of in DNS icing interaction, shows
‘hata dishonest Sl will provide wrong information According
tothe imeraction, users can easily understand the DNS process
nd how tacks muy happen trough DNS.
TCP Mastraion
“Transmision Control Protocol (TCP) provides reliable com:
munication between two hosts ati acheved by a"hre-wny
ands” [13]. There are dee ses in this handshake proces.
Fist he client sende a connection request 10 the server using
some iil sequence number, and a window size fo the baler
{ed bythe len lo store the packets coming fom the serve.
[Alter receiving. the rue, the server sends a message o the
ent including is eandomly chosen sequence number and win
‘dow size along wih the confimation of eens sence number,
[Alter receiving the response form the server, the len raum
an aeknosledgement message with the confirmation of server's
Sequence number and then a TCP connection is established,
‘To make thi press more understandable, we made a dialog
game how two canon characte make frends sown in Figure.
In tis game-baed visualization, Pikach represents the client
and Bultsauerepesents the server. In te Degining,Pikachu
il send a fend request (it step. Then, Buasaur replies 10
the request and senda the frend aceptance (second sep. ler
Pic colis he acepance (Nr) the Fendi between
Pitch and Bulbasar wll be establish. We have aso added
à learing module for TCP SYN Flooding ack
#
Pikachu:
Hi, Bulbasuar. Do you want to be my friend?
Fig. 5: Gambas visualization to explain TCP conection
setup
42 Web Security Visualization
421 CSRE Attack
CSRF stands fr rose request forgery. In this attach, an
ook rates a forge request or tuned weit, The request
appears genuine to the sted websie [14] One purpose for
ESKE atck could be modify information in social media or
Banking system,
As many wor ae aia with the socia mai, CSRF vi
alzalon shows the social media website of two users (Sammy
and Aliso), example adopted fom SEED labs [1S]. Sammy e
trying to become friend with Ale, but she does nt accept his
fend request Then, Sammy uses CSRE to generate à request
From Alice" web browser sing which se logged othe tial
media sever. Sammy create à forge request and embeds it an
‘extemal website He sends the ink to Alice o open Alice, hen.
et actu by the request The user wl be al o intra with
tot the characters im oder 0 lam the functional of CSRE
shown in Figure & Ath same time, debmtions and explanations
willbe shown. A quiz afer ever eel wll e popup to measure
whether the usr Understood the topic or not. Fur, the
ser wil ao be able o sce ow the process of CSRE works in
an aut.
422 XSS Attack
XSS atack stands for ernste sep stack, I an
injection attack hat fects web aplication wih lnea
tuer can manipulate and ij malicious code in web pages
‘Once the ser accesses the web age the malicious code executes
in hise system 11)
As mentioned in CSRE visualization, social medias popular.
among the Inert uses around he word. SS visalizaon will
also show how XSS ca e inte in social media website, For
this case, Sammy wil jet malicious code under his profile with
JavaScript language. So every user who visits Sammy profile
Iie poi wil be opted de o the maicou code (17
ISBN: 1-00132-4987, CSREA Press ©
#4
‘Ste Request Forgery
Fig. 6 GUI of CSRF anack visualization
423 Phishing Attack
IU à am atack whore the user provides information lo an
stacker unknowingly. The common way this ocur forthe
stacker to create an email while mitin o Bea Known Air
uri, uchas a bank e ocial media customer serie (18) When
the ser eek on a link or download an atachment, one ofthe
00 things can happen: on, the Tink wil guido th user 03 fake
etat imitating cime log-in ge account information or
en rot card information: or two the downlad tachment
‘may contin an infection and insaliag a malware on the ser
computable device.
‘The design of the interaction par will asst the wer 10
understand what a sample phishing email wil lok ike and how
to avoid it shown a Figure 7. typical phishing ack may nat
Seer as an ack at fst, Pt as a genuine email fom a ir
put. lt inactive par ofthis ack he user il be sing
à mail app 19 pen their incoming email. Within the incoming
tals, thee e an etal fom Facebook pretending 10 be foo
customer service: when the user goes o the link thatthe email
Provided it wl edict he to Facebook's Login page The user
il ut in hee login infomation, however ance the user enters
‘and attempt to sign-in a warning will pop-up noiyng the user
‘hee information ha been ole. Tin occur in everyday ie
where people's infomation gts sole without warning.
5. Conclusion and Future Work
As the wage of the Internet hops growing, 1er need 10
understand the risk they ate exposed lo when navigating 10
‘tates, The min objective of ur projet sto spread awareness
of eyberccury and educate the ser how to detect and avoid
fer aci a a young age. The framework will not oly allow
the nen o Team the diferent Kinds of attack that areas
‘may se, but the ways they can defend foe the.
‘Cures. we have implemented a Few secunty examples in
the application. We understand thatthe framework has several
limitations, prima in tems of conter and student assessment.
In fare, we plan o include mere atacks and defense mecha
sss in the framework, A this framework application wil Bt
Int Cont. Frontier in Education: CS and CE | FECS'9 |
Fig 7: Phishing Email Visualizaon
he built and tested for PC platform, anar future work would
Im creating a mobile-compatbie version. We plan to use this
Framework for dee of cybersecurity sis cure, ases
the effects ofthis framework on Teaming and prepare à conn
improsement plan (CI), This CIP would include imposing
specie modules tht can enhance wer” understanding, bas
‘on the ner assessment In nde o Keep the unr engaged in a
ame had lung environment, more level will be develop
here the progres and scores wi be bete un, Fra.
ve plan to make this framework open source tothe academie
community aller development and assessment
References
VU O et, Den ab da ME so
DRE e
ra Er tm où
ERE BEE pe mn rn
ST rae SU
DM hl 8 yg he cy
O act
n
w
ISBN: 1-60132-498-7, CSREA Press ©
‘Ste Request Forgery
Fig. 6 GUI of CSRF anack visualization
423 Phishing Attack
IU à am atack whore the user provides information lo an
stacker unknowingly. The common way this ocur forthe
stacker to create an email while mitin o Bea Known Air
uri, uchas a bank e ocial media customer serie (18) When
the ser eek on a link or download an atachment, one ofthe
00 things can happen: on, the Tink wil guido th user 03 fake
etat imitating cime log-in ge account information or
en rot card information: or two the downlad tachment
‘may contin an infection and insaliag a malware on the ser
computable device.
‘The design of the interaction par will asst the wer 10
understand what a sample phishing email wil lok ike and how
to avoid it shown a Figure 7. typical phishing ack may nat
Seer as an ack at fst, Pt as a genuine email fom a ir
put. lt inactive par ofthis ack he user il be sing
à mail app 19 pen their incoming email. Within the incoming
tals, thee e an etal fom Facebook pretending 10 be foo
customer service: when the user goes o the link thatthe email
Provided it wl edict he to Facebook's Login page The user
il ut in hee login infomation, however ance the user enters
‘and attempt to sign-in a warning will pop-up noiyng the user
‘hee information ha been ole. Tin occur in everyday ie
where people's infomation gts sole without warning.
5. Conclusion and Future Work
As the wage of the Internet hops growing, 1er need 10
understand the risk they ate exposed lo when navigating 10
‘tates, The min objective of ur projet sto spread awareness
of eyberccury and educate the ser how to detect and avoid
fer aci a a young age. The framework will not oly allow
the nen o Team the diferent Kinds of attack that areas
‘may se, but the ways they can defend foe the.
‘Cures. we have implemented a Few secunty examples in
the application. We understand thatthe framework has several
limitations, prima in tems of conter and student assessment.
In fare, we plan o include mere atacks and defense mecha
sss in the framework, A this framework application wil Bt
Int Cont. Frontier in Education: CS and CE | FECS'9 |
Fig 7: Phishing Email Visualizaon
he built and tested for PC platform, anar future work would
Im creating a mobile-compatbie version. We plan to use this
Framework for dee of cybersecurity sis cure, ases
the effects ofthis framework on Teaming and prepare à conn
improsement plan (CI), This CIP would include imposing
specie modules tht can enhance wer” understanding, bas
‘on the ner assessment In nde o Keep the unr engaged in a
ame had lung environment, more level will be develop
here the progres and scores wi be bete un, Fra.
ve plan to make this framework open source tothe academie
community aller development and assessment
References
VU O et, Den ab da ME so
DRE e
ra Er tm où
ERE BEE pe mn rn
ST rae SU
DM hl 8 yg he cy
O act
n
w
ISBN: 1-60132-498-7, CSREA Press ©
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
wi geome en ht iy
eee
Po mes
erie a Cape tee El
D panes coran.
mm
mue
15
tha ESAS necpas/ mn oman. ong tnd pnp /erons- sie.
Danse rose (coir) cond May 16208
D SE ae tan ada
119 RSS” Rec pas amant ca /123/20p- 1
Un Say me PES
18 “on Pig At or Api Men o
ISBN: 1-60132-498-7, CSREA Press ©
wi geome en ht iy
eee
Po mes
erie a Cape tee El
D panes coran.
mm
mue
15
tha ESAS necpas/ mn oman. ong tnd pnp /erons- sie.
Danse rose (coir) cond May 16208
D SE ae tan ada
119 RSS” Rec pas amant ca /123/20p- 1
Un Say me PES
18 “on Pig At or Api Men o
ISBN: 1-60132-498-7, CSREA Press ©
16
Int Cont. Frontier in Education: CS and CE | FECS'9 |
Using a Telepresence robot in an educational context
Laurent GALLON, Angel ABENIA
LIUPPA - Universi of Pau and Pays
de l'Adour - Pau, France
(laurent gallon angel abenia} Guniv-paw.e
Abstract This paper deals wilh the we of telepresence
robot nan een conte T this day. these ases re
‘en elated 0 the problematic of homebound student
The emphatic contest associated wi these students masks
the pedagogical dius encountered by telepresence
Icumens. Im this ott, we ft dea ue of the bot
be homebound sudens, highlighting motivational factors
Then we focus on pesen wing the robo, once sen
hate comer deines Finally, we describe our atenpi so
reduce transactional distance by adding comectd earning
KeyWords telepresence bot motion, tational dans
1. Introduction
For the las few years we have witnessed an inten
tion of he experimental use of telepresence robos in
the educational system. In France, à recent study in he
‘Auvergne Rhine-Alpes Frech arca (AURA) has reported
the findings ofa classroom we for students ho ae home:
ound! Othe tic [2] [10] have enforced hese resus
nd show thatthe min ad vale of telepresence in hi
mets the preservation of the soil nk between the
Students, the scho, the tescher and special the class
rates. This reservation isan important guarantee of Schoo!
entity andthe redaction of the rk of dropping out
However, beyond the paychoociological impact questions
shout Teaming oppatune Va teleprenece robes ae
Andes several dius comet distro the distant sud
[Bi or example duties of perception ofthe teacher's
and clssmate” body language (ital proprioception) due
lo a wideangle comer. or he persption of he “Me.
robos” and the new form of soclizaon allowed by hi
‘mechanical avatar (4. The teacher may also be disturbed
in the realization of hier task take ino ascount the
peste “presence” ofthis ste, incl (he set in
‘he didactic station and follow the cvoluion of her
Teaming, epoca inthe case of practical und sil sess
mens. Aer the postive Impact ofthe robot during the fis
‘es, opow ovr time can sometimes be noted, due lo
à to large wansctonal distance [S] celte 1 à lack of
Practical adapted fete inthe telepresence device, Several
Françoise DUBERGEY, Maité NEGUI
SAPADAO - Papilles de Enseignement Public
des Landes (PEP40) - Mont de Marsan, France
[email protected]
projets have begun to explore these dius. J. Bell
16] sudie the fcing of presence (incarnation) af distant,
students in hybrid teaching. from vieoconerencing 10 he
tse ofthe telepresence rbot It appears thatthe mob
of the robot is essential lo geting closer o a fing of
physical presence. Gleason (7) cons Bells results and
{emphasizes the ned for appeoprite pedagoy. Newhart and
al 10] (1] say the feeling of accept of the robo.
from a teachers and almiisrators point of view. In all
those works the sociologia ad psychological aspects are
taken ino account. bt the dite par is ide discuss
In alton, pedagogical situations ofthe use of a rbot are
lined o simple verbal and visual ineracions (une /
eres), Te use of a robot ln practical woe is Ile or
rot end
In this paper, we propose preliminary analysis of te
use in duration (perseverance) of telepresence robots la an
«ducaiona cones. We hase our analysis on SDT theory
{D1 o sess the motivation while using the robo. More
precise we focus on what happens afer several eins
Df robot wes in the com, that is once the impact
I novelty and empañy forthe homebound stot fas
‘We thon ete some experimentation done o incre the
ape of the interactions a the robot with humans and
isa space. in onder 1 reduce the wansctional distance
[U2] inde the student à perception o sce and control
and hen Keep hinder engaged and motive.
2. Background
2.1 SDT theory
‘The Self Determination Theory (SDT) [13] is a psycho
logical theory which can be applied 1 education in order to
understand the bai proces and how to motivate tens
and coin 10 atret thee tention. 1 based om the
imate psychology needs ol: autonomy (eed of being stor
of hisher own life, making hisher own choice according
lo iver preference, competence (ned of coto and
ing compete in à doa in which hee was interested)
and reltednes (ceo ineracing with eer peopl). Dee
‘nd Ryan [13] deine student molhaton as de combination
fof two facto + exert mation, which i povided by
an outside hop scher, classmate, ITS, ca. and
internal motivation, which is provided by the perception
the stents of hier ability to accompli pape
ISBN: 1-60132-498-7, CSREA Press ©
Int Cont. Frontier in Education: CS and CE | FECS'9 |
Using a Telepresence robot in an educational context
Laurent GALLON, Angel ABENIA
LIUPPA - Universi of Pau and Pays
de l'Adour - Pau, France
(laurent gallon angel abenia} Guniv-paw.e
Abstract This paper deals wilh the we of telepresence
robot nan een conte T this day. these ases re
‘en elated 0 the problematic of homebound student
The emphatic contest associated wi these students masks
the pedagogical dius encountered by telepresence
Icumens. Im this ott, we ft dea ue of the bot
be homebound sudens, highlighting motivational factors
Then we focus on pesen wing the robo, once sen
hate comer deines Finally, we describe our atenpi so
reduce transactional distance by adding comectd earning
KeyWords telepresence bot motion, tational dans
1. Introduction
For the las few years we have witnessed an inten
tion of he experimental use of telepresence robos in
the educational system. In France, à recent study in he
‘Auvergne Rhine-Alpes Frech arca (AURA) has reported
the findings ofa classroom we for students ho ae home:
ound! Othe tic [2] [10] have enforced hese resus
nd show thatthe min ad vale of telepresence in hi
mets the preservation of the soil nk between the
Students, the scho, the tescher and special the class
rates. This reservation isan important guarantee of Schoo!
entity andthe redaction of the rk of dropping out
However, beyond the paychoociological impact questions
shout Teaming oppatune Va teleprenece robes ae
Andes several dius comet distro the distant sud
[Bi or example duties of perception ofthe teacher's
and clssmate” body language (ital proprioception) due
lo a wideangle comer. or he persption of he “Me.
robos” and the new form of soclizaon allowed by hi
‘mechanical avatar (4. The teacher may also be disturbed
in the realization of hier task take ino ascount the
peste “presence” ofthis ste, incl (he set in
‘he didactic station and follow the cvoluion of her
Teaming, epoca inthe case of practical und sil sess
mens. Aer the postive Impact ofthe robot during the fis
‘es, opow ovr time can sometimes be noted, due lo
à to large wansctonal distance [S] celte 1 à lack of
Practical adapted fete inthe telepresence device, Several
Françoise DUBERGEY, Maité NEGUI
SAPADAO - Papilles de Enseignement Public
des Landes (PEP40) - Mont de Marsan, France
[email protected]
projets have begun to explore these dius. J. Bell
16] sudie the fcing of presence (incarnation) af distant,
students in hybrid teaching. from vieoconerencing 10 he
tse ofthe telepresence rbot It appears thatthe mob
of the robot is essential lo geting closer o a fing of
physical presence. Gleason (7) cons Bells results and
{emphasizes the ned for appeoprite pedagoy. Newhart and
al 10] (1] say the feeling of accept of the robo.
from a teachers and almiisrators point of view. In all
those works the sociologia ad psychological aspects are
taken ino account. bt the dite par is ide discuss
In alton, pedagogical situations ofthe use of a rbot are
lined o simple verbal and visual ineracions (une /
eres), Te use of a robot ln practical woe is Ile or
rot end
In this paper, we propose preliminary analysis of te
use in duration (perseverance) of telepresence robots la an
«ducaiona cones. We hase our analysis on SDT theory
{D1 o sess the motivation while using the robo. More
precise we focus on what happens afer several eins
Df robot wes in the com, that is once the impact
I novelty and empañy forthe homebound stot fas
‘We thon ete some experimentation done o incre the
ape of the interactions a the robot with humans and
isa space. in onder 1 reduce the wansctional distance
[U2] inde the student à perception o sce and control
and hen Keep hinder engaged and motive.
2. Background
2.1 SDT theory
‘The Self Determination Theory (SDT) [13] is a psycho
logical theory which can be applied 1 education in order to
understand the bai proces and how to motivate tens
and coin 10 atret thee tention. 1 based om the
imate psychology needs ol: autonomy (eed of being stor
of hisher own life, making hisher own choice according
lo iver preference, competence (ned of coto and
ing compete in à doa in which hee was interested)
and reltednes (ceo ineracing with eer peopl). Dee
‘nd Ryan [13] deine student molhaton as de combination
fof two facto + exert mation, which i povided by
an outside hop scher, classmate, ITS, ca. and
internal motivation, which is provided by the perception
the stents of hier ability to accompli pape
ISBN: 1-60132-498-7, CSREA Press ©
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
tasks, Intemal motion is always songer than extemal
main. On his bass, the whole maation oa person o
Accomplish a tsk can be classified into tne keels: aba,
‘context and stations, Each el describes a dirt
«volaion time scale. Te global level addresses main
that comes rom the social enviroment, religion. ee (oa
time range. The contenu level adresses motion Bt
‘comes fom the context of the sten!» environment, as
for example the school coment (medie timo range) The
Sion level address motivation from the cue
tation in which the sen I at given moment (hor
time range), Siuaonal contents are dhe strongest (bu he
shoes) cones. On the ether hand. global ones are
the weaken oer a short period of time, but are persien
foughout He. Changing à context perception can nly
be only achieved by repeating many times ever situational
‘context in which the suden as a fcling of success and
‘ont positive perception of hive kill).
In be ease of the use of a telepresence robot by à
mebound student, the Art uses ofthe rbot inthe clase
rom are ascii with strong situational come! (hor
range dation) in which the whole mutation i induced by
y and empathy, At this ime he sient, casemate
and teacher are no guided by educational concer. AS
‘scribed by Newhart in [1 abide screed between he
teacher, classes, and the homebound stent This bridge
dics not only include social pects, Dt also the remoto
Spaces, Same res must be defined o ensure safe ridge
cen sakcolders. We adres his point in section 3
‘Gradually. the inital coments replaced by the educational
solely (contextual lve, weaker bot more pere). in
Shick he question om how o ean through a rob, how
to evaluate Knowledge and sills though a rbot, and how
to inset aro in pedagogical activities ae asked At his
time, menthe capaci, ofthe homebound student trough
the robot à leg motion. The more funcions are
numerous and elective, he more motion and penistnce
are preset. Te adequacy ofthe rab’ capables wid
leaching tank closely elated othe mon distance
22 ‘Transactional distance
‘Transactional distance (TD) is defined by Moore [12 as
the degree of psychological distance between the sae
andthe teacher It can te quantified a à function of three
variables logue, Sucre ad leaner autonomy la [ES
Zhang propose to ten TD ino thee ems: ansactona
ivan Reece sde and teacher (DST) ramacional
distance between student and student (TDSS) and wanse-
tonal distance between student and content (TDSC). An
ron [14] suggests thatthe smaller these measures, the
‘more sing the Iaming experience, and a à rel,
‘more substnialereverince, In online distance Lamine.
irdional TD eis on tecnologica mediation. Weidich
15] poposes a defino of TDTECH, which assesses the
Anal dane of te mer and the ines or
technology. He argues that this extent depends on two
factors“) the Base proieny of the sent in ung
the mena tec. (2) the dsg an funcional
(Gz. Ma) of the techos Holl, as pena y
the alent A
pes
Ta Hang proposes a framework 1 undesund and
ses scenes eines on amine He demie
ds modea dere dto conquered comm
sation, wi high confidence in her computer
Sills More peche. in ibe sut of online camine
Sens show's song ends in computer sl
etary. maton o arin. nine communication
Selec. Selected ang and leer cota re
the weakest ems I [ Weich ls hi les TOTECH
fxr (ident rain) vih Hung» compere
ac Inher wor, be denser that modem
Stet ave a god proficiency in sl new tecnologies
-TDTECH mainly dpend on the functional be robot
offs. The couse loire has abo a major pa. The
Enea between he dat set and ae unas
involved nthe pedagogical ton (lesa, eche.
and abo betwen ie stent and de ita spre, we
Site depending dis toploy. Fee example the
Case of tr, he sun oly ces to Ae and a
totes ln he cue of lesen erben, the Sen mus
terse o ince with he tach, lo wih her
last, in oer 10 ak quen or lo sn vot
Stork Fly inthe cue of ral work, the stant
Ist ako be able fo nrc wih he dan pce ry
Ou pa manipulations, or when he mt posa,
play's clay Meni mie loe rap of Sens 4
Sich Hebe belongs So: oc vs, documen Sarin,
And physi apace fhe abt are pinay.
3. Our project
34 Overview
Our project comes fom the collaboration ofthe Computer
Science Lab ofthe University of Pas, in France, and SAPAD
40 (organization for a pedagogical help of homebound
Students, department of he Landes (40) in France. These
‘organizations help homebound students during thei coma
Tescence. and ep 10 finance home cases. Bui i nt
ays easy 0 find teachers who agree going 1 a students
home, because ofthe gevgrplial distance or because ee
is are ot enough teacher ln te desired special The use
loftelepesence robots à solution. Sipe 2018, 24 students
‘re benefited from thease of 3 mot Tn te Following, we
ive à feedback ofthese uses, focusing on he cor We
made 1 ensure a the robot could be used in he sete
incoune, ll through ihr comalescence,
ISBN: 1-60132-498-7, CSREA Press ©
7
tasks, Intemal motion is always songer than extemal
main. On his bass, the whole maation oa person o
Accomplish a tsk can be classified into tne keels: aba,
‘context and stations, Each el describes a dirt
«volaion time scale. Te global level addresses main
that comes rom the social enviroment, religion. ee (oa
time range. The contenu level adresses motion Bt
‘comes fom the context of the sten!» environment, as
for example the school coment (medie timo range) The
Sion level address motivation from the cue
tation in which the sen I at given moment (hor
time range), Siuaonal contents are dhe strongest (bu he
shoes) cones. On the ether hand. global ones are
the weaken oer a short period of time, but are persien
foughout He. Changing à context perception can nly
be only achieved by repeating many times ever situational
‘context in which the suden as a fcling of success and
‘ont positive perception of hive kill).
In be ease of the use of a telepresence robot by à
mebound student, the Art uses ofthe rbot inthe clase
rom are ascii with strong situational come! (hor
range dation) in which the whole mutation i induced by
y and empathy, At this ime he sient, casemate
and teacher are no guided by educational concer. AS
‘scribed by Newhart in [1 abide screed between he
teacher, classes, and the homebound stent This bridge
dics not only include social pects, Dt also the remoto
Spaces, Same res must be defined o ensure safe ridge
cen sakcolders. We adres his point in section 3
‘Gradually. the inital coments replaced by the educational
solely (contextual lve, weaker bot more pere). in
Shick he question om how o ean through a rob, how
to evaluate Knowledge and sills though a rbot, and how
to inset aro in pedagogical activities ae asked At his
time, menthe capaci, ofthe homebound student trough
the robot à leg motion. The more funcions are
numerous and elective, he more motion and penistnce
are preset. Te adequacy ofthe rab’ capables wid
leaching tank closely elated othe mon distance
22 ‘Transactional distance
‘Transactional distance (TD) is defined by Moore [12 as
the degree of psychological distance between the sae
andthe teacher It can te quantified a à function of three
variables logue, Sucre ad leaner autonomy la [ES
Zhang propose to ten TD ino thee ems: ansactona
ivan Reece sde and teacher (DST) ramacional
distance between student and student (TDSS) and wanse-
tonal distance between student and content (TDSC). An
ron [14] suggests thatthe smaller these measures, the
‘more sing the Iaming experience, and a à rel,
‘more substnialereverince, In online distance Lamine.
irdional TD eis on tecnologica mediation. Weidich
15] poposes a defino of TDTECH, which assesses the
Anal dane of te mer and the ines or
technology. He argues that this extent depends on two
factors“) the Base proieny of the sent in ung
the mena tec. (2) the dsg an funcional
(Gz. Ma) of the techos Holl, as pena y
the alent A
pes
Ta Hang proposes a framework 1 undesund and
ses scenes eines on amine He demie
ds modea dere dto conquered comm
sation, wi high confidence in her computer
Sills More peche. in ibe sut of online camine
Sens show's song ends in computer sl
etary. maton o arin. nine communication
Selec. Selected ang and leer cota re
the weakest ems I [ Weich ls hi les TOTECH
fxr (ident rain) vih Hung» compere
ac Inher wor, be denser that modem
Stet ave a god proficiency in sl new tecnologies
-TDTECH mainly dpend on the functional be robot
offs. The couse loire has abo a major pa. The
Enea between he dat set and ae unas
involved nthe pedagogical ton (lesa, eche.
and abo betwen ie stent and de ita spre, we
Site depending dis toploy. Fee example the
Case of tr, he sun oly ces to Ae and a
totes ln he cue of lesen erben, the Sen mus
terse o ince with he tach, lo wih her
last, in oer 10 ak quen or lo sn vot
Stork Fly inthe cue of ral work, the stant
Ist ako be able fo nrc wih he dan pce ry
Ou pa manipulations, or when he mt posa,
play's clay Meni mie loe rap of Sens 4
Sich Hebe belongs So: oc vs, documen Sarin,
And physi apace fhe abt are pinay.
3. Our project
34 Overview
Our project comes fom the collaboration ofthe Computer
Science Lab ofthe University of Pas, in France, and SAPAD
40 (organization for a pedagogical help of homebound
Students, department of he Landes (40) in France. These
‘organizations help homebound students during thei coma
Tescence. and ep 10 finance home cases. Bui i nt
ays easy 0 find teachers who agree going 1 a students
home, because ofthe gevgrplial distance or because ee
is are ot enough teacher ln te desired special The use
loftelepesence robots à solution. Sipe 2018, 24 students
‘re benefited from thease of 3 mot Tn te Following, we
ive à feedback ofthese uses, focusing on he cor We
made 1 ensure a the robot could be used in he sete
incoune, ll through ihr comalescence,
ISBN: 1-60132-498-7, CSREA Press ©
7
18
“The description i chronological Fist we place ourselves
in theft context where nvely and empty induces the
Stakeholles's motation. In this par. uo sb pars ae
“ferent : he fr (sion 32) deals withthe actions
lo preparo the arial of the robot. The second (section 33)
Feten tothe ist ues ina classroom, and the creation 0
Safe Mide between stakchldes.
‘Alter some sessions of robot ne, he nit cones fades
and is replaced by the cational comen. In section 34,
e rete the possibility of how to comic to Be engaged in
the we of a abo. y adding a dedicated connected amine
“iront tht races the transactional distance, andthe
sk of dropping ut
32 Preparing the arrival of the robot
‘The preparation ofthe stakeholders a he arial ofthe
robot is eset The more effective this preparation. he
‘more involved the various stakeholders in the we of he
robot, ad he more the fist content Ihe ones in tes of
‘matali at in time On the the and, por preparation
il to sce the ind context quick} dipper and pve vay
lo he icli of teaching a robot, wih a high risk of
“roping ot, I the semaindr ofthis section, we describe
the hey point to which we pad parte tention For each
sakeoller
21 Choosing the right robot
As we mind before, the fst ses of a robot are
accomplished in a very Song context ven By money
nd empty. But hs content fades qui, and is plc
bythe educational context, in which seven pedagogic
“leas appear, and can be à reason for dropping ut. At
this mo, tbe tation i clearly impacted bythe epactes
‘ofthe interaction ofthe robot (TDTECH). Depenling on he
topology o courses the homebound student takes, the choco
ofthe robot can be a benefit or an obstacle to motion For
‘example, course ae given na smal classroom, ith ile
Space between the tbls cumbersome obo wil muke he
diva den feo tha else is inuring the est of he
lass from the moment hc wants 40 move the disant
robot. Inthe cae ofa cure, gon video quay ise
Advantage o sce whi the teacher i win on the Bord
So the ntl choice ofthe robo Is essential for motivation
depending on the school environment, and the cures the
homebound suden i aking
‘We have experimented 3 diferent robots; Double from
Double Robotics, Beam fom AwvaholSuitable Teele.
and Ubbo expe from Axyn Robotics (FD
Each rot has diferent technical harcterisice which
impact he perepion the student has and so TDTECH. A
summary of some ofthese characteristics given in Table
\
Our experience shows that connection problems ae the
main actor of impact on motivan 10 we the ro
Int Cont. Frontier in Education: CS and CE | FECS'9 |
un.
E | Le u
ed a
Fig I: Used telepresence bos
Table 1 st of technical capacities of telepresence robots
=a So
mer = =o weg
a DTC SEE NON MTOR
TDTECH is mainly impacted by this facto. The quality
of video and sound is abo importan. This leads un 10
Systematically une 4G connections, instead of Wi to aid
problems of sensibly, roaming wile moving inthe class:
oom, sharing of bandwidth, and somtimes authentication
issue. The weigh can also be a problem ifthe robot has
to be carried by sulens, for example lo go from one
floor to another. Final, cstton can be a problem in
some cases. especially in crowded clasevoms (handbags
on the fon), e in classrooms with He space between
lables. Other characteris sem to be es portant. For
example, a Short batery life i not necessary à proble:
homebound sales ar not conecte all though the day
Hong, because of a poor capacity of concentration, medical
(are, „Furthermore, during a session. the rabo rarely
moves, whi extends is Batry ie, Finally och Deak
‘ems sfc to recharge the hate
Notice tat camection vues do ot ony ocur shoo,
they ako appear at stent” home. This leads us lo lo
adopt 4G connections for the sudent Unforunsely. his i
rot always posible a a hospital. or in some rural arcs.
In thee caes, aller one or to temp, the Comeción
problems become stronger tan he need o rcover the saa
Hk, andthe student stops using the robo.
[As mentioned by Newhart [10], ensuing god technical
ridge between distant spaces (classroom and student oca
in) à exenta for mothation.
ISBN: 1-60132-498-7, CSREA Press ©
“The description i chronological Fist we place ourselves
in theft context where nvely and empty induces the
Stakeholles's motation. In this par. uo sb pars ae
“ferent : he fr (sion 32) deals withthe actions
lo preparo the arial of the robot. The second (section 33)
Feten tothe ist ues ina classroom, and the creation 0
Safe Mide between stakchldes.
‘Alter some sessions of robot ne, he nit cones fades
and is replaced by the cational comen. In section 34,
e rete the possibility of how to comic to Be engaged in
the we of a abo. y adding a dedicated connected amine
“iront tht races the transactional distance, andthe
sk of dropping ut
32 Preparing the arrival of the robot
‘The preparation ofthe stakeholders a he arial ofthe
robot is eset The more effective this preparation. he
‘more involved the various stakeholders in the we of he
robot, ad he more the fist content Ihe ones in tes of
‘matali at in time On the the and, por preparation
il to sce the ind context quick} dipper and pve vay
lo he icli of teaching a robot, wih a high risk of
“roping ot, I the semaindr ofthis section, we describe
the hey point to which we pad parte tention For each
sakeoller
21 Choosing the right robot
As we mind before, the fst ses of a robot are
accomplished in a very Song context ven By money
nd empty. But hs content fades qui, and is plc
bythe educational context, in which seven pedagogic
“leas appear, and can be à reason for dropping ut. At
this mo, tbe tation i clearly impacted bythe epactes
‘ofthe interaction ofthe robot (TDTECH). Depenling on he
topology o courses the homebound student takes, the choco
ofthe robot can be a benefit or an obstacle to motion For
‘example, course ae given na smal classroom, ith ile
Space between the tbls cumbersome obo wil muke he
diva den feo tha else is inuring the est of he
lass from the moment hc wants 40 move the disant
robot. Inthe cae ofa cure, gon video quay ise
Advantage o sce whi the teacher i win on the Bord
So the ntl choice ofthe robo Is essential for motivation
depending on the school environment, and the cures the
homebound suden i aking
‘We have experimented 3 diferent robots; Double from
Double Robotics, Beam fom AwvaholSuitable Teele.
and Ubbo expe from Axyn Robotics (FD
Each rot has diferent technical harcterisice which
impact he perepion the student has and so TDTECH. A
summary of some ofthese characteristics given in Table
\
Our experience shows that connection problems ae the
main actor of impact on motivan 10 we the ro
Int Cont. Frontier in Education: CS and CE | FECS'9 |
un.
E | Le u
ed a
Fig I: Used telepresence bos
Table 1 st of technical capacities of telepresence robots
=a So
mer = =o weg
a DTC SEE NON MTOR
TDTECH is mainly impacted by this facto. The quality
of video and sound is abo importan. This leads un 10
Systematically une 4G connections, instead of Wi to aid
problems of sensibly, roaming wile moving inthe class:
oom, sharing of bandwidth, and somtimes authentication
issue. The weigh can also be a problem ifthe robot has
to be carried by sulens, for example lo go from one
floor to another. Final, cstton can be a problem in
some cases. especially in crowded clasevoms (handbags
on the fon), e in classrooms with He space between
lables. Other characteris sem to be es portant. For
example, a Short batery life i not necessary à proble:
homebound sales ar not conecte all though the day
Hong, because of a poor capacity of concentration, medical
(are, „Furthermore, during a session. the rabo rarely
moves, whi extends is Batry ie, Finally och Deak
‘ems sfc to recharge the hate
Notice tat camection vues do ot ony ocur shoo,
they ako appear at stent” home. This leads us lo lo
adopt 4G connections for the sudent Unforunsely. his i
rot always posible a a hospital. or in some rural arcs.
In thee caes, aller one or to temp, the Comeción
problems become stronger tan he need o rcover the saa
Hk, andthe student stops using the robo.
[As mentioned by Newhart [10], ensuing god technical
ridge between distant spaces (classroom and student oca
in) à exenta for mothation.
ISBN: 1-60132-498-7, CSREA Press ©
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
322 Preparing the homebound student and hier
parents
‘The major ise for the family i the fer tht the
homebound student willbe further marginalized by ether
students in his rote form. This fing is no related lo
techy ut othe social ink with clssmats Moremer
they are convinced tat the teachers will cep the presence
ofthe robo inthe casero. This Fock comes fom e
‘ducaional background they experienced, whee the teacher
À en as a crtake somewhat like pent I ical
to make tem accep at thee child may or atend rin.
‘lines because the teacher eines Ih robot in hi ces.
“The Git fears of the sen ae about self-image: some
have mot seen tee elsomats for a long me, and ness
and weuimen may have altered their physical appearance
They ar eased when they lear at they can choose he
image they want show the lass (hat or example) oe o,
Pct at al, This technological functionality can generate
rong msn in ii context, ut een he robot docs
ot hve this etre, it ays posible 1 dbl or mask
the webcam from the cockpit
‘We always pesform à pre-connecion test between the
robot and the homehound stent. In order not to be ds
tard y the desir to econer the social ink with th Schoo
forts test the robots located na neural place (ina room
of our university) allowing to focus only on the technica
Aspects A he end of hie irre hat the stent docs
ot anto cominu which shows tht te ability wo use his
iscology is Song (x mentioned by Weich I). In he
ar cases where the student reus 1 use the robot er
the fist tes, he reasons are mainly related o problems of
seleimage, not tech sues.
323 Preparing teachers
“Te inrodocion ofa robo ino the classroom enemies
à ft rolex of mnt from teachers. The presence ola
‘camera in a classroom sat ill. During har clas, e
teachers muster and ti moments Seed”. Opening to
the outside wor is ol easy and he tol canbe considere
voyeur We Lion perfectly well he encens in recent yeas
fof stent publications on Social ewer, degen ios
fof teachers in their classes, andthe impact that these act
Fue had on the profession,
A hs fist poi comes also the ea feng ad with
the reality of the dese, The “world of absence” in he
school environment i indeed devoid of all human: he
diese gives ise o immediate empathy, atthe daly routine
ofthe else males us accustomed o his absence. When
the student not present, hehe may be considered as not
‘xing in the cls prop. that st ay tha one dogs not
mesure (and one dos not ty to measure) the impact of
the illness on the dent and hier scholing. Teachers
“scone the reality ofthis odd of absence om the day Ihe
robot aies in thei classroom.
But ur experience shown tha the reality of wing the robo
is dien. Indeed, as we akeady sad above. he disease
far from being omnipresen in the image wich i sen by the
robot (we only sce the face ofthe student) Its acceptance
ds al the me fated, and very quie. when techen
eave with he robot as wih an “ordinary” stadt. We
have even experimented that a acer, extremely reluctant
to inroduing the robot in hier clan, get a the end
‘ofthe year nto having ed the expriment, convinced by
foedtack from hier colleges
“Anh important point stat the tsche des not wan
to be responsible or ay problems on he robar This over
bo the connection problems, bt also potential rakase
during her couse,
"Alex relctaces can be liminate by discusing wih
the taches ont forehand showing tbm the meri e
proces, and especialy by having them ving the robot, o
doo the Fear ofthis new technology, racing TDTECH
from tei point of view, and Beter understand how the
student is perceiving the css.
324 Preparing school board
“The school board has hey role in the inal context. As
we have son before, a this it age dhe mai inal bss
«les the teacher. Obining the support the amination
(racy of teachers) is very important o “help” inser,
When necessary, 10 make the eo o accept the rot in
‘las, Bu the board mus also he risuredon cern pont
“The robot appears san expensive technological tol (each
robot we we costs approximately 000$) andthe problem
‘oF responsibly which arse in cas of bcakge, et or
breakdown, Secure storage when the rob nt in we can
alo be sick pont.
325 Preparing classmates and choosing referents
“The role of clssmates i ent. The homebound student
wants be able o atend clases mainly lo leave hier
‘medical environment to find a “nomma” environment Clase
‘ates a wat to understand wh dir end mot present
‘One importan thing is ientiying inthe classroom one
ctw of the bomebound students’ ends who can become
sfr To be a reeren means 10 be the guardian of te
robot and this the prin ofthe homebound stent, The
‘main asks that ae assigned toa referent ae: 1) collecting
and returning the robot to its storage point as soon as
possible (moming, noo, evening) preventing the bate
from discharging 2) solving technical problems encoun
tered during lessons (und, camer, disconnetions, =) 3)
changing withthe remote ent as soon the tion
requires sending pictures of the whieboard by MMS,
Specie request when the stent does wot wan o dss
the teachers»). The refeen is a hey element that reassures
the teacher, who do not have to deal with he obo du
ISBN: 1-60132-498-7, CSREA Press ©
1
322 Preparing the homebound student and hier
parents
‘The major ise for the family i the fer tht the
homebound student willbe further marginalized by ether
students in his rote form. This fing is no related lo
techy ut othe social ink with clssmats Moremer
they are convinced tat the teachers will cep the presence
ofthe robo inthe casero. This Fock comes fom e
‘ducaional background they experienced, whee the teacher
À en as a crtake somewhat like pent I ical
to make tem accep at thee child may or atend rin.
‘lines because the teacher eines Ih robot in hi ces.
“The Git fears of the sen ae about self-image: some
have mot seen tee elsomats for a long me, and ness
and weuimen may have altered their physical appearance
They ar eased when they lear at they can choose he
image they want show the lass (hat or example) oe o,
Pct at al, This technological functionality can generate
rong msn in ii context, ut een he robot docs
ot hve this etre, it ays posible 1 dbl or mask
the webcam from the cockpit
‘We always pesform à pre-connecion test between the
robot and the homehound stent. In order not to be ds
tard y the desir to econer the social ink with th Schoo
forts test the robots located na neural place (ina room
of our university) allowing to focus only on the technica
Aspects A he end of hie irre hat the stent docs
ot anto cominu which shows tht te ability wo use his
iscology is Song (x mentioned by Weich I). In he
ar cases where the student reus 1 use the robot er
the fist tes, he reasons are mainly related o problems of
seleimage, not tech sues.
323 Preparing teachers
“Te inrodocion ofa robo ino the classroom enemies
à ft rolex of mnt from teachers. The presence ola
‘camera in a classroom sat ill. During har clas, e
teachers muster and ti moments Seed”. Opening to
the outside wor is ol easy and he tol canbe considere
voyeur We Lion perfectly well he encens in recent yeas
fof stent publications on Social ewer, degen ios
fof teachers in their classes, andthe impact that these act
Fue had on the profession,
A hs fist poi comes also the ea feng ad with
the reality of the dese, The “world of absence” in he
school environment i indeed devoid of all human: he
diese gives ise o immediate empathy, atthe daly routine
ofthe else males us accustomed o his absence. When
the student not present, hehe may be considered as not
‘xing in the cls prop. that st ay tha one dogs not
mesure (and one dos not ty to measure) the impact of
the illness on the dent and hier scholing. Teachers
“scone the reality ofthis odd of absence om the day Ihe
robot aies in thei classroom.
But ur experience shown tha the reality of wing the robo
is dien. Indeed, as we akeady sad above. he disease
far from being omnipresen in the image wich i sen by the
robot (we only sce the face ofthe student) Its acceptance
ds al the me fated, and very quie. when techen
eave with he robot as wih an “ordinary” stadt. We
have even experimented that a acer, extremely reluctant
to inroduing the robot in hier clan, get a the end
‘ofthe year nto having ed the expriment, convinced by
foedtack from hier colleges
“Anh important point stat the tsche des not wan
to be responsible or ay problems on he robar This over
bo the connection problems, bt also potential rakase
during her couse,
"Alex relctaces can be liminate by discusing wih
the taches ont forehand showing tbm the meri e
proces, and especialy by having them ving the robot, o
doo the Fear ofthis new technology, racing TDTECH
from tei point of view, and Beter understand how the
student is perceiving the css.
324 Preparing school board
“The school board has hey role in the inal context. As
we have son before, a this it age dhe mai inal bss
«les the teacher. Obining the support the amination
(racy of teachers) is very important o “help” inser,
When necessary, 10 make the eo o accept the rot in
‘las, Bu the board mus also he risuredon cern pont
“The robot appears san expensive technological tol (each
robot we we costs approximately 000$) andthe problem
‘oF responsibly which arse in cas of bcakge, et or
breakdown, Secure storage when the rob nt in we can
alo be sick pont.
325 Preparing classmates and choosing referents
“The role of clssmates i ent. The homebound student
wants be able o atend clases mainly lo leave hier
‘medical environment to find a “nomma” environment Clase
‘ates a wat to understand wh dir end mot present
‘One importan thing is ientiying inthe classroom one
ctw of the bomebound students’ ends who can become
sfr To be a reeren means 10 be the guardian of te
robot and this the prin ofthe homebound stent, The
‘main asks that ae assigned toa referent ae: 1) collecting
and returning the robot to its storage point as soon as
possible (moming, noo, evening) preventing the bate
from discharging 2) solving technical problems encoun
tered during lessons (und, camer, disconnetions, =) 3)
changing withthe remote ent as soon the tion
requires sending pictures of the whieboard by MMS,
Specie request when the stent does wot wan o dss
the teachers»). The refeen is a hey element that reassures
the teacher, who do not have to deal with he obo du
ISBN: 1-60132-498-7, CSREA Press ©
1
Air coun, and reasares the admin, Knowing ha
the robots never orge in a class, Nevertheless, ii task
is hea, and should not become a burden fr this referent
Student So the best i 0 find two or tre referent in he
Same las who can lea, for example ever da.
Clearly referes are a key pint. They mask technical
‘sues to teachers and the homebound sadent increasing
hier motivan, and so dressing TDTECH
326 Summary
a Table 2 we summarize the main Key pits which hve
an impact on the motivation of the homebound sent in
ing the robot atthe fit sage Cea, the mot erica
‘keller the teacher From a student poi of view, the
‘mor the teacher som ie the nsenion of Ye robot
in hier elses, the mee the saa is porevering
‘The use of referent students i a eral pin, which
males it posible o paral discharge the teacher and he
disant stade rom technical putes, and allowing them
to foes more on lain. Thi the clement of our process
tha signant dereses the transacinal distance at he
sr ofthe robot ws,
Table 2 summary of Key points for mation at the fs
sage
— == ==
Fe se [For =
33 First uses in classroom
"The appearance o an ling sen in a classroom in he
fom of a rbot at ist generates supise Gee Fig. 2), and
quickly empathy and solidarity among students. There i no
problem of image or maginalizaion. I may even happen
thatthe ang student goes, inthe elas. fom beng In a
position af weakness (case of ik illness) 10 à positon
‘envied (the master” of he robot) paradoxical tation
that bis ha a strong impact onthe matias of he
humebound stant. We must adit tha the image tum
bya te presence robots cairo accep than the image fa.
student sho 3 hadridden or physically paire, especial
sine each dent who user the robe chaos the Image
hse will present in font of the camera, This allows he
to comme 1 Benet fom the positive aura ofthe robe
bout eng the image ofthe dieas ake over
is undeniable that the presence ofthe robot cases à
shock” in the clas, and arly changes atmosphere,
apparel ou, rato poste, When the ot presen.
‘ich student became mo responsible than nom. For x.
ample students will mor easly self-discipline tthe level of
hater slow he obo” ahr the homebound sade
Int Cont. Frontier in Education: CS and CE | FECS'9 |
Fig. 2: Catherine driving the robot for the fist ime as part
of prcica work in seroma! constuction classroom
Lo hear well what the teacher says. They ar silent when
the homebound student ant toas the teacher a question
[Althoogh we fave been able to observ these behmorll
‘changes, farther study wil be needed 1 determin what the
real sociological levers on Which the robot has an impot,
ae. Ts sty has. in ou opinion als interes in Mid
School, wee we know tat elias Yo oter are agile
and in ull consmueton should show hat he rante
teacherstdentclass socal Ink isthe main diver ol the
homebound student from using dhe telepeseee soba, and
that classmates are paricularty attentive 1 this ato
“The aval ofthe rbot has esa a pose pact on
the motivation of al classmates. But quickly, new dicas
appear Indec, the interocion Between the actors and the
remote space re limited tough the robo. This inevitably
has à negative impact onthe quality af the knowledge and
Know-how sccumlated by the disant stud The use of
{he rbot in an educational context is mot enough I must
e complemented by imeneton Wolk wih the deren!
stakeholders and also the remote physical puce o get
loser 10 a physica presence. and ede the anse
distance. In the following, we describe some solutions we
have experimented fe that
34 Decreasing transactional distance by
adding a connected learning environment to
the robot
‘This experiment was comluce a ur universi, fle one
oF our undergraduates has injured his ke Ce), and had
Lo comalesee at home for several weeks, We proposed 10
se a telepresence rbot 0 fallow ceria important courses
(Mematis cure and exercises), English (este and
examinan) and IP telephony tre, exercises, pct
als and practical examination), wih dienen spologis:
ores, exercises on the coune and practical work: We
treated comected ling environments dedicated to each
‘gpology. By connected leaming environment we mean à
set of diga wol, remotely accesible by Ter, which
low him to item the disant space o perform the
requested maspulaons. The robot allows Terry o move
ISBN: 1-60132-498-7, CSREA Press ©
the robots never orge in a class, Nevertheless, ii task
is hea, and should not become a burden fr this referent
Student So the best i 0 find two or tre referent in he
Same las who can lea, for example ever da.
Clearly referes are a key pint. They mask technical
‘sues to teachers and the homebound sadent increasing
hier motivan, and so dressing TDTECH
326 Summary
a Table 2 we summarize the main Key pits which hve
an impact on the motivation of the homebound sent in
ing the robot atthe fit sage Cea, the mot erica
‘keller the teacher From a student poi of view, the
‘mor the teacher som ie the nsenion of Ye robot
in hier elses, the mee the saa is porevering
‘The use of referent students i a eral pin, which
males it posible o paral discharge the teacher and he
disant stade rom technical putes, and allowing them
to foes more on lain. Thi the clement of our process
tha signant dereses the transacinal distance at he
sr ofthe robot ws,
Table 2 summary of Key points for mation at the fs
sage
— == ==
Fe se [For =
33 First uses in classroom
"The appearance o an ling sen in a classroom in he
fom of a rbot at ist generates supise Gee Fig. 2), and
quickly empathy and solidarity among students. There i no
problem of image or maginalizaion. I may even happen
thatthe ang student goes, inthe elas. fom beng In a
position af weakness (case of ik illness) 10 à positon
‘envied (the master” of he robot) paradoxical tation
that bis ha a strong impact onthe matias of he
humebound stant. We must adit tha the image tum
bya te presence robots cairo accep than the image fa.
student sho 3 hadridden or physically paire, especial
sine each dent who user the robe chaos the Image
hse will present in font of the camera, This allows he
to comme 1 Benet fom the positive aura ofthe robe
bout eng the image ofthe dieas ake over
is undeniable that the presence ofthe robot cases à
shock” in the clas, and arly changes atmosphere,
apparel ou, rato poste, When the ot presen.
‘ich student became mo responsible than nom. For x.
ample students will mor easly self-discipline tthe level of
hater slow he obo” ahr the homebound sade
Int Cont. Frontier in Education: CS and CE | FECS'9 |
Fig. 2: Catherine driving the robot for the fist ime as part
of prcica work in seroma! constuction classroom
Lo hear well what the teacher says. They ar silent when
the homebound student ant toas the teacher a question
[Althoogh we fave been able to observ these behmorll
‘changes, farther study wil be needed 1 determin what the
real sociological levers on Which the robot has an impot,
ae. Ts sty has. in ou opinion als interes in Mid
School, wee we know tat elias Yo oter are agile
and in ull consmueton should show hat he rante
teacherstdentclass socal Ink isthe main diver ol the
homebound student from using dhe telepeseee soba, and
that classmates are paricularty attentive 1 this ato
“The aval ofthe rbot has esa a pose pact on
the motivation of al classmates. But quickly, new dicas
appear Indec, the interocion Between the actors and the
remote space re limited tough the robo. This inevitably
has à negative impact onthe quality af the knowledge and
Know-how sccumlated by the disant stud The use of
{he rbot in an educational context is mot enough I must
e complemented by imeneton Wolk wih the deren!
stakeholders and also the remote physical puce o get
loser 10 a physica presence. and ede the anse
distance. In the following, we describe some solutions we
have experimented fe that
34 Decreasing transactional distance by
adding a connected learning environment to
the robot
‘This experiment was comluce a ur universi, fle one
oF our undergraduates has injured his ke Ce), and had
Lo comalesee at home for several weeks, We proposed 10
se a telepresence rbot 0 fallow ceria important courses
(Mematis cure and exercises), English (este and
examinan) and IP telephony tre, exercises, pct
als and practical examination), wih dienen spologis:
ores, exercises on the coune and practical work: We
treated comected ling environments dedicated to each
‘gpology. By connected leaming environment we mean à
set of diga wol, remotely accesible by Ter, which
low him to item the disant space o perform the
requested maspulaons. The robot allows Terry o move
ISBN: 1-60132-498-7, CSREA Press ©
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
ig. 3: Tey and Sam in the practical works room
around the room to collaborate with the other students in
his group, and interact wih is teacher. À reerent stent,
Sam. helped Try when he was using the robot (Fg. 3
3:41 Course typology and transactional distance
In the case of a lecture, the ent needs o see and
hear the teacher sometimes tlk o him. and 1 see the
chou well He does not eel any interaction
tate eames. Necessary documents can be distributed eke
tronialy eforhand. A these need ae covered by the
mine capable of the robot. ol necessary in his.
‘ypoogy, ald ado] funcionales The warn
dance arising fom the use of the robot is weak oy
hasan impact on TDST. Nat that, occasionally, having a
prod vis on the whiteboard isnot always possible, die
to censin conditions such as Wighttes. An eura camera
placed narhewhicboard. may bea good solution. Another
sine pin i the nection of reqs to speak. On
students cut thee microphone not 10 inrfre with the
teacher Signifying that they want 1 ask a question then
comes a iste Some robots offer led pane that can be
ven to signal his request. For oer rob. is posible
10 al a small amp on the webcam of he cockpit o the
robo. onder o Mt ren, and report o the teacher,
In can of san exercises, in are iret In ion
tothe nd for ration withthe teaches, the talent mus
able o ira with hiver casemate, especial in
group work. The student must also he bl to show hier
‘ork to the teacher and clases, This feature exits on
ome robots in the form of airing the cockpit con
However, la that ease the image ofthe stent cannot he
seen anymore and interactions becomes thas less nature
Moreover, the stem must also he able osc the work of
lssmats. Robots possessing the ability to climb / descend
rum ie bead, give the student this power. Without hese
“apis, te use ofthe robo increases TDTECH, with an
impact on TDST and TDSS. A porsble remediation he
‘aking of à photo and sending it using MMS between the
referent and the ste
The mee cial typology is practical work. As in the
“Table Impact of course topology on TDTECHL
case of lesson exercises, the student must be abet interac
with chssmtes and the teacher Hohe needs to shoe
documents. But hehe mus ab be able to pero physical
tons in the classroom, at la o cohorte wih hi
Classmates, I this tology, TDTECH is high, and impact
TDST. TDSS and also TDSC. Adding functonlies 10
permi the dista student o interact wih he distant space
IS not always posible. and depends on the subject The
transactional stance can be reduced in some cases by
adding an lapid pedagogical connected environment. For
example, in computer scence practical work, is qui easy
to offer int connections to computer, server IP ek
hms tothe distant student But traca! disco
San aso be cree by ating the educational objectives
fet tothe remote stent For example, during chemty
ranas, if i impossible forthe remato student
do handle dangerous product, he can, on the ether hand,
uid his colleagues In their manipulations, crete cures,
And search documents Hose can also lm manipulations,
o that bese can analyze it tr In is case, dept the
¿ice in handing. the remote Student still feck ke
eng por ofthe group. Hee plays role and paris
in the realization ofthe sing sequence (eam cognition.
This fing of controling hivher pedagogical activity à
mechani that generates Strong nine motivan,
342 Description ofthe connected learning environment.
pe]
In our experimentan, foreach lesson typology, we
associated a dedicated connected leaning environment (Fg.
3) without changing any pedagogical objective. For lesan
eercses, we proposed Try 1 use a shared whiteboard
‘rough a able, und a share ie orge space for persistent
‘works, These able cold oth be used when iterating
‘vith the tear, or with classmates. Clay, his ston
as great for Tey bol fed another problem: some tach
fs were no used working wilh these numeric wol, and
ele to se them in thei cas. TDTECH increased, o
#0
‚08
im
Fig 4: Connect lang environments
ISBN: 1-00132-4987, CSREA Press ©
a
ig. 3: Tey and Sam in the practical works room
around the room to collaborate with the other students in
his group, and interact wih is teacher. À reerent stent,
Sam. helped Try when he was using the robot (Fg. 3
3:41 Course typology and transactional distance
In the case of a lecture, the ent needs o see and
hear the teacher sometimes tlk o him. and 1 see the
chou well He does not eel any interaction
tate eames. Necessary documents can be distributed eke
tronialy eforhand. A these need ae covered by the
mine capable of the robot. ol necessary in his.
‘ypoogy, ald ado] funcionales The warn
dance arising fom the use of the robot is weak oy
hasan impact on TDST. Nat that, occasionally, having a
prod vis on the whiteboard isnot always possible, die
to censin conditions such as Wighttes. An eura camera
placed narhewhicboard. may bea good solution. Another
sine pin i the nection of reqs to speak. On
students cut thee microphone not 10 inrfre with the
teacher Signifying that they want 1 ask a question then
comes a iste Some robots offer led pane that can be
ven to signal his request. For oer rob. is posible
10 al a small amp on the webcam of he cockpit o the
robo. onder o Mt ren, and report o the teacher,
In can of san exercises, in are iret In ion
tothe nd for ration withthe teaches, the talent mus
able o ira with hiver casemate, especial in
group work. The student must also he bl to show hier
‘ork to the teacher and clases, This feature exits on
ome robots in the form of airing the cockpit con
However, la that ease the image ofthe stent cannot he
seen anymore and interactions becomes thas less nature
Moreover, the stem must also he able osc the work of
lssmats. Robots possessing the ability to climb / descend
rum ie bead, give the student this power. Without hese
“apis, te use ofthe robo increases TDTECH, with an
impact on TDST and TDSS. A porsble remediation he
‘aking of à photo and sending it using MMS between the
referent and the ste
The mee cial typology is practical work. As in the
“Table Impact of course topology on TDTECHL
case of lesson exercises, the student must be abet interac
with chssmtes and the teacher Hohe needs to shoe
documents. But hehe mus ab be able to pero physical
tons in the classroom, at la o cohorte wih hi
Classmates, I this tology, TDTECH is high, and impact
TDST. TDSS and also TDSC. Adding functonlies 10
permi the dista student o interact wih he distant space
IS not always posible. and depends on the subject The
transactional stance can be reduced in some cases by
adding an lapid pedagogical connected environment. For
example, in computer scence practical work, is qui easy
to offer int connections to computer, server IP ek
hms tothe distant student But traca! disco
San aso be cree by ating the educational objectives
fet tothe remote stent For example, during chemty
ranas, if i impossible forthe remato student
do handle dangerous product, he can, on the ether hand,
uid his colleagues In their manipulations, crete cures,
And search documents Hose can also lm manipulations,
o that bese can analyze it tr In is case, dept the
¿ice in handing. the remote Student still feck ke
eng por ofthe group. Hee plays role and paris
in the realization ofthe sing sequence (eam cognition.
This fing of controling hivher pedagogical activity à
mechani that generates Strong nine motivan,
342 Description ofthe connected learning environment.
pe]
In our experimentan, foreach lesson typology, we
associated a dedicated connected leaning environment (Fg.
3) without changing any pedagogical objective. For lesan
eercses, we proposed Try 1 use a shared whiteboard
‘rough a able, und a share ie orge space for persistent
‘works, These able cold oth be used when iterating
‘vith the tear, or with classmates. Clay, his ston
as great for Tey bol fed another problem: some tach
fs were no used working wilh these numeric wol, and
ele to se them in thei cas. TDTECH increased, o
#0
‚08
im
Fig 4: Connect lang environments
ISBN: 1-00132-4987, CSREA Press ©
a
For IP tclephony pra work, we used a VPN conection
in Teny's hose and eur university allow in ©
commet to servers IP lephones and the abot. Nice that
“ery made his practical examination in elepresece. under
the same conditions as his clasamates. He alo took Oe
TORIC exam! in telepresence, He had no problems wih
stance and passed both exams successfully
343 Anais
We conducted interviu with Tey, Sam, and he teach
ers who paicipate in ths experiment. et ther opinion
fon the posi we negative impact ofthe connected lesen
mironmens associated o the rbot Gee IS), The resul
these stay ae
+ Knowledge and know-how (TDSC): the opinion is nan
imous for Knowledge, thee is no dilrence between
feceto-fice and distance, At Know-how level, Try Fl.
a ease. Teachers recognized tht he esseial tps
ere Validate, The comected pedagogical environ
‘ent has therefore plyod it role well u a TDSC evel
+ erations wih teachers and clssmates (TDST and
TDSSı: teachers recognized that their iterations in
clas with Temy were equivalen when ing ie robo
compared to faceso-ace. They observed the same
ui and deines in Ter while communicating
do his roto form compared 1 facet Jae: very He
intervention in mathematics, a ot of paria in
English In practical works, lepesene di ot pre
vent him from chain and laughing with castes.
Obviously, the ase of the robot dil not change his
tad, or that ofthe sache. Note tht the mah
teacher inallyetctant 10 use documen sharing
tools, acknowledged that this would ulimately be a
ood ing for her interaction with Ter
+ ilratons wi tant space: in practical works, there
as à before and fer conecedlaming environment.
Before, Ter was an observer. and could only observe
the work of is classmates. Using the dedicated ped
ügoekal connected environment. he was able 10 de
he. 1 realize on his vn remote manipulation, and
lear by practic, a fundamental clement of pelao.
Comore in his abilities, be agreed o take the tak
Of doing his IP telephony exam at he same time
ts classmates. He scored 1220 withthe same exam
compared o ther.
‘This study shows that the use ofa connected earning
environment grey files signant the insertion of
{he telepresence robot ino the pedagogical sequences and
redves the transactional distance, A larger sty, with a
‘Song vallon, should be conducted o conten thse
preliminary resus
naps sigan!
Int Cont. Frontier in Education: CS and CE | FECS'9 |
4. Conclusion and perspectives
In this pape. we led the problem of pescan ia
ing telepresence robots for hometound students We have
Shove tht once he Ina eme come has passe,
Pelagia icles appear when aking no account he
agent in his oboe form in the chips. We have e
Serb several examples of comes laming enviroments
that rece the racional distance.
In future work, we are thinking of consoldation cur
fit ees hough broder study aking o account
in particular cam cognition dimension. so important
in the wold of drain. We have sel eperimenting
witha telepresence escape game, to see ow the players
lerne inthe same physical space, while they ae al
Physically disant om hs pee. Te eoncasions of hese
Works stool allow us 0 cet eleresence camina ur
Unity, fo eofesiona who can not mane physkly
ro long Kamin.
References
1 ami, E Am. Se nt
ate Bema a
OS ee na
a at
on Renee neler he
TEE dams
TR re Or
vw ST oor a a
ae LES
1 SRE LE 12 on Ton mer opt
Saree
a RATE tee ee sas
ee ve
in Site ea rant nommen fn
BEE hn i i eR a
in en een ans
apes este ge BR
119 awe MG KO) Ty of mati dans, ewe
principles of distance ode. 1, 2238.
RE ge Seti in main mw
Em Sl u!
a ett ee ts
ern
en
den propi: Comput. Elan
ISBN: 1-60132-498-7, CSREA Press ©
in Teny's hose and eur university allow in ©
commet to servers IP lephones and the abot. Nice that
“ery made his practical examination in elepresece. under
the same conditions as his clasamates. He alo took Oe
TORIC exam! in telepresence, He had no problems wih
stance and passed both exams successfully
343 Anais
We conducted interviu with Tey, Sam, and he teach
ers who paicipate in ths experiment. et ther opinion
fon the posi we negative impact ofthe connected lesen
mironmens associated o the rbot Gee IS), The resul
these stay ae
+ Knowledge and know-how (TDSC): the opinion is nan
imous for Knowledge, thee is no dilrence between
feceto-fice and distance, At Know-how level, Try Fl.
a ease. Teachers recognized tht he esseial tps
ere Validate, The comected pedagogical environ
‘ent has therefore plyod it role well u a TDSC evel
+ erations wih teachers and clssmates (TDST and
TDSSı: teachers recognized that their iterations in
clas with Temy were equivalen when ing ie robo
compared to faceso-ace. They observed the same
ui and deines in Ter while communicating
do his roto form compared 1 facet Jae: very He
intervention in mathematics, a ot of paria in
English In practical works, lepesene di ot pre
vent him from chain and laughing with castes.
Obviously, the ase of the robot dil not change his
tad, or that ofthe sache. Note tht the mah
teacher inallyetctant 10 use documen sharing
tools, acknowledged that this would ulimately be a
ood ing for her interaction with Ter
+ ilratons wi tant space: in practical works, there
as à before and fer conecedlaming environment.
Before, Ter was an observer. and could only observe
the work of is classmates. Using the dedicated ped
ügoekal connected environment. he was able 10 de
he. 1 realize on his vn remote manipulation, and
lear by practic, a fundamental clement of pelao.
Comore in his abilities, be agreed o take the tak
Of doing his IP telephony exam at he same time
ts classmates. He scored 1220 withthe same exam
compared o ther.
‘This study shows that the use ofa connected earning
environment grey files signant the insertion of
{he telepresence robot ino the pedagogical sequences and
redves the transactional distance, A larger sty, with a
‘Song vallon, should be conducted o conten thse
preliminary resus
naps sigan!
Int Cont. Frontier in Education: CS and CE | FECS'9 |
4. Conclusion and perspectives
In this pape. we led the problem of pescan ia
ing telepresence robots for hometound students We have
Shove tht once he Ina eme come has passe,
Pelagia icles appear when aking no account he
agent in his oboe form in the chips. We have e
Serb several examples of comes laming enviroments
that rece the racional distance.
In future work, we are thinking of consoldation cur
fit ees hough broder study aking o account
in particular cam cognition dimension. so important
in the wold of drain. We have sel eperimenting
witha telepresence escape game, to see ow the players
lerne inthe same physical space, while they ae al
Physically disant om hs pee. Te eoncasions of hese
Works stool allow us 0 cet eleresence camina ur
Unity, fo eofesiona who can not mane physkly
ro long Kamin.
References
1 ami, E Am. Se nt
ate Bema a
OS ee na
a at
on Renee neler he
TEE dams
TR re Or
vw ST oor a a
ae LES
1 SRE LE 12 on Ton mer opt
Saree
a RATE tee ee sas
ee ve
in Site ea rant nommen fn
BEE hn i i eR a
in en een ans
apes este ge BR
119 awe MG KO) Ty of mati dans, ewe
principles of distance ode. 1, 2238.
RE ge Seti in main mw
Em Sl u!
a ett ee ts
ern
en
den propi: Comput. Elan
ISBN: 1-60132-498-7, CSREA Press ©
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
A Hands-on Oriented Cyber-Learning Curriculum for
Undergraduate Cybersecurity Education
Yaswanth Koll, Ahmad Y. Javaid
Electrical Engineering and Computer Se
ence Department
“The University of Toledo
“Toledo, OH 43606, USA
‘[email protected], Ahmad [email protected]
Abstract Wih oberanack on daly news nwa, e
ici 0 the eyberaacs are usally the people wh lack
Lula of hoe ty happen. I in also non that dis:
lating ames frm technology in this igual world à not
{elton to sis problem. On de conta earn cbr
mas, how they work and protecting oneself nthe ober
world is a more appropriate solution. Dhs overall practice
‘enabling eybertearaig hough he development of sie
ofthear curicalum is ofen termed as evber-eduaton
Integrating sich curriculum in undergraduate sie à
eric and needs no comincing. Ths paper discusses a
comprehensive hanson based cbr camine curriculum
tre rel, which con de eier qed os a separate
course or negated bo eng cherry cones, as
Felt The course fer on one and insight no Me
Inver mechanisms fa Jo succengulcxberatucs. We
study and prepare hand lbs for eight dret clanes
of atacks and related opensource tools 0 help sents
in insights om these attacks, and lear how 10 prevent
fr sofezuand again thom These clases include web:
‘ach, vinerablliy explotacion passwd cocine social
engineering. denatofservice, fens. and an orher™
Steger with some general security ates. I ttl, 15
tools were stalled. hat agan corea tothe above eight
clases
Keywords: Cyber carci, eer cu. eer
seaming, Ops os, Mando karin
1. Introduction
A be data varying fom personal informatio o indus
‘il contol systems are being connected and tise
through he networks all over the wold, which put cyber
‘uri in a vial rol ofthe system, One of he leading ete
Security solos rm CISCO defines eybenecuriy us he
practice of peeing systems, networks, and programs rom
al as" [1]. The United Stats top he Is foe mos
tags cher at across the word and cybersrimials.
incaescyhecriminals wo its most wanted i. The Unie
Sate govemmet i planing 1 spend 15 bln dolls for
all eybereury seed avis rss the country in 2019.
entity theft ane of the won impacts of a data Dresch
caused due 1 cyber ak, which i increasing every year
‘nd tot 60 milion Americans cain ha tir eis
hse been sen. With th Its ecologies such a the
Iniemet of Things (IST), every device inthe home including
door lock connected to the Internet, making i avilable in
besace and pone to ber aci [2]. According 1 à
Study conducted by TBM, he number of mega data breaches
Gmoling more than milion record) tose to 6 in 2017
from just 9 in 2013. To give a financial acount ofthe ass
deo the beeches, estate that a reach of SO milion
records will seul in an approximate 10 of 380 millon
do 31
“The above mentions manifest the importance of cyber
security awareness among people, Being avare of eyes
arty tas and how they happen, has become a esp:
Sil rather than an option. According 10 CISCO [4 Ihe
‘ost common cyber ack ar, maar phishing, Man
be middle, Deniabot service, SQL injection and Zerodoy
exploit À recent work discuss val le of the employ.
ces in prcting the organization rom cyber atacs [5]
Te sites that every employee à responsible fr following
the securiy polices of the organization. Despite all the
arenes campaigns conducted by US government and no
prof organizations lke the Cyber Secuiy Alliance here
Is continuing ignorance among the public andthe organiza
tions: According toa survey conducted by CompTIA. ony
‘ne thie of the organizan: in the USA need mandato)
Sbersecufy anarenes taining [6] is essential hat every
individual and employes of an organizan should resche
eybersecurity awareness tine which can be achieved
Though eshenecurty education, Therefore we develop à
comprehensive hands-on based cyberdkaming curiculum
that can be offered as a separate couse 0e integrated into
using ebenecusiy cures.
2. Literature Survey
‘The eghesccurity teas ae nt limited 10 stealing dt
dpi series they alo pose a severe thet to word
pese. Sity cyhenecuriy predictions for 2019 includes
¿ber war (7. À her ack objets i o sea infor
‘ato, harm or compromise the computer to wet For ker
ISBN: 1-60132-498-7, CSREA Press ©
A Hands-on Oriented Cyber-Learning Curriculum for
Undergraduate Cybersecurity Education
Yaswanth Koll, Ahmad Y. Javaid
Electrical Engineering and Computer Se
ence Department
“The University of Toledo
“Toledo, OH 43606, USA
‘[email protected], Ahmad [email protected]
Abstract Wih oberanack on daly news nwa, e
ici 0 the eyberaacs are usally the people wh lack
Lula of hoe ty happen. I in also non that dis:
lating ames frm technology in this igual world à not
{elton to sis problem. On de conta earn cbr
mas, how they work and protecting oneself nthe ober
world is a more appropriate solution. Dhs overall practice
‘enabling eybertearaig hough he development of sie
ofthear curicalum is ofen termed as evber-eduaton
Integrating sich curriculum in undergraduate sie à
eric and needs no comincing. Ths paper discusses a
comprehensive hanson based cbr camine curriculum
tre rel, which con de eier qed os a separate
course or negated bo eng cherry cones, as
Felt The course fer on one and insight no Me
Inver mechanisms fa Jo succengulcxberatucs. We
study and prepare hand lbs for eight dret clanes
of atacks and related opensource tools 0 help sents
in insights om these attacks, and lear how 10 prevent
fr sofezuand again thom These clases include web:
‘ach, vinerablliy explotacion passwd cocine social
engineering. denatofservice, fens. and an orher™
Steger with some general security ates. I ttl, 15
tools were stalled. hat agan corea tothe above eight
clases
Keywords: Cyber carci, eer cu. eer
seaming, Ops os, Mando karin
1. Introduction
A be data varying fom personal informatio o indus
‘il contol systems are being connected and tise
through he networks all over the wold, which put cyber
‘uri in a vial rol ofthe system, One of he leading ete
Security solos rm CISCO defines eybenecuriy us he
practice of peeing systems, networks, and programs rom
al as" [1]. The United Stats top he Is foe mos
tags cher at across the word and cybersrimials.
incaescyhecriminals wo its most wanted i. The Unie
Sate govemmet i planing 1 spend 15 bln dolls for
all eybereury seed avis rss the country in 2019.
entity theft ane of the won impacts of a data Dresch
caused due 1 cyber ak, which i increasing every year
‘nd tot 60 milion Americans cain ha tir eis
hse been sen. With th Its ecologies such a the
Iniemet of Things (IST), every device inthe home including
door lock connected to the Internet, making i avilable in
besace and pone to ber aci [2]. According 1 à
Study conducted by TBM, he number of mega data breaches
Gmoling more than milion record) tose to 6 in 2017
from just 9 in 2013. To give a financial acount ofthe ass
deo the beeches, estate that a reach of SO milion
records will seul in an approximate 10 of 380 millon
do 31
“The above mentions manifest the importance of cyber
security awareness among people, Being avare of eyes
arty tas and how they happen, has become a esp:
Sil rather than an option. According 10 CISCO [4 Ihe
‘ost common cyber ack ar, maar phishing, Man
be middle, Deniabot service, SQL injection and Zerodoy
exploit À recent work discuss val le of the employ.
ces in prcting the organization rom cyber atacs [5]
Te sites that every employee à responsible fr following
the securiy polices of the organization. Despite all the
arenes campaigns conducted by US government and no
prof organizations lke the Cyber Secuiy Alliance here
Is continuing ignorance among the public andthe organiza
tions: According toa survey conducted by CompTIA. ony
‘ne thie of the organizan: in the USA need mandato)
Sbersecufy anarenes taining [6] is essential hat every
individual and employes of an organizan should resche
eybersecurity awareness tine which can be achieved
Though eshenecurty education, Therefore we develop à
comprehensive hands-on based cyberdkaming curiculum
that can be offered as a separate couse 0e integrated into
using ebenecusiy cures.
2. Literature Survey
‘The eghesccurity teas ae nt limited 10 stealing dt
dpi series they alo pose a severe thet to word
pese. Sity cyhenecuriy predictions for 2019 includes
¿ber war (7. À her ack objets i o sea infor
‘ato, harm or compromise the computer to wet For ker
ISBN: 1-60132-498-7, CSREA Press ©
macs, on the other hand is tb prctic of peroming
compar atcks on éhal sates to achieve the tation
interests In traonal warfare, the nations fight physically
ut ina cyherwarire, there is no direct physical stack
Instead, evryhing is done in viral cybenpare lading ©
couse ines physical damage like, manipulating sada
‘onto, exploiting water plat, drang a vain which
has adverse ect onthe economy ofthe targeted maton
Stunt worm was designed 10 compromis Ian’ meter
program by manipulating the indus cotas without
Being notice by displaying normal conditions 1 the plan
engin, Reports were claiming tht the US. and Lunel
ovement designe the Suxaet worm as an act of yber-
‘arf. Cyber Temes cn be defined a the convergence
tri and cyberspace. Cyberteneis i the we of
“computer technology to cause severe disruption, ar and
Fear in the economy. I is related o Tour main aspect
‘computer generation, pital motivation, physical violence,
and psjcholgieal coercion [8
A recent work showcases the noces to bu! Items:
tional cooperation on cyber defense and detre agains
‘jhe terrorism. I showcases the possible was used by
the trono expli eyherspace and mentions tht every
‘county has its cyber ks ad incidence response teams.
propones tht thee should be a rob, itemationa eg
Framework under the contol ofthe UN that adresses all
the eybemccirity related cs and shire the inlignce
hse among tbe nations across the globe [9], The ra
{eal approach fr detertence of y ere is proposed
in LOL, discusses the challenges imohed in cyber
terri deemence and a robos framework 10 over
them. Another popular work surveyed the Psychological
‘elect of yber errors, They have conducted fel sey
‘experiments that simulated cyber ec and interviewed
522 individual The results ae analyzed on à score Of d
in which eer teorsm (Leta) is marked at 36, which
Shows severe psiloc impact [1
“The eye ack tagte at national influe leads
to sere harm, damage 1 the national economy and the
‘ens global peace The yber heats hat nation can fae are
Intemational tenes, sae-sponsord train, mals.
Fuck, Insider teal. The methods lo Cor thse
threats using intligenc are proposed in [12]. Thee ae
ao posits of insider estee 10 an organization
that may be used acidentally oe inteonall by the en
ployees À recen work analyzes th posible insider shea,
ow they rise problems in organizations and discuss he
awaits tha ar elvan lo vais scenarios (3)
A popular survey on types of eye aks and how they
‘an fe detected, classics the cyber attacks into 13 pet
including Denikoservice,ephereapionae, cyber temo.
im, cyber war, active ack andthe various approaches
including. agen-tased approach, arial ineligenos a
prosch tht can be sed in deletion and prevention of the
Int Cont. Frontier in Education: CS and CE | FECS'9 |
sacks (14, With the Intense research being conoced on
machine learning and dat mining researchers ae exploring
‘ways tose these two ares nto the cybersecuriy eld ode
tec invusion, A suey conducted on discovering the we of
machine lung and data ining in cyberscuiy ition
detection 3 presented in 15. Roy et al. proposed game
theory mode or addressing network scuiy problem and
surveyed the game designing techniques and tir outcomes
Da
Nowadays everything rom a device to a cy is Being
converted smart ens by integration of computing and
ommunicaton capabilities o. which makes them pre
lo epber stacks. The sit ges are the next generation
power supply and management systems, which ae par of
the era national infrastructure. A smart grid achieved
by combining advanced computing and communication tec
nologies o chance eficiensy in power management. The
Smart prs are one of the ot reis to the cyber tacks
AS bey may cae severe damage and a considerable loss 10
the malo. À survey pape by Wang tal. 17] dsribes the
posible cytersecuiy cllnges ca bythe smart grid.
The concept a smar cess defined as the communication
ofall he devices in he city o sohe significan issues ike
trafic, publi Safety, emergency response. The work [18]
¿cues the cybenecuriy challenges encountered while
‘operating such à lag ety of comectd devices.
‘Cod computing can be defined a platform for storing.
managing and processing dats located o emo servers, hs
an be accessed using the internet. Cloud computing ams 1
reduce the cost of buying and maintaining servers by fering
Computer resources as services, The simpli! alison
‘Soul computing provide a insight no is concep, ends
and re diretns of chou compas (19). Availity
Of organizations and persona data on the ineretcload)
takes ita empsing large Ir eyberriminas Proper scurty
mesures should be taken 10 prevent cyber cis (2)
Denial Service stacks aim i wo bring down the service
fred by Roding the server with requests and making
Unrsponsive 0 legitimate requests. The cloud computing i
based on the socie model which makes 4 prone 10
DoS and DDS tacks. There is ongoing research on the
issues eased because of DDoS attacks in clou computing
and future directos [21]. Wi the Internet of Things and
Cloud computing technologies proliferating the integration
‘obo echaiqus as Boome a necesi, and the scary
‘hallenges ha can be fed must study (22
“The statin mentioned above manifest the importance of
eybersccurityedocaton and avareness that els 10 prevent
ber tacks in various domains, The ae several proposals
on the guidelines w design a eybersecuriy curclum.
Cy esscuriy eatin requires more practical and hand
on based leaming aprech [3], An analysis conducted by
Fred B. Schneider [24] on the cybersecurity education in
the univers states tat the course shoul be developed
ISBN: 1-60132-498-7, CSREA Press ©
compar atcks on éhal sates to achieve the tation
interests In traonal warfare, the nations fight physically
ut ina cyherwarire, there is no direct physical stack
Instead, evryhing is done in viral cybenpare lading ©
couse ines physical damage like, manipulating sada
‘onto, exploiting water plat, drang a vain which
has adverse ect onthe economy ofthe targeted maton
Stunt worm was designed 10 compromis Ian’ meter
program by manipulating the indus cotas without
Being notice by displaying normal conditions 1 the plan
engin, Reports were claiming tht the US. and Lunel
ovement designe the Suxaet worm as an act of yber-
‘arf. Cyber Temes cn be defined a the convergence
tri and cyberspace. Cyberteneis i the we of
“computer technology to cause severe disruption, ar and
Fear in the economy. I is related o Tour main aspect
‘computer generation, pital motivation, physical violence,
and psjcholgieal coercion [8
A recent work showcases the noces to bu! Items:
tional cooperation on cyber defense and detre agains
‘jhe terrorism. I showcases the possible was used by
the trono expli eyherspace and mentions tht every
‘county has its cyber ks ad incidence response teams.
propones tht thee should be a rob, itemationa eg
Framework under the contol ofthe UN that adresses all
the eybemccirity related cs and shire the inlignce
hse among tbe nations across the globe [9], The ra
{eal approach fr detertence of y ere is proposed
in LOL, discusses the challenges imohed in cyber
terri deemence and a robos framework 10 over
them. Another popular work surveyed the Psychological
‘elect of yber errors, They have conducted fel sey
‘experiments that simulated cyber ec and interviewed
522 individual The results ae analyzed on à score Of d
in which eer teorsm (Leta) is marked at 36, which
Shows severe psiloc impact [1
“The eye ack tagte at national influe leads
to sere harm, damage 1 the national economy and the
‘ens global peace The yber heats hat nation can fae are
Intemational tenes, sae-sponsord train, mals.
Fuck, Insider teal. The methods lo Cor thse
threats using intligenc are proposed in [12]. Thee ae
ao posits of insider estee 10 an organization
that may be used acidentally oe inteonall by the en
ployees À recen work analyzes th posible insider shea,
ow they rise problems in organizations and discuss he
awaits tha ar elvan lo vais scenarios (3)
A popular survey on types of eye aks and how they
‘an fe detected, classics the cyber attacks into 13 pet
including Denikoservice,ephereapionae, cyber temo.
im, cyber war, active ack andthe various approaches
including. agen-tased approach, arial ineligenos a
prosch tht can be sed in deletion and prevention of the
Int Cont. Frontier in Education: CS and CE | FECS'9 |
sacks (14, With the Intense research being conoced on
machine learning and dat mining researchers ae exploring
‘ways tose these two ares nto the cybersecuriy eld ode
tec invusion, A suey conducted on discovering the we of
machine lung and data ining in cyberscuiy ition
detection 3 presented in 15. Roy et al. proposed game
theory mode or addressing network scuiy problem and
surveyed the game designing techniques and tir outcomes
Da
Nowadays everything rom a device to a cy is Being
converted smart ens by integration of computing and
ommunicaton capabilities o. which makes them pre
lo epber stacks. The sit ges are the next generation
power supply and management systems, which ae par of
the era national infrastructure. A smart grid achieved
by combining advanced computing and communication tec
nologies o chance eficiensy in power management. The
Smart prs are one of the ot reis to the cyber tacks
AS bey may cae severe damage and a considerable loss 10
the malo. À survey pape by Wang tal. 17] dsribes the
posible cytersecuiy cllnges ca bythe smart grid.
The concept a smar cess defined as the communication
ofall he devices in he city o sohe significan issues ike
trafic, publi Safety, emergency response. The work [18]
¿cues the cybenecuriy challenges encountered while
‘operating such à lag ety of comectd devices.
‘Cod computing can be defined a platform for storing.
managing and processing dats located o emo servers, hs
an be accessed using the internet. Cloud computing ams 1
reduce the cost of buying and maintaining servers by fering
Computer resources as services, The simpli! alison
‘Soul computing provide a insight no is concep, ends
and re diretns of chou compas (19). Availity
Of organizations and persona data on the ineretcload)
takes ita empsing large Ir eyberriminas Proper scurty
mesures should be taken 10 prevent cyber cis (2)
Denial Service stacks aim i wo bring down the service
fred by Roding the server with requests and making
Unrsponsive 0 legitimate requests. The cloud computing i
based on the socie model which makes 4 prone 10
DoS and DDS tacks. There is ongoing research on the
issues eased because of DDoS attacks in clou computing
and future directos [21]. Wi the Internet of Things and
Cloud computing technologies proliferating the integration
‘obo echaiqus as Boome a necesi, and the scary
‘hallenges ha can be fed must study (22
“The statin mentioned above manifest the importance of
eybersccurityedocaton and avareness that els 10 prevent
ber tacks in various domains, The ae several proposals
on the guidelines w design a eybersecuriy curclum.
Cy esscuriy eatin requires more practical and hand
on based leaming aprech [3], An analysis conducted by
Fred B. Schneider [24] on the cybersecurity education in
the univers states tat the course shoul be developed
ISBN: 1-60132-498-7, CSREA Press ©
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
asd on the way how stacker tink which helps the
students to lea the discipline ofthe at of bing secure
Systems. A new NSA driven model for designing the cyber
‘evry cuiclum includes the teaching of eybeneruiy
Fundamental, polices, ad legal ethics (28). The elles
of à game basal eybersecury ining approaches are d
‘used in 126 (2) À popular work [28] applis challenge.
sed learning methodology 0 eybesscuntyclction tha
encoursgesstlens to collaborate, sk questions, gain i
dep Knowledge and uy to solve rel ori challenges,
“There ar various cyherseurty awareness delivery metodo
to the ers including, intctorled, online, game based,
simulation bsos delivery methods [29]. The subiscipines
including Network seur; web scort wage of tok,
forensics, shouldbe covered for elective eybersccury e
ation [30] The curen and futur tends of cybeecuiy
‘education are discussed in [I]
3. Proposed Method
34 Motivation
Before tating the design of the cous, stay has hen
conducted on eybenecuniy courses and their criclam
sffered in some ofthe renownod univers in the USA.
sol on this sty, while mont of these eures ince
some practical aspects of eybenccuity. they are most
result based, iin. A process Dal approach rks
mor ei, in making the eyberccuriy conos clear
tothe student [23] Classroom demonstration ofthe yber-
Security lets and he process of how the attacks happen
‘il cante the practical knowledge ater than hore
aspects
"The course is designed wih the aim of ofeing mor
practical knowlege by exploring the nen mechanisms of
tome socesfl cyber atch. The curs ofthe couse
‘comprises of 1S tos use o demons aout every type
of possible eybersecurty atack and forensics techniques
that are Ano Hi dt
32 Course Structure
‘The course we developed intodbees the hacker's pepe:
lve rater than a security personne’ perspective, which
‘enables the stants to Team the mind of à hacken at
Sages in [2] Every lb is conducted in a hands-on and
‘experiment based sting, a discusod in 23), Te proposed
une requires hase presque course on yen
ic might fave an obvious tile such a “Fundamentals of
Oybenesuriy” or "Foundational Computer Seuriy.” at
discusses the overall concepts of network fundamen
encryption techies, eybersecury: Types of eyber aac,
Perspectives, this, laws te, as popond in [251 Every
Speriment contin the following sections
+ Alm contains the desrption of the motive of the
eperiment
Fig. 1: Coune Labs
+ About discuses the description o the tas being used
in the experiment
+ Esmironment Setup discusses the instalation and setup
of the envionment required 10 perfom the ac.
Te includes tool istalion and comiguraion. This
‘ves hee understanding ofthe tol etre and is
the student to overcome any future challenges while
‘working withthe toa,
+ Methodology discusses the practica and dete step
y step press of performing the stack using he os,
33 Course Syllabus
‘The course comprise of 15 tots laid int even cat
prise Web-based attack wol, Vlnerahilty Exploitation
‘Tals, Password cracking tok, Social engineering tol,
Denial of Service tol, Freie tol, oer category wih
general sec tol. Te nos are selected sed mainly on
Seren creia. uneonaliy eis of we, documentation,
oss platform compatbiity and fe of cost. Figure 1 shows
the over labs inl in the designed coun
AA Web based attack Tools:
Web-bacd stick tools are und to perform attacks in
solving netweks and website vues, Four tcs ae
Semonsrtd in this coun,
+ Wet Tool: Wet tol is sed 10 download content
iteratively rom the web and minorin he websites or
ishing attacks
Zenmap Tool: Zenmap tol is used 1 scan the sy
Leman tht are connected othe network to de.
termine their OS (pe, communication protocol, apen
por, network topology. Route, ee
SQlmap Tool: SQLmap is used 1 hack ito a wulner-
able website database logar ll he user AZ login
Ewtereap Tool: Ferca Tool is used to sell the
amer erential ofthe vic by sing ARP poisoning
leone
ISBN: 1-60132-498-7, CSREA Press ©
asd on the way how stacker tink which helps the
students to lea the discipline ofthe at of bing secure
Systems. A new NSA driven model for designing the cyber
‘evry cuiclum includes the teaching of eybeneruiy
Fundamental, polices, ad legal ethics (28). The elles
of à game basal eybersecury ining approaches are d
‘used in 126 (2) À popular work [28] applis challenge.
sed learning methodology 0 eybesscuntyclction tha
encoursgesstlens to collaborate, sk questions, gain i
dep Knowledge and uy to solve rel ori challenges,
“There ar various cyherseurty awareness delivery metodo
to the ers including, intctorled, online, game based,
simulation bsos delivery methods [29]. The subiscipines
including Network seur; web scort wage of tok,
forensics, shouldbe covered for elective eybersccury e
ation [30] The curen and futur tends of cybeecuiy
‘education are discussed in [I]
3. Proposed Method
34 Motivation
Before tating the design of the cous, stay has hen
conducted on eybenecuniy courses and their criclam
sffered in some ofthe renownod univers in the USA.
sol on this sty, while mont of these eures ince
some practical aspects of eybenccuity. they are most
result based, iin. A process Dal approach rks
mor ei, in making the eyberccuriy conos clear
tothe student [23] Classroom demonstration ofthe yber-
Security lets and he process of how the attacks happen
‘il cante the practical knowledge ater than hore
aspects
"The course is designed wih the aim of ofeing mor
practical knowlege by exploring the nen mechanisms of
tome socesfl cyber atch. The curs ofthe couse
‘comprises of 1S tos use o demons aout every type
of possible eybersecurty atack and forensics techniques
that are Ano Hi dt
32 Course Structure
‘The course we developed intodbees the hacker's pepe:
lve rater than a security personne’ perspective, which
‘enables the stants to Team the mind of à hacken at
Sages in [2] Every lb is conducted in a hands-on and
‘experiment based sting, a discusod in 23), Te proposed
une requires hase presque course on yen
ic might fave an obvious tile such a “Fundamentals of
Oybenesuriy” or "Foundational Computer Seuriy.” at
discusses the overall concepts of network fundamen
encryption techies, eybersecury: Types of eyber aac,
Perspectives, this, laws te, as popond in [251 Every
Speriment contin the following sections
+ Alm contains the desrption of the motive of the
eperiment
Fig. 1: Coune Labs
+ About discuses the description o the tas being used
in the experiment
+ Esmironment Setup discusses the instalation and setup
of the envionment required 10 perfom the ac.
Te includes tool istalion and comiguraion. This
‘ves hee understanding ofthe tol etre and is
the student to overcome any future challenges while
‘working withthe toa,
+ Methodology discusses the practica and dete step
y step press of performing the stack using he os,
33 Course Syllabus
‘The course comprise of 15 tots laid int even cat
prise Web-based attack wol, Vlnerahilty Exploitation
‘Tals, Password cracking tok, Social engineering tol,
Denial of Service tol, Freie tol, oer category wih
general sec tol. Te nos are selected sed mainly on
Seren creia. uneonaliy eis of we, documentation,
oss platform compatbiity and fe of cost. Figure 1 shows
the over labs inl in the designed coun
AA Web based attack Tools:
Web-bacd stick tools are und to perform attacks in
solving netweks and website vues, Four tcs ae
Semonsrtd in this coun,
+ Wet Tool: Wet tol is sed 10 download content
iteratively rom the web and minorin he websites or
ishing attacks
Zenmap Tool: Zenmap tol is used 1 scan the sy
Leman tht are connected othe network to de.
termine their OS (pe, communication protocol, apen
por, network topology. Route, ee
SQlmap Tool: SQLmap is used 1 hack ito a wulner-
able website database logar ll he user AZ login
Ewtereap Tool: Ferca Tool is used to sell the
amer erential ofthe vic by sing ARP poisoning
leone
ISBN: 1-60132-498-7, CSREA Press ©
332 Vulnerability Exploitation Tools:
‘Vulnerability exploitation tools are used o exploit the
unpsched ylneaies presen in the system. Two tools
re demonstrate in his cours
‘+ Armitage Tot: Aritge tol is wed 10 gain backdoor
din access 1 the Windows 7 operating system which
allows the atacker to modify ls kyloging, taking
tereenhots and webcam shot, ee
+ Metasploit Framework: Metsplot framework s sol
Lo pm backdoor acces tothe Android operating sy
tem which allows the altcker (0 acces media es,
contacts tke scents, remote cling, ce.
333 Password eracking Tools:
Passwont cracking toos am to deco, identify the passe
‘word of the targeted system by using varios techniques and
lectins. Two tol are demonstrated in this couse
‘+ John the Ripper Took Joi the Ripper ol suse «>
‘rack ZgyRAR Be, Lino, Hash type passwords,
+ Mimikate Tool: Mimikatz tool is wel as a pos
exploitation too o cack into the user eredentals of
the Windows operating system which has been com
promised sing Armitage wo,
3.344 Social Enginering Tok:
Social Engineering Tools are wed to perform soc
engineering aus Ike phishing Baiting, Taig, ee.
Social Engineering ook i demonstrated in his course
+ Social Enginering Toolkit: Social Engineering alkit
is used to perform website pishing aac o al he
ter credentials,
335 Deniatot Service Toot:
Denal-of Service Tools sd o bring the server down by
Aooding it wäh requests. GoldenEye Tool is demonstrated
in this coun,
+ GoldenEye Tool: Goldene Tol is used 10 perform
à Denial service tack on he serve
336 Forenses Too
Forensics tol are usd to perform free analysis on a
system during the cinco response phase, Tec Free
tools are demonstrated in his cous,
+ The Sleuth Kit: The Sleuth Kit is wed to perform
forensic investigation by analyeing and recover dat
from disk image.
+ Volt Framework The Vol Framework is
sed to perform digital forensics imestigtion on the
Sole memory (RAM) of the stem,
+ FoloForensice Tool: Forensics tol is wed to an
alyze and dtet the properties and medications
Performa onthe ge
Int Cont. Frontier in Education: CS and CE | FECS'9 |
337 Other Took
+ GnuPG Toot GnuPG Too! is used to implement en-
cypton and derypion ofthe content shed by the
wer using the OpenPGP standard
Malte Tol: Matto tol used to discover and
map the connections between people, groups oa sei
networks. web domains, and Servers te. This helps
in understanding the whole picture and finding the
Vulnerables in the mapped network.
34 Student Learning Outcomes
A is wellknown that itis important to define student
teaming outcomes (SLO) as part of any undergraduate
Suriculum. Accreditation agencies such as ABET las tt,
guiones in ems of what language could te used to define
SLOs so hat they are quantiable and mesurable. For
the proposed hanvon oriented coun, we developed the
following SLOS
{Upon completion a he cure, the stent wil ge complete
understanding of
+ TCPAP vulnerbiiics, Man-In-The Mile atack us
ing ARP poisoning and Denia of Service stacks using
‘SYN packets.» Zenmap. GoldenEye. Etap Tools
Information exposed with open port, mapping of infor
mation gathered an en, dough vanous websites
incoling social-netwerking sites. company websites
te. Zenmap, Mallgo Tools
SOL injection, website phishing iterative downloading
cof web comen. Wget SQL map, Social Engineering
Tool cs
Vulnrube exploation of poplar operating systems
Android and Windows. = Meusphit Trumenork, Ar
mitge wol
Prety Good Privcy(PGP) cet standard and en
Spion algrthns.- GruPG Tool
Vars pasword cracking techniques including brut
Tore, Pos plan technique that captures he en
pie passwords, John the Ripper, Minikatz Tos,
Image forensics, dk image anal nclding RAM.
"The Sleuth Ki, Vlasity Framework, Fuchorensics.
too!
35 Armitage Tool: An Example Lab
‘To provide an night ino the course we designed, one
of te labs i discussed in move deal in ths sic: The
design ofthis ab has been previos, published [32]
351 Aim
In this experiment, Amitge toot i used in back“
door admin aces lo the Windows 7 opening system
sich allows ie attacher © modify ks, eyogging. king
Sorrento and webcam so, ele
ISBN: 1-60132-498-7, CSREA Press ©
‘Vulnerability exploitation tools are used o exploit the
unpsched ylneaies presen in the system. Two tools
re demonstrate in his cours
‘+ Armitage Tot: Aritge tol is wed 10 gain backdoor
din access 1 the Windows 7 operating system which
allows the atacker to modify ls kyloging, taking
tereenhots and webcam shot, ee
+ Metasploit Framework: Metsplot framework s sol
Lo pm backdoor acces tothe Android operating sy
tem which allows the altcker (0 acces media es,
contacts tke scents, remote cling, ce.
333 Password eracking Tools:
Passwont cracking toos am to deco, identify the passe
‘word of the targeted system by using varios techniques and
lectins. Two tol are demonstrated in this couse
‘+ John the Ripper Took Joi the Ripper ol suse «>
‘rack ZgyRAR Be, Lino, Hash type passwords,
+ Mimikate Tool: Mimikatz tool is wel as a pos
exploitation too o cack into the user eredentals of
the Windows operating system which has been com
promised sing Armitage wo,
3.344 Social Enginering Tok:
Social Engineering Tools are wed to perform soc
engineering aus Ike phishing Baiting, Taig, ee.
Social Engineering ook i demonstrated in his course
+ Social Enginering Toolkit: Social Engineering alkit
is used to perform website pishing aac o al he
ter credentials,
335 Deniatot Service Toot:
Denal-of Service Tools sd o bring the server down by
Aooding it wäh requests. GoldenEye Tool is demonstrated
in this coun,
+ GoldenEye Tool: Goldene Tol is used 10 perform
à Denial service tack on he serve
336 Forenses Too
Forensics tol are usd to perform free analysis on a
system during the cinco response phase, Tec Free
tools are demonstrated in his cous,
+ The Sleuth Kit: The Sleuth Kit is wed to perform
forensic investigation by analyeing and recover dat
from disk image.
+ Volt Framework The Vol Framework is
sed to perform digital forensics imestigtion on the
Sole memory (RAM) of the stem,
+ FoloForensice Tool: Forensics tol is wed to an
alyze and dtet the properties and medications
Performa onthe ge
Int Cont. Frontier in Education: CS and CE | FECS'9 |
337 Other Took
+ GnuPG Toot GnuPG Too! is used to implement en-
cypton and derypion ofthe content shed by the
wer using the OpenPGP standard
Malte Tol: Matto tol used to discover and
map the connections between people, groups oa sei
networks. web domains, and Servers te. This helps
in understanding the whole picture and finding the
Vulnerables in the mapped network.
34 Student Learning Outcomes
A is wellknown that itis important to define student
teaming outcomes (SLO) as part of any undergraduate
Suriculum. Accreditation agencies such as ABET las tt,
guiones in ems of what language could te used to define
SLOs so hat they are quantiable and mesurable. For
the proposed hanvon oriented coun, we developed the
following SLOS
{Upon completion a he cure, the stent wil ge complete
understanding of
+ TCPAP vulnerbiiics, Man-In-The Mile atack us
ing ARP poisoning and Denia of Service stacks using
‘SYN packets.» Zenmap. GoldenEye. Etap Tools
Information exposed with open port, mapping of infor
mation gathered an en, dough vanous websites
incoling social-netwerking sites. company websites
te. Zenmap, Mallgo Tools
SOL injection, website phishing iterative downloading
cof web comen. Wget SQL map, Social Engineering
Tool cs
Vulnrube exploation of poplar operating systems
Android and Windows. = Meusphit Trumenork, Ar
mitge wol
Prety Good Privcy(PGP) cet standard and en
Spion algrthns.- GruPG Tool
Vars pasword cracking techniques including brut
Tore, Pos plan technique that captures he en
pie passwords, John the Ripper, Minikatz Tos,
Image forensics, dk image anal nclding RAM.
"The Sleuth Ki, Vlasity Framework, Fuchorensics.
too!
35 Armitage Tool: An Example Lab
‘To provide an night ino the course we designed, one
of te labs i discussed in move deal in ths sic: The
design ofthis ab has been previos, published [32]
351 Aim
In this experiment, Amitge toot i used in back“
door admin aces lo the Windows 7 opening system
sich allows ie attacher © modify ks, eyogging. king
Sorrento and webcam so, ele
ISBN: 1-60132-498-7, CSREA Press ©
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
352 About
“Armitage plugs into the Meusplot framework and offers
à graphical ser interface, Armitage wol grphicl user
intere, visually represents the features, such as Kinng
à ot, len and sever exploitation, pvilege escalation
nd pivoting I contin the feature of dynamie workspace
mironment which allows the stack to change the targets
andthe tye of tack rapid. Amiage les people share
the same deuil and session. I opens shared sessions lo
teamwork while performing penetration testing. Armitage
hs ols call bots which cn be wed utoma dierent
Kinds of tasks. Armitage encapsulates, agregate, and ga
izes the tol hat are present in the Metasploit framework
ino an interac.
Armitage contains lt of postexplotaton wol hat are
execute on the vicimiAZS machine ale iis compro-
ised. By using these wol, an anche can find paso
hashes, note vitimdAZS kestoes execute command ine
omnis, gin rot pile, record video and mure. Alter
the victimiAZs machine iscompromised, Armitage eps the
acer 0 we the compromised target 10 launch another
fsck I his experiment we are going 0 se the Armitage
tool 0 hack ino the widows machine.
353 Environment Setup
2) Windows 7 Is
“Step
Im this atack. the operating system used is
Windows 7, To download the ISO fle click
heeps+//s0tt lay net /operating-systen/
windons- T-home-preniun-full-version-
Tren-daunload- 120-32-64-Dsc ‚henihere
and slot the Oli version. Now open the vial
ox and click onthe “Now” icon Ener te name as
“Windows 7. select type as "Microsoft Windows" and
version a “Windows 7 (610
+ Step 2
Now hit mex and allocate the memory size (RAM) of
1 GB. Then hit "neat and select “rete viral hard
Ask non” and lick “eat” Select "VDI (Vilos
Disk Image) inthe next menu Inthe next serene
the fle size of 40 GB and lick “rete”
+ Sup 3
Now click on the “segs” icon to open seins and
browse 10 “Storage Empty” Click on the disk icon
and select “Choose Vial Optical Disk File and then
Select the 150 fe download
+ Step 4:
Now stat the "Windows 7 Machine and proceed
through the installation process.
o) Postgres Installation: Postgres he database used
by the Moto frame w slow and reeves)
toads and expo, To install Posgresgl download fist
update the packages in the Ubont to do a execute the
following command
sado apt-get pda
Now excete the following command 1 isa he Post
sre =
do apt! install posten!
To check ithe Postgres is runing execute the folowing
command
Service postgres stats
+) Metasploit framework instalation:
+ Step:
To download the Metasploit graphical installer
dick” hteps://dounloads metasplott.
Con/data/telenses/metasploit-latest-
Yinux-x64- installer -runhere, Now open the
Aerminal and run i in oot mode ut ect "sudo
Sa" Now make he downloaded Metasploit executable
ty executing the folowing command.
"ehmod ex Rename”
Step 2:
Now run te installer by executing ih following com
“femme”
Follow through the tps of the installer and at e
end umelet the "Access Metsplot Web UI” and
Tit “Finish” Now restan the Metasploit service by
executing the follwing command
Service metasplot rsa”
4) Armitage tot installation:
+ Step ls To download the Armitage ar le click
http://w. fast andeasyhacking.com/
dow load/armitageis0si3.cgzhere. — Now
cuna the tar fle by cxecul the following
‘oman
tar aval lense”
Were xs extract fils rom an archive, : vrtnch
les pres, : ler the archive through grip E se
rtve fle or device ARCHIVE
‘Step 2: Now move the eurcicd Armitage folder into
the insted Metso folder by exscting the ollo
ing command
mv armitage fopuetspoit”
Change the directory 1 “amilae” by executing the
following command
ed puma”
+ Step 3: Before lurching he Armitage ol change the
‘network stings ofthe Windows machine and Ubuntu
{o "Internal network" o tha they oth are connected
in the same network and share the same subt
Now bunch the Armitage 10) hy exccting the lo:
ISBN: 1-60132-498-7, CSREA Press ©
Ea
352 About
“Armitage plugs into the Meusplot framework and offers
à graphical ser interface, Armitage wol grphicl user
intere, visually represents the features, such as Kinng
à ot, len and sever exploitation, pvilege escalation
nd pivoting I contin the feature of dynamie workspace
mironment which allows the stack to change the targets
andthe tye of tack rapid. Amiage les people share
the same deuil and session. I opens shared sessions lo
teamwork while performing penetration testing. Armitage
hs ols call bots which cn be wed utoma dierent
Kinds of tasks. Armitage encapsulates, agregate, and ga
izes the tol hat are present in the Metasploit framework
ino an interac.
Armitage contains lt of postexplotaton wol hat are
execute on the vicimiAZS machine ale iis compro-
ised. By using these wol, an anche can find paso
hashes, note vitimdAZS kestoes execute command ine
omnis, gin rot pile, record video and mure. Alter
the victimiAZs machine iscompromised, Armitage eps the
acer 0 we the compromised target 10 launch another
fsck I his experiment we are going 0 se the Armitage
tool 0 hack ino the widows machine.
353 Environment Setup
2) Windows 7 Is
“Step
Im this atack. the operating system used is
Windows 7, To download the ISO fle click
heeps+//s0tt lay net /operating-systen/
windons- T-home-preniun-full-version-
Tren-daunload- 120-32-64-Dsc ‚henihere
and slot the Oli version. Now open the vial
ox and click onthe “Now” icon Ener te name as
“Windows 7. select type as "Microsoft Windows" and
version a “Windows 7 (610
+ Step 2
Now hit mex and allocate the memory size (RAM) of
1 GB. Then hit "neat and select “rete viral hard
Ask non” and lick “eat” Select "VDI (Vilos
Disk Image) inthe next menu Inthe next serene
the fle size of 40 GB and lick “rete”
+ Sup 3
Now click on the “segs” icon to open seins and
browse 10 “Storage Empty” Click on the disk icon
and select “Choose Vial Optical Disk File and then
Select the 150 fe download
+ Step 4:
Now stat the "Windows 7 Machine and proceed
through the installation process.
o) Postgres Installation: Postgres he database used
by the Moto frame w slow and reeves)
toads and expo, To install Posgresgl download fist
update the packages in the Ubont to do a execute the
following command
sado apt-get pda
Now excete the following command 1 isa he Post
sre =
do apt! install posten!
To check ithe Postgres is runing execute the folowing
command
Service postgres stats
+) Metasploit framework instalation:
+ Step:
To download the Metasploit graphical installer
dick” hteps://dounloads metasplott.
Con/data/telenses/metasploit-latest-
Yinux-x64- installer -runhere, Now open the
Aerminal and run i in oot mode ut ect "sudo
Sa" Now make he downloaded Metasploit executable
ty executing the folowing command.
"ehmod ex Rename”
Step 2:
Now run te installer by executing ih following com
“femme”
Follow through the tps of the installer and at e
end umelet the "Access Metsplot Web UI” and
Tit “Finish” Now restan the Metasploit service by
executing the follwing command
Service metasplot rsa”
4) Armitage tot installation:
+ Step ls To download the Armitage ar le click
http://w. fast andeasyhacking.com/
dow load/armitageis0si3.cgzhere. — Now
cuna the tar fle by cxecul the following
‘oman
tar aval lense”
Were xs extract fils rom an archive, : vrtnch
les pres, : ler the archive through grip E se
rtve fle or device ARCHIVE
‘Step 2: Now move the eurcicd Armitage folder into
the insted Metso folder by exscting the ollo
ing command
mv armitage fopuetspoit”
Change the directory 1 “amilae” by executing the
following command
ed puma”
+ Step 3: Before lurching he Armitage ol change the
‘network stings ofthe Windows machine and Ubuntu
{o "Internal network" o tha they oth are connected
in the same network and share the same subt
Now bunch the Armitage 10) hy exccting the lo:
ISBN: 1-60132-498-7, CSREA Press ©
Ea
2
fen
ine command
After aunching it asks fr he systems IP address
on which tis running. Ue the “on command to
the check IP adres and ene i
54 Methodology
+ Step 1: Now in Armitage browse 0 “Hoss- Nap
Scan- Quick Scan (OS delet” and enter the IP aes
appear and right click on i 10 browse 1 "Hos
Operating System Windows 7
+ Step 2: Go to the modes
meter revert
pane in the left
and open the payed set
the LHOST (listener hos) o 6505 and output a "exe
Create a fokler named "pay" in the pad
“ohne and sore the generated “exe
+ Step 3: Now again select the same pay bu this
time set the output lo “mainder” which opens the
por 6565 on Ubuntu machine 1 cape the rover
+ Step 4: Now download the “exe” fe in he windows
machine by opening ntemet explorer and entering the
URL "Pads of Ubuntu machinepaylod” where
the files ote, Aer downloading run the “exe” le
«+ Step 5: Te windows system con inthe Armitage oot
< o red representing that ts explo
the meterpreer session opened and alo shows the IP
Shown in figure 2.
+ Step 6 Right cc où the system icon shows the
available exploits. For example. Sou can tae a sren
‘ho ofthe age system, access les, record ey og
Int Cont. Frontier in Education: CS and CE | FECS' |
Fig. 3 Available tacks onthe Windows machine (tim)
4. Conclusion
Now a days every device, from mobiles 10 intra
network, which makes eyber security most important aspect
in every indivi ie. With al the om going rescue in
the eyber security Fe new methods ar being developed to
‘machine leaning, data mining, but none ofthese out
beable to top the ober criminal from finding thse way o
jo foe help people and organizations defend gas the
ter security threats, According o a survey ondocted by
Ponemos nte 8 of te daa bese in eganiaions
fc sus by employee negligence 129. Repos also show
that Unies States ble Seco cf requires pproimatey
20100-30000 quai Cyber Secar specialists (33). Ths
{preparing the sent lo defend homes and the
Organization, from eybe security ach.
The hand-on exposure appaich is considered as one of
education [33]. Is achieved by cresting lab based Inia
tio euiculam which makes evry stunt vo perform the
experiments by offering the required environment nnd
‘effective implementation of 7 deren clases of cyber
stacks rough andan based approach o the students
References
ISBN: 1-00132-4987, CSREA Prose ©
fen
ine command
After aunching it asks fr he systems IP address
on which tis running. Ue the “on command to
the check IP adres and ene i
54 Methodology
+ Step 1: Now in Armitage browse 0 “Hoss- Nap
Scan- Quick Scan (OS delet” and enter the IP aes
appear and right click on i 10 browse 1 "Hos
Operating System Windows 7
+ Step 2: Go to the modes
meter revert
pane in the left
and open the payed set
the LHOST (listener hos) o 6505 and output a "exe
Create a fokler named "pay" in the pad
“ohne and sore the generated “exe
+ Step 3: Now again select the same pay bu this
time set the output lo “mainder” which opens the
por 6565 on Ubuntu machine 1 cape the rover
+ Step 4: Now download the “exe” fe in he windows
machine by opening ntemet explorer and entering the
URL "Pads of Ubuntu machinepaylod” where
the files ote, Aer downloading run the “exe” le
«+ Step 5: Te windows system con inthe Armitage oot
< o red representing that ts explo
the meterpreer session opened and alo shows the IP
Shown in figure 2.
+ Step 6 Right cc où the system icon shows the
available exploits. For example. Sou can tae a sren
‘ho ofthe age system, access les, record ey og
Int Cont. Frontier in Education: CS and CE | FECS' |
Fig. 3 Available tacks onthe Windows machine (tim)
4. Conclusion
Now a days every device, from mobiles 10 intra
network, which makes eyber security most important aspect
in every indivi ie. With al the om going rescue in
the eyber security Fe new methods ar being developed to
‘machine leaning, data mining, but none ofthese out
beable to top the ober criminal from finding thse way o
jo foe help people and organizations defend gas the
ter security threats, According o a survey ondocted by
Ponemos nte 8 of te daa bese in eganiaions
fc sus by employee negligence 129. Repos also show
that Unies States ble Seco cf requires pproimatey
20100-30000 quai Cyber Secar specialists (33). Ths
{preparing the sent lo defend homes and the
Organization, from eybe security ach.
The hand-on exposure appaich is considered as one of
education [33]. Is achieved by cresting lab based Inia
tio euiculam which makes evry stunt vo perform the
experiments by offering the required environment nnd
‘effective implementation of 7 deren clases of cyber
stacks rough andan based approach o the students
References
ISBN: 1-00132-4987, CSREA Prose ©
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
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ISBN: 1-60132-498-7, CSREA Press ©
m
w
m
mo
m
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Sa arto Confrence on Cyr Coat PIS EE
BE Kom ge Maman
Bea sungen
234-291, Taylor & Francis (2016) “ee
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SL
Saas
Rune See ath Nee,
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ISBN: 1-60132-498-7, CSREA Press ©
Int Cont. Frontier in Education: CS and CE | FECS'9 |
Cognitive Training
Mare Pat Alone Dai Cane Sn Ya,
Pal Capa Eng tial & Conte Engen Hal € Compa Enneng
‘Recent Nees Y ‘heise Ue Names © ‘hen Ut Noes
Dan mood USA Fond USA
cmp pen eds po a
Abat Copie merci fau on que
‘seine atte ee cmd md Sree
inthe bran The cp nets ide an meer
pape anne Ove tne te open of ds
{irra hich eds o wee ep fs ie
‘at ean ern rs hat when ped ih
A (i eat te ety Tee,
‘np mts dl and che th ope lle BEG
Ba recrded fem de ede tale er
ine "ne ul email mati ice rn,
‘Scheme engages mor. Ts BEG dat vd be wed
See pace at oi tape te sal Toy
eme et id hehe pee arte develope
‘Teepe sr the wer
ven Vr Rally, Ev nal (EEG)
Copain, Cp Tring
vay Hom parce fo pesca, boa nage, a
‘inde mod copie see rula Bon aero, lo
emy 1 lnguge The amontonan reeled 30
‘ites Aeris soy once out 7s percent less y
1 person a the age of 70 compared to à pers a the (18
Ta] vt technology advancing more and more very dy. i
{ery ey to mines in nea th ited ape
tha are adobe 1 the pl Otis ls i the ia
space may ot be tenia a al 1 the development of
nitive ls This rogram ie mento combine the best
th word, ing et tena fil ey
Inne a postive effect o he develope af egalive dll
‘Te we wi be jee io ie cern ed
‘ch of there environment wil ota game it rg
ei technlogie the HI Vive tl ety heel and
the Hay naeh, wil alow for the develpment and
ancement of copie se
Da Virtat Realty
As the nme implies, vial really ie + multe
ment commonly acme by à admet delay
Wh sna sree i don e te mere ge (De
Cognitive Ting Progam wll se device cle the TC
‘Vie, wiih its signe beet 1 be wen ınd
wed cloud wih pese 300 dere cales
Both desee sy on sensor o back movement of de
vies a well se bl goce tack the ses
‘ovement and place them i he silted iene
‘The setup fr the HTC Vive shown in ane
ouate tothe ser shout pepe wen the hen
A wei as how the nr shouldbe placed ln dr 10
Repas tac e Vie.
ip CV bp
II. Eectroencephatgram,
cated an decuoencepaleram(BEO), The EEG ls dee by
adas decbeds on a era scap 10d he sual of
codes ur he pacemen ofthe sion can ay om
‘Seat diese Far the follwing pep, the bl,
Aci i measured ung the Emol Imig heads a 5
‘Same res ER shown ip 2
‘ee Ei night ess pce.
‘The Ina is à str wer jst ike many aber
ows bot he na nd he Viv lo
‘esta ofthe user wilh a mob ande canes
‘Gmlaying vales fad fran ach tee Using the
Items 1070 syste, awe play tocas
{he elecroder ca the sap share he agit wl ete
gs.
ISBN: 1-00132-4987, CSREA Press ©
Cognitive Training
Mare Pat Alone Dai Cane Sn Ya,
Pal Capa Eng tial & Conte Engen Hal € Compa Enneng
‘Recent Nees Y ‘heise Ue Names © ‘hen Ut Noes
Dan mood USA Fond USA
cmp pen eds po a
Abat Copie merci fau on que
‘seine atte ee cmd md Sree
inthe bran The cp nets ide an meer
pape anne Ove tne te open of ds
{irra hich eds o wee ep fs ie
‘at ean ern rs hat when ped ih
A (i eat te ety Tee,
‘np mts dl and che th ope lle BEG
Ba recrded fem de ede tale er
ine "ne ul email mati ice rn,
‘Scheme engages mor. Ts BEG dat vd be wed
See pace at oi tape te sal Toy
eme et id hehe pee arte develope
‘Teepe sr the wer
ven Vr Rally, Ev nal (EEG)
Copain, Cp Tring
vay Hom parce fo pesca, boa nage, a
‘inde mod copie see rula Bon aero, lo
emy 1 lnguge The amontonan reeled 30
‘ites Aeris soy once out 7s percent less y
1 person a the age of 70 compared to à pers a the (18
Ta] vt technology advancing more and more very dy. i
{ery ey to mines in nea th ited ape
tha are adobe 1 the pl Otis ls i the ia
space may ot be tenia a al 1 the development of
nitive ls This rogram ie mento combine the best
th word, ing et tena fil ey
Inne a postive effect o he develope af egalive dll
‘Te we wi be jee io ie cern ed
‘ch of there environment wil ota game it rg
ei technlogie the HI Vive tl ety heel and
the Hay naeh, wil alow for the develpment and
ancement of copie se
Da Virtat Realty
As the nme implies, vial really ie + multe
ment commonly acme by à admet delay
Wh sna sree i don e te mere ge (De
Cognitive Ting Progam wll se device cle the TC
‘Vie, wiih its signe beet 1 be wen ınd
wed cloud wih pese 300 dere cales
Both desee sy on sensor o back movement of de
vies a well se bl goce tack the ses
‘ovement and place them i he silted iene
‘The setup fr the HTC Vive shown in ane
ouate tothe ser shout pepe wen the hen
A wei as how the nr shouldbe placed ln dr 10
Repas tac e Vie.
ip CV bp
II. Eectroencephatgram,
cated an decuoencepaleram(BEO), The EEG ls dee by
adas decbeds on a era scap 10d he sual of
codes ur he pacemen ofthe sion can ay om
‘Seat diese Far the follwing pep, the bl,
Aci i measured ung the Emol Imig heads a 5
‘Same res ER shown ip 2
‘ee Ei night ess pce.
‘The Ina is à str wer jst ike many aber
ows bot he na nd he Viv lo
‘esta ofthe user wilh a mob ande canes
‘Gmlaying vales fad fran ach tee Using the
Items 1070 syste, awe play tocas
{he elecroder ca the sap share he agit wl ete
gs.
ISBN: 1-00132-4987, CSREA Press ©
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
igre. ii ight Ite 19.20 so pco [1
‘etn diy nari ede
dunes potes mei cee,
IV. Cage Trate
none and understands thous owe. experience,
‘wich rc o tin fran Clas that indude memory,
‘vocabulary. Anat aplication fr mobile
(lies Mie, vhs à eo heat ate meter in
fede 1 ait the fey of me], Maher ne
for een who get wpe easly, withthe ies of tn
‘hem fo cone er emo by having 10 elm down i
‘de to progress roo he un.
allows many distractions to occur depending om the
nomad
sta good the user e placed to à
‘co VR Cope ting Ds ord fe
opin talon ane ta wheat scant
‘om mig De pe aced coma Tee Lamony
‘thir ann rio ong sth
Era
they ate steed, ately ring où rss may notte the
bat fr cognitive ining More performance mer wi
ee inselecing cole sien By sng e EEG,
the prog de le lo ect Be change in ie toes
perfomance mens, shom a Figure 4. ad aut the
‘Sul tir ocur or dto be pme ns os ey
Tor example Figure tis an example sel me teeing
rue peremancs meiesincioog tre, empre,
seed, tement focus nd lan
pr, Emi Porc mai
all mel de Como me au 5 bone
Hopi ande pee ss piro
Wal use bath rentes programed vil ay ting fom
Valen whee use ie ranting, Doping
ie ote whee the ochpadi reed the wer wl eer
teleport oder tonavigat cunde ara fra ee ew
5 Arge te drecton ofthe ver a inerseons
Vitro here i an aro Tr willbe fig ra where
rando else aber we opped and wil ow hante
oveyer eit Ther wil then change the icons atte
rm in edt Arc the ed ae no Me repose
Colored in The game play which eel he user sa,
ow many of he tee es ey ave ren. a well
ihe amount of ars Baer he aveo recto move e.
tothe nex level Ua the perfamunes mens, the game
‘wil ether bene mee Aol y increas he seed of
ie conveyor bet nd nceniag the mr af be he
fame wl come lees ficult by sowing down he seed
he conveyer belt dcrening the number our at
‘op. Tas willie teu progres trough er game at
tha own pace working arn as they wat aston hey
yee Dic pág Comos um
e fois ho in Fae 6 e Mol ence
em emy coges mi ire 7, De
ae esa with 23 by 3 mat whoa sequence of
chest When the start nt le pe by ane of he
nee Be un wll te om ler pop ve fea de
‘nnd anon qe Te we toa
sequence ao à wall loa Ar he et
ISBN: 1-00132-4987, CSREA Press ©
El
igre. ii ight Ite 19.20 so pco [1
‘etn diy nari ede
dunes potes mei cee,
IV. Cage Trate
none and understands thous owe. experience,
‘wich rc o tin fran Clas that indude memory,
‘vocabulary. Anat aplication fr mobile
(lies Mie, vhs à eo heat ate meter in
fede 1 ait the fey of me], Maher ne
for een who get wpe easly, withthe ies of tn
‘hem fo cone er emo by having 10 elm down i
‘de to progress roo he un.
allows many distractions to occur depending om the
nomad
sta good the user e placed to à
‘co VR Cope ting Ds ord fe
opin talon ane ta wheat scant
‘om mig De pe aced coma Tee Lamony
‘thir ann rio ong sth
Era
they ate steed, ately ring où rss may notte the
bat fr cognitive ining More performance mer wi
ee inselecing cole sien By sng e EEG,
the prog de le lo ect Be change in ie toes
perfomance mens, shom a Figure 4. ad aut the
‘Sul tir ocur or dto be pme ns os ey
Tor example Figure tis an example sel me teeing
rue peremancs meiesincioog tre, empre,
seed, tement focus nd lan
pr, Emi Porc mai
all mel de Como me au 5 bone
Hopi ande pee ss piro
Wal use bath rentes programed vil ay ting fom
Valen whee use ie ranting, Doping
ie ote whee the ochpadi reed the wer wl eer
teleport oder tonavigat cunde ara fra ee ew
5 Arge te drecton ofthe ver a inerseons
Vitro here i an aro Tr willbe fig ra where
rando else aber we opped and wil ow hante
oveyer eit Ther wil then change the icons atte
rm in edt Arc the ed ae no Me repose
Colored in The game play which eel he user sa,
ow many of he tee es ey ave ren. a well
ihe amount of ars Baer he aveo recto move e.
tothe nex level Ua the perfamunes mens, the game
‘wil ether bene mee Aol y increas he seed of
ie conveyor bet nd nceniag the mr af be he
fame wl come lees ficult by sowing down he seed
he conveyer belt dcrening the number our at
‘op. Tas willie teu progres trough er game at
tha own pace working arn as they wat aston hey
yee Dic pág Comos um
e fois ho in Fae 6 e Mol ence
em emy coges mi ire 7, De
ae esa with 23 by 3 mat whoa sequence of
chest When the start nt le pe by ane of he
nee Be un wll te om ler pop ve fea de
‘nnd anon qe Te we toa
sequence ao à wall loa Ar he et
ISBN: 1-00132-4987, CSREA Press ©
El
eva, he game will then ue the performance mice to
denis fe pane said become mer cl by
Increasing te amber of sleet the sequence of by
‘craig the ae ofthe max. Te Cary te the
une determines at he game sheuldbecane es il,
Re game wil deen he aie of De sequence and wil
cree the az of the man, Tis wil help the woe
Pros a thrown pace.
gee 7 Bates ong seus con
Int Cont. Frontier in Education: CS and CE | FECS'9 |
‘he visa ety games have been crewed and ested
‘The BEG aa eve rom the ight hs bee integrated
svi Unty in oder fo make the Unity gamer pt he
{ete fueras and ecctemet. The games wil became
(ca whee Care ious items ne ve hgh fron,
Betr become more cu when the sre low andthe
eig
ie projects det, eig Ihe progam i om the
este. A aba willbe rester progres
{ewer wh wil repeat the program trash specified
time Thi aba wi lo euere ac he prosrest
‘om the Deglanng. AU be sane tine, move gen ca De
‘edo ute devlopsndeance er eevee
IN peDastonine, gi he
BEE
rat ge mins
In AE ea Fe. (ed he er
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(8 Al Deen “Tn tag TE et hc ba yo
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e bi mer aia St
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ISBN: 1-00132-4987, CSREA Press ©
denis fe pane said become mer cl by
Increasing te amber of sleet the sequence of by
‘craig the ae ofthe max. Te Cary te the
une determines at he game sheuldbecane es il,
Re game wil deen he aie of De sequence and wil
cree the az of the man, Tis wil help the woe
Pros a thrown pace.
gee 7 Bates ong seus con
Int Cont. Frontier in Education: CS and CE | FECS'9 |
‘he visa ety games have been crewed and ested
‘The BEG aa eve rom the ight hs bee integrated
svi Unty in oder fo make the Unity gamer pt he
{ete fueras and ecctemet. The games wil became
(ca whee Care ious items ne ve hgh fron,
Betr become more cu when the sre low andthe
eig
ie projects det, eig Ihe progam i om the
este. A aba willbe rester progres
{ewer wh wil repeat the program trash specified
time Thi aba wi lo euere ac he prosrest
‘om the Deglanng. AU be sane tine, move gen ca De
‘edo ute devlopsndeance er eevee
IN peDastonine, gi he
BEE
rat ge mins
In AE ea Fe. (ed he er
(Sie
(8 Al Deen “Tn tag TE et hc ba yo
nn ra D [ee] Pcl hy DO Arte
AS
EN)
1H Engr GO Em Vr MaS rate CA
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ISBN: 1-00132-4987, CSREA Press ©
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
Co-construction of Computer Science knowledge-to-be-taught in a
French context
‘T Duron!, Y Chiprianov? and L. Gallon’,
HLAUPPA. Univenity of Pau and Pays de Adour Pau, France
AIRISA, University of South Briain, Rennes, France
Abstract—The French national curricula for elementary
‘and secondary schools introduced teaching Computer Se.
fence (CS) concepts as mandatory. Benning the 20162017
school year This aso raised questions related o specifically
hat CS concepts shouldbe taught and ho Several pro.
posal of teubools, pedagogical Kin and ether knowledge
ferbetanght have ben made: some of them contain a
parently surprising and even what seems, ata fst lane
Scienifcaliy incorrect knowledge, which cold prove tobe
tales pup’ learing In hs paper we anale such
Proposals, and advance explanations based on the Theory
(ofthe Didactic Transposition of Knowledge (TDTK). The
TDTK consider at he Anleger ah sh result
fa complex proces of various interactions and negotiations
bene the numerous actor ofthe educational stem. Me
enify such interactions, which explain the existence of
“ido obsaces Being aware of such caveats may reduce
ihe apparition ofthis typeof ebstctes in fnur construción
of simios CS bodies of knowledge tobe taht.
Keywords: K.12, Comput! Thinking. Didi, cure
sign and aay
Introduction
‘The mandaory introduction of Computer Science (CS)
‘concepts in the French elementary (6-10 years old) and
mie (11-14 casa) school national curul, begining
the school ear of 20162017 [1], has had profound impacts
fom wha and how CS is ght in France, However sapin
may this have heen for some, it was not lolly without
Prevent nthe T980s thee was a movement a caching
(CS anceps (and training teachers according), which was
replaced the 1990s with teaching Digital Literacy for
‘tails on the istry of teaching CS in France ef. (2)
Following. the international wend on Computational
‘Thinking [3], and report, sch as that of the Academy
of Sciences (8, pinplating Face lateness in ating
proper CS teaching ln elementary and mide school the
Poli decison was taken to inde CS concepts in he
ational cuicla for these levels I shold be note tht
due to historical decisions (at this pont France did not
he any primary or mide schoo! teaches that had been
Forma tine in CS, ony in Digital Liters.
Fig, 1: Except fom Mission
AAs a comequense of this incoación, a number of
resources, ithe form of textbooks, Cuba) polagogcal
‘its ecommendaton documents, hive ben proposal
Designing such proposals is important, however, 8 only
par of the continuous improvement education proces. To
{rate the potential of such resources, questions ned o
amer, sch a: Whi the knowledge such resources
sm 1 teach? How is this knowledge actly tag by
teachers and leamed by pupils? Moreover, some of thse
resources contain a numberof “etes” tht could tit
lance, be classe mu, and which cold become
bales in pupils lamin. How were such “are”
inroduced and possible inthe fist place?
‘One sich example concems the Pit [SIG] pau:
kcal hit sig the Thy! robo for inrdcin robots
and programming. especially in elementary’, bt als mile
School nob is dstibted under a CC-BY ene and
has engendered several developmen and versions. We fous
here onthe 2018 version IS
TniRobot proposes a sequence of 14 missions of which
mission 347 them (e "Si los.) intodes, in
fl o eminology, the concepts of event and action, fom
ventdriven programming. Thymio has 6 preprogrammed
Beier, of which, mission 3 proposes exercises, 10 dis
cover 4 The connacttbedas enercne for the behavior
called The explorer (yellow) (Te “Lexplerateur Gane)
is presented in Fi, 1. The “evens” (or mae, a we will
sce teow, the condi on which the evens are Hered)
ase induced dy the word TF (e "ST and the ations ae
inroduce by the word THEN (fr. "ALORS”) The expected
resul the discovery ofthe explorer Behavior sing the
Ribot terminology)" Thymio detects an objet in font
Nisam nd mare
ISBN: 1-60132-498-7, CSREA Press ©
Co-construction of Computer Science knowledge-to-be-taught in a
French context
‘T Duron!, Y Chiprianov? and L. Gallon’,
HLAUPPA. Univenity of Pau and Pays de Adour Pau, France
AIRISA, University of South Briain, Rennes, France
Abstract—The French national curricula for elementary
‘and secondary schools introduced teaching Computer Se.
fence (CS) concepts as mandatory. Benning the 20162017
school year This aso raised questions related o specifically
hat CS concepts shouldbe taught and ho Several pro.
posal of teubools, pedagogical Kin and ether knowledge
ferbetanght have ben made: some of them contain a
parently surprising and even what seems, ata fst lane
Scienifcaliy incorrect knowledge, which cold prove tobe
tales pup’ learing In hs paper we anale such
Proposals, and advance explanations based on the Theory
(ofthe Didactic Transposition of Knowledge (TDTK). The
TDTK consider at he Anleger ah sh result
fa complex proces of various interactions and negotiations
bene the numerous actor ofthe educational stem. Me
enify such interactions, which explain the existence of
“ido obsaces Being aware of such caveats may reduce
ihe apparition ofthis typeof ebstctes in fnur construción
of simios CS bodies of knowledge tobe taht.
Keywords: K.12, Comput! Thinking. Didi, cure
sign and aay
Introduction
‘The mandaory introduction of Computer Science (CS)
‘concepts in the French elementary (6-10 years old) and
mie (11-14 casa) school national curul, begining
the school ear of 20162017 [1], has had profound impacts
fom wha and how CS is ght in France, However sapin
may this have heen for some, it was not lolly without
Prevent nthe T980s thee was a movement a caching
(CS anceps (and training teachers according), which was
replaced the 1990s with teaching Digital Literacy for
‘tails on the istry of teaching CS in France ef. (2)
Following. the international wend on Computational
‘Thinking [3], and report, sch as that of the Academy
of Sciences (8, pinplating Face lateness in ating
proper CS teaching ln elementary and mide school the
Poli decison was taken to inde CS concepts in he
ational cuicla for these levels I shold be note tht
due to historical decisions (at this pont France did not
he any primary or mide schoo! teaches that had been
Forma tine in CS, ony in Digital Liters.
Fig, 1: Except fom Mission
AAs a comequense of this incoación, a number of
resources, ithe form of textbooks, Cuba) polagogcal
‘its ecommendaton documents, hive ben proposal
Designing such proposals is important, however, 8 only
par of the continuous improvement education proces. To
{rate the potential of such resources, questions ned o
amer, sch a: Whi the knowledge such resources
sm 1 teach? How is this knowledge actly tag by
teachers and leamed by pupils? Moreover, some of thse
resources contain a numberof “etes” tht could tit
lance, be classe mu, and which cold become
bales in pupils lamin. How were such “are”
inroduced and possible inthe fist place?
‘One sich example concems the Pit [SIG] pau:
kcal hit sig the Thy! robo for inrdcin robots
and programming. especially in elementary’, bt als mile
School nob is dstibted under a CC-BY ene and
has engendered several developmen and versions. We fous
here onthe 2018 version IS
TniRobot proposes a sequence of 14 missions of which
mission 347 them (e "Si los.) intodes, in
fl o eminology, the concepts of event and action, fom
ventdriven programming. Thymio has 6 preprogrammed
Beier, of which, mission 3 proposes exercises, 10 dis
cover 4 The connacttbedas enercne for the behavior
called The explorer (yellow) (Te “Lexplerateur Gane)
is presented in Fi, 1. The “evens” (or mae, a we will
sce teow, the condi on which the evens are Hered)
ase induced dy the word TF (e "ST and the ations ae
inroduce by the word THEN (fr. "ALORS”) The expected
resul the discovery ofthe explorer Behavior sing the
Ribot terminology)" Thymio detects an objet in font
Nisam nd mare
ISBN: 1-60132-498-7, CSREA Press ©
Int Cont. Frontier in Education: CS and CE | FECS'9 |
aan ] [Hermann
‘tetera pa
ezo fa | an rt
L
Dr
CS
coats
||
ig. 2: The didactic transposition proces, rom [7]
off, THEN i goes tack “IF Thymio detects an objet
‘ts igh, THEN i tors lt “IE Tymio dost detect,
thing, THEN i adtaces” "IF Thymio detest an objects
ns Tel, THEN it turns igh. The use of the word
‘ay’ come as a sures, and gly 50, a the concept i
noes is elated to an vent, The Asch tal editor
for programming Thymio even uses the keyword WHEN,
ut the Ascba Visual Programming Language (VPL) uses
the keyword TE. One would expect the we of the same word
in he graphical editor as in the tex one - WHEN (ir
QUAND’). ‘While this may seem insignificant, here are
‘uses in which pais are dnt (Cf. Fig. 3)
In what fllows we gue that such fetes" are not
simple “errs, but the result of à complex proces of
transformation of the scholarly Knowledge ino Knowledge
lo tap In hi process many cts are moved. vi
dire consens, numerous constant, whose soltions
Are sometimes sumpesing
2. Didactic Transposition of Knowledge
Knowledge, a his aught inthe School, nt immutable
‘isa human construc so as 10 ull paricular gol, AS
als evolve thoagh tine and to follow changes in socie
the knowlege taht in the Scho! voles as well. As
some ofthe main goals are related teaching Beginners. he
Knowledge taught in school diles fom the knowledge ai
as fs rented hy researchers itis simple”, diferent
Structured. ovelps and condicions have bcn limite
the Scholar. scenic Knowledge has been subject lo a
series ol teasforations, for 4 lo become knowledge ©
be tug in School. It has ben argued that “(bodies of
Knowledge are, with afew exceptions pot designed 0 te
tang ut o be used T each a od of knowledge ss
high artical enterprise” [8
In this paper we imestigte how such transformations
ase happening in the CS cucuta that is being defined
“uen in France. The décisions of which subjects, rom
the broad CS sie Knowledge, o choo or teaching is.
inuenced by various acts, rom high pola levels sich
a mines und academicians 1 ator cloro the train
Such as tachers, escaner as collbortors of tsches und
à sat of the system. To analyze ths stem and how
i inuences the wanematons onthe CS knowledge to
Fe laugh, we adopt a theoretical Background based on the
“Theory ofthe Didac Trampostion of Knom edge CTDTK).
‘Didactics is he scene of the difusion of knowledge in
any insitaon (e. class of pups, society at age). More
riculary 4 i de siehe study (and the Knonledge
resuling her of the innumerble ations taken 1 case
(oe impede) the difusion of such and such a body of
Knowledge in such and such aniston [91 The TDTK
has original teen proposed in French, in the 1980. and
has achieved a wide spread and aeeptnce in th French“
speaking communities, alo in the Spanish-speaking. but
‘much ss inthe Eglise communities, o dob
also because of eaivey Te and It tanins (which
‘we selected afew in he bibliography of is paper na).
tis theory nia propose in the context of mathematics,
teaching, but bis sine evolved to encompass teaching of
er science subjects such as biology and geography.
“The Theory ofthe Didactic Tunspositon of Knowledge
(TDTK) SL. {10}, ses he "anio from Knonladge
1 tool o e put to us, to Knowledge a something tobe
tayght and lead”, Let us note that for un in ths pops,
the concept of Lae, in all os further decintions
comprises both Sl. Know-how (soi fie). as well
theoretical” Anowiodge (fe sai)
‘The TDTK distinguishes dus several ypes of knowledge
The scholarly bodies of) knowledge (I. savir savant)
denotes “an egatized and more or Is integrated whole”
Ish, Wis produced by researchers and scholars, usally
integrated ln theories, to be found in vescarch ales and
scie books, Taking his type of Knowledge as sr
ine point, the TDTK ses how À is momo into
Inrtedgeso-besaught (I. savoir à enseigne), which à
the "scholarly knowledge that exists only in contexts han
‘aon be fal replicated within choo” (8, sally as.
appears in cuit txtboks and ter similar sources.
This fumer transformed ito taht Knowledge (soir
ensignó - "he knowledge which becomes visible, so 10
Speaks in the classroom” 10), a Hf presented in the
paul comext of class, by a panlcular teacher, 10
3 pariculr group of pupils etc. OF couse. theres a
further dilference between the taugt knowledge and what
scully leamed by pupils, the learned knowledge (soir
appris comaísances). À synthetic view ofthe TDTK is
presented in Fig. 2.
“These wranformaions are the resol of interactions be
tween actos of the educational system. The totaly of
those actors form what i cal, in the TDTK, the dec
hooper he "sper" 0 those who in abou teaching
[HO] al tose who shar an interest in the teaching system.
1 consis ofthe agent = those actors who ae in charge
of knowledge (eg. teaches), but abo af the ai» those
sanding outside the teaching sphere, Obviously, dierent
people hive dilleen onu in respect to education.
ISBN: 1-60132-498-7, CSREA Press ©
aan ] [Hermann
‘tetera pa
ezo fa | an rt
L
Dr
CS
coats
||
ig. 2: The didactic transposition proces, rom [7]
off, THEN i goes tack “IF Thymio detects an objet
‘ts igh, THEN i tors lt “IE Tymio dost detect,
thing, THEN i adtaces” "IF Thymio detest an objects
ns Tel, THEN it turns igh. The use of the word
‘ay’ come as a sures, and gly 50, a the concept i
noes is elated to an vent, The Asch tal editor
for programming Thymio even uses the keyword WHEN,
ut the Ascba Visual Programming Language (VPL) uses
the keyword TE. One would expect the we of the same word
in he graphical editor as in the tex one - WHEN (ir
QUAND’). ‘While this may seem insignificant, here are
‘uses in which pais are dnt (Cf. Fig. 3)
In what fllows we gue that such fetes" are not
simple “errs, but the result of à complex proces of
transformation of the scholarly Knowledge ino Knowledge
lo tap In hi process many cts are moved. vi
dire consens, numerous constant, whose soltions
Are sometimes sumpesing
2. Didactic Transposition of Knowledge
Knowledge, a his aught inthe School, nt immutable
‘isa human construc so as 10 ull paricular gol, AS
als evolve thoagh tine and to follow changes in socie
the knowlege taht in the Scho! voles as well. As
some ofthe main goals are related teaching Beginners. he
Knowledge taught in school diles fom the knowledge ai
as fs rented hy researchers itis simple”, diferent
Structured. ovelps and condicions have bcn limite
the Scholar. scenic Knowledge has been subject lo a
series ol teasforations, for 4 lo become knowledge ©
be tug in School. It has ben argued that “(bodies of
Knowledge are, with afew exceptions pot designed 0 te
tang ut o be used T each a od of knowledge ss
high artical enterprise” [8
In this paper we imestigte how such transformations
ase happening in the CS cucuta that is being defined
“uen in France. The décisions of which subjects, rom
the broad CS sie Knowledge, o choo or teaching is.
inuenced by various acts, rom high pola levels sich
a mines und academicians 1 ator cloro the train
Such as tachers, escaner as collbortors of tsches und
à sat of the system. To analyze ths stem and how
i inuences the wanematons onthe CS knowledge to
Fe laugh, we adopt a theoretical Background based on the
“Theory ofthe Didac Trampostion of Knom edge CTDTK).
‘Didactics is he scene of the difusion of knowledge in
any insitaon (e. class of pups, society at age). More
riculary 4 i de siehe study (and the Knonledge
resuling her of the innumerble ations taken 1 case
(oe impede) the difusion of such and such a body of
Knowledge in such and such aniston [91 The TDTK
has original teen proposed in French, in the 1980. and
has achieved a wide spread and aeeptnce in th French“
speaking communities, alo in the Spanish-speaking. but
‘much ss inthe Eglise communities, o dob
also because of eaivey Te and It tanins (which
‘we selected afew in he bibliography of is paper na).
tis theory nia propose in the context of mathematics,
teaching, but bis sine evolved to encompass teaching of
er science subjects such as biology and geography.
“The Theory ofthe Didactic Tunspositon of Knowledge
(TDTK) SL. {10}, ses he "anio from Knonladge
1 tool o e put to us, to Knowledge a something tobe
tayght and lead”, Let us note that for un in ths pops,
the concept of Lae, in all os further decintions
comprises both Sl. Know-how (soi fie). as well
theoretical” Anowiodge (fe sai)
‘The TDTK distinguishes dus several ypes of knowledge
The scholarly bodies of) knowledge (I. savir savant)
denotes “an egatized and more or Is integrated whole”
Ish, Wis produced by researchers and scholars, usally
integrated ln theories, to be found in vescarch ales and
scie books, Taking his type of Knowledge as sr
ine point, the TDTK ses how À is momo into
Inrtedgeso-besaught (I. savoir à enseigne), which à
the "scholarly knowledge that exists only in contexts han
‘aon be fal replicated within choo” (8, sally as.
appears in cuit txtboks and ter similar sources.
This fumer transformed ito taht Knowledge (soir
ensignó - "he knowledge which becomes visible, so 10
Speaks in the classroom” 10), a Hf presented in the
paul comext of class, by a panlcular teacher, 10
3 pariculr group of pupils etc. OF couse. theres a
further dilference between the taugt knowledge and what
scully leamed by pupils, the learned knowledge (soir
appris comaísances). À synthetic view ofthe TDTK is
presented in Fig. 2.
“These wranformaions are the resol of interactions be
tween actos of the educational system. The totaly of
those actors form what i cal, in the TDTK, the dec
hooper he "sper" 0 those who in abou teaching
[HO] al tose who shar an interest in the teaching system.
1 consis ofthe agent = those actors who ae in charge
of knowledge (eg. teaches), but abo af the ai» those
sanding outside the teaching sphere, Obviously, dierent
people hive dilleen onu in respect to education.
ISBN: 1-60132-498-7, CSREA Press ©
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
‘Therefore, “Wis the sk of the moosphere o cope sith
the demands made by sity onthe teaching stem, by
‘ransmuting them nto conditions acceptable to both pais
city and its teaching system” 110, Coneguenty. the
‘ental function ofthe mosphere i the meet with the
Soviet, aking into account deren condon, coms,
ruine in compromises.
"We fous in thi operon analyzing the dic tans
sion of CS know ede related the introduction of ment
programming based on IiRobe, a it happens in the conten
fof a research and taining project - PERSEVERONS'. We
do emphasize dat er actions, Knowledge and research
fate happening in PERSEVERONS, which are out ofthe
‘Scope of thin paper. In his context, we have denied as
gent of the educadora system: the Curcula Superior
‘Council (Conse! mpéricar des programmes) the body
‘which deines the national French CS cuca, CS und
Leaming Scenes researchers, CS pedagogical counselors
(le Emcignantsréerns pour les wage du numérique,
‘primary and secondary schoolteachers. In the not stos
"Se aulgze how these agents ae iterating in press
(of negotiation and co-comstrcion - à process of defining
together, through interactions more or less diet - oa CS
3. The co-construction process
Inthe coment of our case study based on IniobaL it
sms sa ir assumption that he knowledgeto bea
Soul revolve around robots and their programming. We
investigate in this section the transposon of such know
‘le rom the def of cha knowledge of what e
‘alle event-driven programming (one of te mai paradigme
‘ed for programming robos). 10 is transformation In
Knowledgetorbetaght, as fund in the French national
curicla and inthe Inohos pedagogical ki (and one of
ls declinación, the IniRobar for Schoo) and fuer ino
‘aught and lear Knowledge, observed in regalar French
School, while emphasing the actions of dienen acts
involved in each phase
3.1 Defining the scholarly knowledge
Providing a complete historical and epistemological tay
on he CS concepts ached 1 eentaiven programming i
‘ofthe spe ofthis paper However. we do indicate tha
the concept usually considered a im relation withthe 0:
‘called even driven paradigm have oon defined in sever
places, in diferen mann, with dient names, and
{hough there are commonalities among these definons,
there ar also numerous and important dienen.
Tor example, 11] defines a computational ven as “any
‘hing hat happens inthe course ol «comput bah
occurrences in th program el. a well as cocurencos
‘ouside the computton proper”. A Similar and more pre
ape aie
definition is that of 112. fo which evens ar “he trams
tions Between ses that may appear in a system or it
cironment, Plea noce tha thes defnlions consider
bth the external and the internal nature of evens
‘Other authors. Ike for example Turing-avanl winner L.
Lamport [13]. oler a more complete picture, speaking of
several concep: events (which are nor Formally define
processes, messes (defined asthe means of communication
mong spl iin processes - seu ystems and
‘whose sending or eceivng ae considered an een, pal
nderin (ofthe sending and reception of messages) logical
and physical clocks (or synchronization) ec
1A] speaks ahou waiting for an event in which ease the
program cannot complete un operation immediatly and us.
register callback = function na wil De invoked when
the even occurs. This wating is typical done in kop
that pols or evens and encts the appropri callback
hen the event occur. To dileentit btucen event
‘mechanisms of Being [..] by a combi” 112. which
provide an event every time condon ste, ae nde
A concep! similar tothe cick isthe even handler = à
method “able to respond to one Kind of external action (or
ven [IS]. An event is defied as an tema cin
‘Other researchers make a différence een what is
called dreaded or procedure orienta) and event-driven (or
message oriente) programming modeluhytem [14 ing.
er lo show tete daly eg. (16, oe the precedence ol
‘one over the lle (a cas in some contexts) eg. 14117
Defining the concep reed o the so called “eve
sven programming paradigm” has three been à ong
roces, in wich several CS researchers (the only type of
tors and more precisely ly in TDTK terminology in
this pao) have Bul on or against the work of previous
researchers. The resubingscholaly knowledge may have
ride that enable construcion of el work applications
(use of Led) ut i sll a rater lt snd
specialized body to understand, sr and cast.
32 Defining the knowledge-to-be-taught : the
curricula
In France, a disncionsusaly made between 2 ype of
Knowledge: tagt: te national eurcua resold from
the extemal imposition proces of schol knowledge
and which serves asa reference document for the second
‘ype of knowledgeso-be-taugh, which comprise textbooks,
Vencer rain documents ad ether smile documents. The
arcs self he esl of negation process between
Several organizaons and coun. The Consul Superior
Count the body which deines the national French
curricula for elementary and middle scho. However it
‘oes not work in lation, ad an analysis of 6 CS 2016
arcu] shows a number of infueces rom repo of
the Academy of Sciences FA, to athe organization such as
ISBN: 1-60132-498-7, CSREA Press ©
‘Therefore, “Wis the sk of the moosphere o cope sith
the demands made by sity onthe teaching stem, by
‘ransmuting them nto conditions acceptable to both pais
city and its teaching system” 110, Coneguenty. the
‘ental function ofthe mosphere i the meet with the
Soviet, aking into account deren condon, coms,
ruine in compromises.
"We fous in thi operon analyzing the dic tans
sion of CS know ede related the introduction of ment
programming based on IiRobe, a it happens in the conten
fof a research and taining project - PERSEVERONS'. We
do emphasize dat er actions, Knowledge and research
fate happening in PERSEVERONS, which are out ofthe
‘Scope of thin paper. In his context, we have denied as
gent of the educadora system: the Curcula Superior
‘Council (Conse! mpéricar des programmes) the body
‘which deines the national French CS cuca, CS und
Leaming Scenes researchers, CS pedagogical counselors
(le Emcignantsréerns pour les wage du numérique,
‘primary and secondary schoolteachers. In the not stos
"Se aulgze how these agents ae iterating in press
(of negotiation and co-comstrcion - à process of defining
together, through interactions more or less diet - oa CS
3. The co-construction process
Inthe coment of our case study based on IniobaL it
sms sa ir assumption that he knowledgeto bea
Soul revolve around robots and their programming. We
investigate in this section the transposon of such know
‘le rom the def of cha knowledge of what e
‘alle event-driven programming (one of te mai paradigme
‘ed for programming robos). 10 is transformation In
Knowledgetorbetaght, as fund in the French national
curicla and inthe Inohos pedagogical ki (and one of
ls declinación, the IniRobar for Schoo) and fuer ino
‘aught and lear Knowledge, observed in regalar French
School, while emphasing the actions of dienen acts
involved in each phase
3.1 Defining the scholarly knowledge
Providing a complete historical and epistemological tay
on he CS concepts ached 1 eentaiven programming i
‘ofthe spe ofthis paper However. we do indicate tha
the concept usually considered a im relation withthe 0:
‘called even driven paradigm have oon defined in sever
places, in diferen mann, with dient names, and
{hough there are commonalities among these definons,
there ar also numerous and important dienen.
Tor example, 11] defines a computational ven as “any
‘hing hat happens inthe course ol «comput bah
occurrences in th program el. a well as cocurencos
‘ouside the computton proper”. A Similar and more pre
ape aie
definition is that of 112. fo which evens ar “he trams
tions Between ses that may appear in a system or it
cironment, Plea noce tha thes defnlions consider
bth the external and the internal nature of evens
‘Other authors. Ike for example Turing-avanl winner L.
Lamport [13]. oler a more complete picture, speaking of
several concep: events (which are nor Formally define
processes, messes (defined asthe means of communication
mong spl iin processes - seu ystems and
‘whose sending or eceivng ae considered an een, pal
nderin (ofthe sending and reception of messages) logical
and physical clocks (or synchronization) ec
1A] speaks ahou waiting for an event in which ease the
program cannot complete un operation immediatly and us.
register callback = function na wil De invoked when
the even occurs. This wating is typical done in kop
that pols or evens and encts the appropri callback
hen the event occur. To dileentit btucen event
‘mechanisms of Being [..] by a combi” 112. which
provide an event every time condon ste, ae nde
A concep! similar tothe cick isthe even handler = à
method “able to respond to one Kind of external action (or
ven [IS]. An event is defied as an tema cin
‘Other researchers make a différence een what is
called dreaded or procedure orienta) and event-driven (or
message oriente) programming modeluhytem [14 ing.
er lo show tete daly eg. (16, oe the precedence ol
‘one over the lle (a cas in some contexts) eg. 14117
Defining the concep reed o the so called “eve
sven programming paradigm” has three been à ong
roces, in wich several CS researchers (the only type of
tors and more precisely ly in TDTK terminology in
this pao) have Bul on or against the work of previous
researchers. The resubingscholaly knowledge may have
ride that enable construcion of el work applications
(use of Led) ut i sll a rater lt snd
specialized body to understand, sr and cast.
32 Defining the knowledge-to-be-taught : the
curricula
In France, a disncionsusaly made between 2 ype of
Knowledge: tagt: te national eurcua resold from
the extemal imposition proces of schol knowledge
and which serves asa reference document for the second
‘ype of knowledgeso-be-taugh, which comprise textbooks,
Vencer rain documents ad ether smile documents. The
arcs self he esl of negation process between
Several organizaons and coun. The Consul Superior
Count the body which deines the national French
curricula for elementary and middle scho. However it
‘oes not work in lation, ad an analysis of 6 CS 2016
arcu] shows a number of infueces rom repo of
the Academy of Sciences FA, to athe organization such as
ISBN: 1-60132-498-7, CSREA Press ©
Pr and A
Regarding Anowiedgs related 10 bots and eveatdien
programming, the French national cumcula or mile
School fr example [1 pp: 26, 30), includes requirements
such as “ue à program in which actions ae Mere
by extrior evens. or "gering of an aston by an
Sen. I is important o ote that tbe CS concepts are
mentioned in the curl in 2 dic pas: Mamans
{nd Technology. While he requirements evoked above ae
common to tah parts, thee are CS concepts specific
only one of thm. AS such, the Mathematics par abo
includes “pupils ae ioduced to event programming di.
Programm événements". “programming actions in
Parallel, “control etes relied o evens, while the
Technology pat includes: “Sensor, actuate, trace”. One
cam see ral the Mathematics par is mor focused on the
programming Sid, while te Tecnology par ao includes
mor pronounced engineering and mechanical element
‘One can demi, in e cuil, CS concepts tat have
been selected from the scholary Knowledge, such as cient
(hich in he curicula seem lo concer many exter
¿sens - so messages”, action (probably similar 0 the
concepts of ella hander riggering and conto struc
fares lated 10 events (eabaty relate to waling and oop
poling) actions parallel elated processes? or another
rame fo evens). Why and how have been these once
Selected? A posible answer may come rom what seems
15 be a major source of inspiration forthe CS par of the
‘ucla a report af he Academy of Science [4 pp. 23,25
‘hich indicates, in elton to exentdriven programming
ocept suchas: "notion of pal igri” "sensors and
totes, algrthns[.] control the system by acting on.
tuts depending on the ensed vales, the reine
‘command in a cod lop"
Howeer. one can notice that, while the Academy report
presents ogeer more mechanical (sesos, actus) und
moe programmatic Igor, op) once, e cucu
sogrepts them into a Mathomatic and Technolgy par
Ho coud this e eyplined? As mentioned in he inte
Bon on the itor of teaching CS in France tating from
the 1990s, teachers were tained mainly to Digital Lteracy,
ut oto CS (programming), Therefore in the 2010, when
‘he (plea) decision to introduce CS teaching vas taken,
‘he Curcua Superior Counc ound ic contoned with
the reali of having no teachers propery tried, oem
the retained solution was 1 spare the CS concepts ito 2
subjects and asin hir teaching 10 teacher; which were he
‘mot key to have conection to and hopealy teres i)
these concep. The French maton cumkulai refor
od example of how diferent actors, rm pola decision
mers, the Academy of Science and the Cuericula Superior
Int Cont. Frontier in Education: CS and CE | FECS'9 |
Coani negotiated indrcly). according to their purposes
tnd wih pel-nel! conti.
‘One can alo notice that the comica identifies CS
conceis to be taught but does not enter ino details. For
example, rigering is mention. but not filtering by a
condon: the concept of erent appears, bu no discussion
ofthe time implican, on questions related othe partial
‘ndering of sending andlor reception of even. Av we
‘all se, this may have had implications on the father
transposition of he knolalge- beugt
33 Defining the knowledge-to-be-taught: the
case of pedagogical kits
Aa numberof decisions regarding choices among shot:
aly Knowledge, such a focusing on cen conceps of
sent rien programming. suelas a separation at idle
school, nto Mathematics and Technology: were tan, a
à resul of an extemal wansposton process between ty
‘ofthe educational sytem such asthe Academy of Science
‘nd police decision makes, onthe one hand. and agents
such asthe Curricula Superior Coun on te other hand
the identi concep remain described ater vaguely and
{numberof choices ail need to be made, One such
more detailed speciation i povided bythe IiRobot [6]
pedagogia ki. With aversion made available in 201415)
o somehon in parle with he development of the ecu
‘lf, mainly by cion. which seem to be peimanly CS
researcher or schoolteacher, seh interes in Education
Science research, laiRobot has several declared objectives,
among which "the acquisition and practical use ala number
fof fundamental concepts, uch a for example: “sensor
Factor, instruction, "lor" and how to us bas
concepts of ven-bsed programming" by elemenary and
‘idle school ppi 6). scems therefore safe 1 ase
the authors of Inibot followed the principi of the low
floor (easy get stats) [IS], and wed 10 avoid as much
28 possible known dicas
Programming in explicily evemdeven model i very
dica” 119. Several cause lave been denied For this
among which we find particulary relevant for our discus
Son the fact that he interactive logic of à program i
Fragmented actos multiple even handlers [14119]. While
Sequential programming is stud a single How of
orl, with contol stuctres such as Dancing (Le. IF)
and oops, evenrisen programming requires à seis of
small calbaisfsrdlers. The contol Mow among these
handle is not obvious, because of the mers of the
onl TU): à program merely registers wilh he execution
Emironment its intrest to be resumed on coin events 4
is be execution environment which dispatches the events
16 he even handlers iti not the program which calls the
Rand Ths the conto flow among handles is expreso
only imp, rough manipulation of hard st (ES)
ISBN: 1-60132-498.7, CSREA Press ©
Regarding Anowiedgs related 10 bots and eveatdien
programming, the French national cumcula or mile
School fr example [1 pp: 26, 30), includes requirements
such as “ue à program in which actions ae Mere
by extrior evens. or "gering of an aston by an
Sen. I is important o ote that tbe CS concepts are
mentioned in the curl in 2 dic pas: Mamans
{nd Technology. While he requirements evoked above ae
common to tah parts, thee are CS concepts specific
only one of thm. AS such, the Mathematics par abo
includes “pupils ae ioduced to event programming di.
Programm événements". “programming actions in
Parallel, “control etes relied o evens, while the
Technology pat includes: “Sensor, actuate, trace”. One
cam see ral the Mathematics par is mor focused on the
programming Sid, while te Tecnology par ao includes
mor pronounced engineering and mechanical element
‘One can demi, in e cuil, CS concepts tat have
been selected from the scholary Knowledge, such as cient
(hich in he curicula seem lo concer many exter
¿sens - so messages”, action (probably similar 0 the
concepts of ella hander riggering and conto struc
fares lated 10 events (eabaty relate to waling and oop
poling) actions parallel elated processes? or another
rame fo evens). Why and how have been these once
Selected? A posible answer may come rom what seems
15 be a major source of inspiration forthe CS par of the
‘ucla a report af he Academy of Science [4 pp. 23,25
‘hich indicates, in elton to exentdriven programming
ocept suchas: "notion of pal igri” "sensors and
totes, algrthns[.] control the system by acting on.
tuts depending on the ensed vales, the reine
‘command in a cod lop"
Howeer. one can notice that, while the Academy report
presents ogeer more mechanical (sesos, actus) und
moe programmatic Igor, op) once, e cucu
sogrepts them into a Mathomatic and Technolgy par
Ho coud this e eyplined? As mentioned in he inte
Bon on the itor of teaching CS in France tating from
the 1990s, teachers were tained mainly to Digital Lteracy,
ut oto CS (programming), Therefore in the 2010, when
‘he (plea) decision to introduce CS teaching vas taken,
‘he Curcua Superior Counc ound ic contoned with
the reali of having no teachers propery tried, oem
the retained solution was 1 spare the CS concepts ito 2
subjects and asin hir teaching 10 teacher; which were he
‘mot key to have conection to and hopealy teres i)
these concep. The French maton cumkulai refor
od example of how diferent actors, rm pola decision
mers, the Academy of Science and the Cuericula Superior
Int Cont. Frontier in Education: CS and CE | FECS'9 |
Coani negotiated indrcly). according to their purposes
tnd wih pel-nel! conti.
‘One can alo notice that the comica identifies CS
conceis to be taught but does not enter ino details. For
example, rigering is mention. but not filtering by a
condon: the concept of erent appears, bu no discussion
ofthe time implican, on questions related othe partial
‘ndering of sending andlor reception of even. Av we
‘all se, this may have had implications on the father
transposition of he knolalge- beugt
33 Defining the knowledge-to-be-taught: the
case of pedagogical kits
Aa numberof decisions regarding choices among shot:
aly Knowledge, such a focusing on cen conceps of
sent rien programming. suelas a separation at idle
school, nto Mathematics and Technology: were tan, a
à resul of an extemal wansposton process between ty
‘ofthe educational sytem such asthe Academy of Science
‘nd police decision makes, onthe one hand. and agents
such asthe Curricula Superior Coun on te other hand
the identi concep remain described ater vaguely and
{numberof choices ail need to be made, One such
more detailed speciation i povided bythe IiRobot [6]
pedagogia ki. With aversion made available in 201415)
o somehon in parle with he development of the ecu
‘lf, mainly by cion. which seem to be peimanly CS
researcher or schoolteacher, seh interes in Education
Science research, laiRobot has several declared objectives,
among which "the acquisition and practical use ala number
fof fundamental concepts, uch a for example: “sensor
Factor, instruction, "lor" and how to us bas
concepts of ven-bsed programming" by elemenary and
‘idle school ppi 6). scems therefore safe 1 ase
the authors of Inibot followed the principi of the low
floor (easy get stats) [IS], and wed 10 avoid as much
28 possible known dicas
Programming in explicily evemdeven model i very
dica” 119. Several cause lave been denied For this
among which we find particulary relevant for our discus
Son the fact that he interactive logic of à program i
Fragmented actos multiple even handlers [14119]. While
Sequential programming is stud a single How of
orl, with contol stuctres such as Dancing (Le. IF)
and oops, evenrisen programming requires à seis of
small calbaisfsrdlers. The contol Mow among these
handle is not obvious, because of the mers of the
onl TU): à program merely registers wilh he execution
Emironment its intrest to be resumed on coin events 4
is be execution environment which dispatches the events
16 he even handlers iti not the program which calls the
Rand Ths the conto flow among handles is expreso
only imp, rough manipulation of hard st (ES)
ISBN: 1-60132-498.7, CSREA Press ©
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
I is maybe to avoid sch dicas ret to under-
standing the Fragmented and imened conta ow tat the
thors of Iitoot proposed the use of the weed “IF to
inte wht they all an “event a we hve seen in Fig
1. Th may help “Towering he Hoe 18) the entry poi or
pups, when frst encountering cuenten programming.
by approaching the fragmented event-driven contol ow lo
‘sential on. Thin seems the more Hk) as, in special
(simple) eases, the contol Bow of an exendeivn progam
may actually be Sequential. Therefore, as long as he si
ationdexercses only require sequential code, popls having
{Sequential representan of the event-driven program
‘oes not show 1 e problematic. However ar he. i his
ly taught even-iven programming? Moreover the
Similar of using logical contions: fom he lin of
an event by conditions when rigeringhvatngoop poling
and, respectively. of the ranch condi, Increase the
Similar between the 2 concep
‘Nonetheless, the semantics of ilering of sens by com
dons es depo y the keyword WHEN) is diferent
from that of a ranch (IF). À ler has to be unique in a
program, while Branching conditions may appear multiple
Times. This becomes visbl in some cate, uch a dul
presented the situation tod by Iniobot im Mission
10, analyze in more dei in Fig. 3
‘The 2014 version of nor has evolved, engendering
several branches and multiple version. We focus hee on a
2016 version. Pita for Scho! (20, the basis chos for
actes in PERSEVERONS, Fist change w mac à he
dimension ofthe document: rom 24 pages for nit o
D pages for Inbot fr School, The authors of Tibor.
for Schol are CS pedagogical colors, whose declared
objectives comprise, among otbes: "woking numerous
‘competencies med 10 mastering the language (orl and
ling), mastering mathematical languages and mastering
scie languages" (20, p.21. While there Sl are in
portant objectives related mainly 0 teaching CS concep
IniRobot for School uses the actes with Thymio "0
practice languages, to practice Scie and tecnologica
procedures” and “o organize the personal work” 120. 03
AS well ln relation wih other jenes of the French
rational cnica (defined or all school sujet) [1]. WO
IniRobor comi of 6 sessions containing a toa of 14
mission, with à Wal ximated competion time of aout
6 hours (possibly longer, depending on audience), IniRobot
for School consists al 12 sessions, during which contents
from InsRobot missions I, 2,34 5, 6,78, 10 re partial
reused, rendered, developed and enriched, fora Wil ofa
‘timated completion time of about 12 hous.
“The ators of IniRobo for Schoo! have thus selected
coming 1 thei objectives rom IniRoboL contents lated
to CS concepts found in he curicub, excluded others (e.
mission 11, 12,13 fom iRobot) and aed other know
ge (e. mision 1 on drawing Thymi) not neesan re
aed to CS, in order to augment the nterdiscpiar content
Unir Les alo ote Wain iRobot or School, white
concepts such as event ad action ae mentioned sever
Times and exemplified no mention is made conditions or
iternghwatng which is, as we have see, in accordance
the ck of menton in the cuca
34 Defining the taught knowledge
At his phase inthe transposon, itis the teachers! ten
interne in the proces. Based onthe curicl. textbooks
pedagogical is, cer resources and the ting they (a
Supposed to) have received, the French educational system
pei teachers to define stations 10 he taught in the
hssroom, that introduce and argue the need oF CS concep
“These ar high expectations ficult meet, especial by
teachers with mo al aig in CS
“To support the teaches in hs rather daunting task, tbe
decision makers. most notably the Prime Minister and he
Missy of Eatin, have intervened tho
Spaces for taining, research and digital organization all
for projets It has selected 22 projects, fra tal of 195
Millon Euros. The sueca projects demonstrated that
they Feat Schools. county local autores, companies
research iterators, and other actos, sound an innovative
Projet wih objectives rearing diia abject = whether 10
Use them as pedagogical resource o in ein to now
Sisto be acquired. or as «research obj =, ing place
fon disen eines which enable a precise monitoring and
‘alton (especial of pupils avoled in experiment).
[As parto oe such projet, PERSEVERONS, we have the
‘opportunity o observing and analyzing interactions between
be numero actors involved. These interactions have driven
the transposition of CS Knowledge bea, as defied
bythe curul. textbooks and pedagogical Kits. We have
observa several teachers and lass, Aseping records
in te form af noes, videos and photos, following an
hservationbaed, ese study documen anderen
Content analysis, qual research meth” 21,
Tu sould come as no sureise that even though the
teachers used the same main pedagorial Kit Robot for
‘School, thee were difereces in the way the clas ie was
amande the emphasis on some explanations or stations,
the general and CS-speciie cher experience et, However,
some conditions were sey common, uch a pupils working
in groups of 2 ce 3, wth | computer and I Thymi, in al
‘lasrooms of similar sis, between around 10 amd 1, for
shout I hau, in 12 sessions per weck for 10 weeks
“This allowed observing some recuring pbenamens ans
nn qe nm
ISBN: 1-60132-498-7, CSREA Press ©
7
I is maybe to avoid sch dicas ret to under-
standing the Fragmented and imened conta ow tat the
thors of Iitoot proposed the use of the weed “IF to
inte wht they all an “event a we hve seen in Fig
1. Th may help “Towering he Hoe 18) the entry poi or
pups, when frst encountering cuenten programming.
by approaching the fragmented event-driven contol ow lo
‘sential on. Thin seems the more Hk) as, in special
(simple) eases, the contol Bow of an exendeivn progam
may actually be Sequential. Therefore, as long as he si
ationdexercses only require sequential code, popls having
{Sequential representan of the event-driven program
‘oes not show 1 e problematic. However ar he. i his
ly taught even-iven programming? Moreover the
Similar of using logical contions: fom he lin of
an event by conditions when rigeringhvatngoop poling
and, respectively. of the ranch condi, Increase the
Similar between the 2 concep
‘Nonetheless, the semantics of ilering of sens by com
dons es depo y the keyword WHEN) is diferent
from that of a ranch (IF). À ler has to be unique in a
program, while Branching conditions may appear multiple
Times. This becomes visbl in some cate, uch a dul
presented the situation tod by Iniobot im Mission
10, analyze in more dei in Fig. 3
‘The 2014 version of nor has evolved, engendering
several branches and multiple version. We focus hee on a
2016 version. Pita for Scho! (20, the basis chos for
actes in PERSEVERONS, Fist change w mac à he
dimension ofthe document: rom 24 pages for nit o
D pages for Inbot fr School, The authors of Tibor.
for Schol are CS pedagogical colors, whose declared
objectives comprise, among otbes: "woking numerous
‘competencies med 10 mastering the language (orl and
ling), mastering mathematical languages and mastering
scie languages" (20, p.21. While there Sl are in
portant objectives related mainly 0 teaching CS concep
IniRobot for School uses the actes with Thymio "0
practice languages, to practice Scie and tecnologica
procedures” and “o organize the personal work” 120. 03
AS well ln relation wih other jenes of the French
rational cnica (defined or all school sujet) [1]. WO
IniRobor comi of 6 sessions containing a toa of 14
mission, with à Wal ximated competion time of aout
6 hours (possibly longer, depending on audience), IniRobot
for School consists al 12 sessions, during which contents
from InsRobot missions I, 2,34 5, 6,78, 10 re partial
reused, rendered, developed and enriched, fora Wil ofa
‘timated completion time of about 12 hous.
“The ators of IniRobo for Schoo! have thus selected
coming 1 thei objectives rom IniRoboL contents lated
to CS concepts found in he curicub, excluded others (e.
mission 11, 12,13 fom iRobot) and aed other know
ge (e. mision 1 on drawing Thymi) not neesan re
aed to CS, in order to augment the nterdiscpiar content
Unir Les alo ote Wain iRobot or School, white
concepts such as event ad action ae mentioned sever
Times and exemplified no mention is made conditions or
iternghwatng which is, as we have see, in accordance
the ck of menton in the cuca
34 Defining the taught knowledge
At his phase inthe transposon, itis the teachers! ten
interne in the proces. Based onthe curicl. textbooks
pedagogical is, cer resources and the ting they (a
Supposed to) have received, the French educational system
pei teachers to define stations 10 he taught in the
hssroom, that introduce and argue the need oF CS concep
“These ar high expectations ficult meet, especial by
teachers with mo al aig in CS
“To support the teaches in hs rather daunting task, tbe
decision makers. most notably the Prime Minister and he
Missy of Eatin, have intervened tho
Spaces for taining, research and digital organization all
for projets It has selected 22 projects, fra tal of 195
Millon Euros. The sueca projects demonstrated that
they Feat Schools. county local autores, companies
research iterators, and other actos, sound an innovative
Projet wih objectives rearing diia abject = whether 10
Use them as pedagogical resource o in ein to now
Sisto be acquired. or as «research obj =, ing place
fon disen eines which enable a precise monitoring and
‘alton (especial of pupils avoled in experiment).
[As parto oe such projet, PERSEVERONS, we have the
‘opportunity o observing and analyzing interactions between
be numero actors involved. These interactions have driven
the transposition of CS Knowledge bea, as defied
bythe curul. textbooks and pedagogical Kits. We have
observa several teachers and lass, Aseping records
in te form af noes, videos and photos, following an
hservationbaed, ese study documen anderen
Content analysis, qual research meth” 21,
Tu sould come as no sureise that even though the
teachers used the same main pedagorial Kit Robot for
‘School, thee were difereces in the way the clas ie was
amande the emphasis on some explanations or stations,
the general and CS-speciie cher experience et, However,
some conditions were sey common, uch a pupils working
in groups of 2 ce 3, wth | computer and I Thymi, in al
‘lasrooms of similar sis, between around 10 amd 1, for
shout I hau, in 12 sessions per weck for 10 weeks
“This allowed observing some recuring pbenamens ans
nn qe nm
ISBN: 1-60132-498-7, CSREA Press ©
7
8
TEE TEE
CO EEE
Fig. Expected solution programming Thymio's explore
Behavior. rom (5
the diferent clases, among which the one related 10 the
tse of the IF keyword, described in more deal here
35 Defining the learned knowledge
‘One phenomenon, recurrent pups “mistake” observe
in seve contents and situations, can be exemplified by
Mision 10 (om abs, optional part of Sein 10 of
iodo fr Schoo. ask pus to program Thymioso dt
la mones about fel, aviding al sales (orespondin
do its explorer Behavior, cf. Fig. De opina. sks to
add insuetjns so ha Thymio change i colo o redil
la detects an otc, ad lo green if not The expected
solution (cf. Fi. 3 15, p. 23) consists of 4 intmations
(grey Bock), ech comenponding to an event (atthe lft of
the sign), and 2 cios (at he ght") In Indo
terminology thei respective semantics woul Be (5. p- 14
A Toni does not detect anything with ls rt senon,
auhance and change color o green; if Thymio dees
Something at its et, tum eight and change olor to red
if Thymio des something in font of i back avay while
turning ite and change color w red: if Tymio des
Something at fight, um let and change cole 1 re
‘One “mistake” pupils make (Fig. sa instead of
ding a Second action to the right ofthe "sign, for the
same “even they al second astuctin, wit he ame
"even. Ths is signaled by the comple as an emo (in ed
the top of Fig. 3) of the ype: the evens ar the same:
fof course, fr the program o de deterministic, the cent
acer soe unique. While there may be sever
Splanaons for hs mistake, such as understanding at
‘ach even has oly one omesponding actonstrcion
(wile actual, a he sgt of the” sgn thre lock
of istrcions. which may contain an ation ofeach (PO.
However one posible explanation, on which we focus
here is thatthe pupils consracted representation of the
event concept which à chose lo a seque ne, and
which Metro allows them lo verify te same condition
Ui al of Tymi's foma sen do aa dtet anything,
in the example of Fig. 3) Several times. It woul seem
that constuctng representan ofthe event concep a
includes me aspects (with asemantes of whe (each and
ery time) al oF Thymio’s frontal sensors do not detec
antigen example), would elp in understanding
Int Cont. Frontier in Education: CS and CE | FECS'9 |
the uniqueness of the type of event and of its attached
actions While aproucing the cvendeven contr! Now 10
2 sequential one may “Tower the our à more appropriate
representation needs o replace it as soon as possible. if
“teal” sentis programming is tobe tight
While this isa fy smigiforsa example, is ana
ysis helps understanding difficult encore a each
phase ofthe didactic uanspositon co-cnstactin proses
from (1) the esterim of the scholarly knowlege on
escntdeien programming (in which tine coment
fue made using concep such as pura ordering, and
Conditions are delia as part of à filering of evens, in
à walingiriggeringlonp poling mechanism). den by
sometimes compeúng, sometimes continuing CS researches
using tough (2) the selection of concepts o bag
election influence by political decision makers, academic
Gestion (iy i the Sense of TK), national cuca
denon bodies (which in our case sy sem ove out
these time and conditions considerations, (3) the ret
tion and reorganization into books, pedagogical kis, or
Similar resources, y researchers. ches and polagogcal
Counselors mainly concred with cation [sue wa
casing thei understanding by pris (ad thus in our cass,
Seemingly approaching the exe drive flow of cono o
A Sequential ane by using keywords like “IP instead of
"WHEN. (4) the development of classroom Lessons by
teachers and ally (9) the continuous colin of pui
representation of the tag concepts, who by “mistakes”
experiment and const hin representation in ur ee.
E assuming tht conlitonvevent are not unique
4. Conclusion
White most curent esearch related to Computational
Thinking (CT), especialy in a K-12 cota, Ds focused
mainly on designing activites for teaching CT concept
Such pedagogical documents need 1 he analyzed and ex
permet in classrooms so that they can be valide and
peo I is paper we adopte qual appro, as
à rt step o Ing phenomena tht appear cul}
in clasevoms Ti lowed 10 ¡deny date obs
{othe leaning of pup, Futerwcial and epbiemelegkl-
driven analysts revealed css of such dic obstacles in
TE
Fa
Fig 4: Typical pupils’ mistake
9
ISBN: 1-60132-498-7, CSREA Press ©
TEE TEE
CO EEE
Fig. Expected solution programming Thymio's explore
Behavior. rom (5
the diferent clases, among which the one related 10 the
tse of the IF keyword, described in more deal here
35 Defining the learned knowledge
‘One phenomenon, recurrent pups “mistake” observe
in seve contents and situations, can be exemplified by
Mision 10 (om abs, optional part of Sein 10 of
iodo fr Schoo. ask pus to program Thymioso dt
la mones about fel, aviding al sales (orespondin
do its explorer Behavior, cf. Fig. De opina. sks to
add insuetjns so ha Thymio change i colo o redil
la detects an otc, ad lo green if not The expected
solution (cf. Fi. 3 15, p. 23) consists of 4 intmations
(grey Bock), ech comenponding to an event (atthe lft of
the sign), and 2 cios (at he ght") In Indo
terminology thei respective semantics woul Be (5. p- 14
A Toni does not detect anything with ls rt senon,
auhance and change color o green; if Thymio dees
Something at its et, tum eight and change olor to red
if Thymio des something in font of i back avay while
turning ite and change color w red: if Tymio des
Something at fight, um let and change cole 1 re
‘One “mistake” pupils make (Fig. sa instead of
ding a Second action to the right ofthe "sign, for the
same “even they al second astuctin, wit he ame
"even. Ths is signaled by the comple as an emo (in ed
the top of Fig. 3) of the ype: the evens ar the same:
fof course, fr the program o de deterministic, the cent
acer soe unique. While there may be sever
Splanaons for hs mistake, such as understanding at
‘ach even has oly one omesponding actonstrcion
(wile actual, a he sgt of the” sgn thre lock
of istrcions. which may contain an ation ofeach (PO.
However one posible explanation, on which we focus
here is thatthe pupils consracted representation of the
event concept which à chose lo a seque ne, and
which Metro allows them lo verify te same condition
Ui al of Tymi's foma sen do aa dtet anything,
in the example of Fig. 3) Several times. It woul seem
that constuctng representan ofthe event concep a
includes me aspects (with asemantes of whe (each and
ery time) al oF Thymio’s frontal sensors do not detec
antigen example), would elp in understanding
Int Cont. Frontier in Education: CS and CE | FECS'9 |
the uniqueness of the type of event and of its attached
actions While aproucing the cvendeven contr! Now 10
2 sequential one may “Tower the our à more appropriate
representation needs o replace it as soon as possible. if
“teal” sentis programming is tobe tight
While this isa fy smigiforsa example, is ana
ysis helps understanding difficult encore a each
phase ofthe didactic uanspositon co-cnstactin proses
from (1) the esterim of the scholarly knowlege on
escntdeien programming (in which tine coment
fue made using concep such as pura ordering, and
Conditions are delia as part of à filering of evens, in
à walingiriggeringlonp poling mechanism). den by
sometimes compeúng, sometimes continuing CS researches
using tough (2) the selection of concepts o bag
election influence by political decision makers, academic
Gestion (iy i the Sense of TK), national cuca
denon bodies (which in our case sy sem ove out
these time and conditions considerations, (3) the ret
tion and reorganization into books, pedagogical kis, or
Similar resources, y researchers. ches and polagogcal
Counselors mainly concred with cation [sue wa
casing thei understanding by pris (ad thus in our cass,
Seemingly approaching the exe drive flow of cono o
A Sequential ane by using keywords like “IP instead of
"WHEN. (4) the development of classroom Lessons by
teachers and ally (9) the continuous colin of pui
representation of the tag concepts, who by “mistakes”
experiment and const hin representation in ur ee.
E assuming tht conlitonvevent are not unique
4. Conclusion
White most curent esearch related to Computational
Thinking (CT), especialy in a K-12 cota, Ds focused
mainly on designing activites for teaching CT concept
Such pedagogical documents need 1 he analyzed and ex
permet in classrooms so that they can be valide and
peo I is paper we adopte qual appro, as
à rt step o Ing phenomena tht appear cul}
in clasevoms Ti lowed 10 ¡deny date obs
{othe leaning of pup, Futerwcial and epbiemelegkl-
driven analysts revealed css of such dic obstacles in
TE
Fa
Fig 4: Typical pupils’ mistake
9
ISBN: 1-60132-498-7, CSREA Press ©
Intl Cont. Frontiers in Education: CS and CE| FECS'19 |
the complet ofthe dick tamspositon process im
ing numerous str, wih various contraints ad objectives
‘More specify, we focused on eventiven prog
ring, observing and analyzing during 3 years, how the
ImiRobo for Scho! pedagogia Kit using the Thy root
as wed o tach and arn concepts related 10 the ent:
‘riven paradigm. We hs pinpointed tht concepts of vente
‘riven programming form he main foes of CS knowledge
tale in elementary and mide school (oer fly
gun chocs incide robotic, inligent (cooperative)
{atonomous) agents, ties et) In an epistemological a
prooch. we reviewed schol, eesearhinrodeed dei
tons of Concepts that current ae considered to be elated
to what i called enden programming. showing their
relations and underning their complexy (eg eternal vs
Internal event, messages vs. poceses, We analyzed how
Some ofthese concepts were selected and paral redefined
(eg. event acon) in the French national cuicla and
end how th lack of mention of cer concep (E.
fering on conditions. may conte to further dial
des. We found tha these selections are indeed selected
in the pedagogia Ks that implement the cuil, and
are compounded wih didactic and podagoekal comes
Of “simplifying” the taught concepts (eg. frseming the
Fragmented event control flow as sequel one). This
analysis (im paar he evew ofthe shot Knowledge)
may serve aa Bas in fire designs of veto
programming pedagogical proposal,
In is work, we mainly focus on dic obtacks.
Wii, for example, de icy al understanding the
fragmented control How of event.drhen programming sa
epistemological obstacle, ne dida choice of the I
Keyword (while intended precisely to reduce ths piste
‘ological obsta), wih is unforeseen side eet, int
dicing didactic obstacles (sequential representation of the
‘xcurence of exe), rated bythe very reden (ut
{of ddacis concems) of some event ven concepts, While
‘hey are probably unavoidable in any didactic wansposiion
proces. is important o recognize sich obstacles be aware
Sf them and ry o res them fuer along the ie
“This analysis can therefore be used 10 daw the ate
ton, in paul, to comica and pedagogia! documents
(extooks, kis. et) designer, 1 pay singular tention ©
how they refine scholarly concepts as these “new” rep
resta - the htowiedgeo-be-augh may introduce ts
‘own obstacles Moreover. his analysis may serve researchers
And analysis ofthe noue. eat (be cuca
textbooks, pedagogical his) as caution to deaving concu
‘os oo hat; and isc ers a dsper consideration
ofthe wider context and he comple iterations between
the imolved actos (be hey agent ofthe education system
ory), which may influence decisions seeming at à fs
lance. "weit" or simply "eones". thus enlightens
the fact that the bal” result of the taught knowledge i
the product of a proces of co-consttion in which many
actors imenene a ire sags
References
Wy eine ig
ee
ee
SR Te
I GAL Harn. B. Bro Délnge, M. Gantt, an Tr "Com
ÉD sat Sete
3 M Mig Comptia inking” Commun, ACM. ve 49 m3,
en
EEE ne me u One
En
eg
m M Gac, cn ey fe ise apo.
wn Rept lar ace
et
eis
va "Athol apc ci nl fr Mati
o ae a ca
DER Me
qa SR enter gens
to Seam tea ee
u a a
her
een
105) cman Malen. “Reread: Lange sport oer
colette mem mem
Bere
60e SR id er
tn See eae Ne eae
Being
er
pike hin Ao AI
vn Wa esa ae
Resist De
eave ce a eae
co PR hee i te“ on tin
rss Mensen
Spend St
In RS Eon, mt
BB Henn
m
ISBN: 1-60132-498-7, CSREA Press ©
the complet ofthe dick tamspositon process im
ing numerous str, wih various contraints ad objectives
‘More specify, we focused on eventiven prog
ring, observing and analyzing during 3 years, how the
ImiRobo for Scho! pedagogia Kit using the Thy root
as wed o tach and arn concepts related 10 the ent:
‘riven paradigm. We hs pinpointed tht concepts of vente
‘riven programming form he main foes of CS knowledge
tale in elementary and mide school (oer fly
gun chocs incide robotic, inligent (cooperative)
{atonomous) agents, ties et) In an epistemological a
prooch. we reviewed schol, eesearhinrodeed dei
tons of Concepts that current ae considered to be elated
to what i called enden programming. showing their
relations and underning their complexy (eg eternal vs
Internal event, messages vs. poceses, We analyzed how
Some ofthese concepts were selected and paral redefined
(eg. event acon) in the French national cuicla and
end how th lack of mention of cer concep (E.
fering on conditions. may conte to further dial
des. We found tha these selections are indeed selected
in the pedagogia Ks that implement the cuil, and
are compounded wih didactic and podagoekal comes
Of “simplifying” the taught concepts (eg. frseming the
Fragmented event control flow as sequel one). This
analysis (im paar he evew ofthe shot Knowledge)
may serve aa Bas in fire designs of veto
programming pedagogical proposal,
In is work, we mainly focus on dic obtacks.
Wii, for example, de icy al understanding the
fragmented control How of event.drhen programming sa
epistemological obstacle, ne dida choice of the I
Keyword (while intended precisely to reduce ths piste
‘ological obsta), wih is unforeseen side eet, int
dicing didactic obstacles (sequential representation of the
‘xcurence of exe), rated bythe very reden (ut
{of ddacis concems) of some event ven concepts, While
‘hey are probably unavoidable in any didactic wansposiion
proces. is important o recognize sich obstacles be aware
Sf them and ry o res them fuer along the ie
“This analysis can therefore be used 10 daw the ate
ton, in paul, to comica and pedagogia! documents
(extooks, kis. et) designer, 1 pay singular tention ©
how they refine scholarly concepts as these “new” rep
resta - the htowiedgeo-be-augh may introduce ts
‘own obstacles Moreover. his analysis may serve researchers
And analysis ofthe noue. eat (be cuca
textbooks, pedagogical his) as caution to deaving concu
‘os oo hat; and isc ers a dsper consideration
ofthe wider context and he comple iterations between
the imolved actos (be hey agent ofthe education system
ory), which may influence decisions seeming at à fs
lance. "weit" or simply "eones". thus enlightens
the fact that the bal” result of the taught knowledge i
the product of a proces of co-consttion in which many
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ISBN: 1-60132-498-7, CSREA Press ©
Int Cont. Frontier in Education: CS and CE | FECS'9 |
An Assessment Study on the Teaching of Critical Thinking and
Mathematical Proofs in a Discrete Structures Course
Hang Dinh
Department of Computer and Information Sciences
Indiana University South Bend
hudinn@iashedu
Abstract Critical shining and mathematical profs are
o Tearing outcomes of Jocs in our Discrete Sucre
forse. Im thi paper. we stay how these wo learning
‘outcome fet euch ther Our study i based on asses
data rm wo eins of ur Disree Structures couse
th mathematical pros being taught before erica ink.
nein he frst edo and taught afer ciel hiking in he
Second en Resalta four data show tht student in the
irs edition performed significantly heuer in understanding
‘proof and beer in critical thinking than students in the
Second elton di. However the difereee bacon the
men scores on understanding profs of de two ens
ds mot statically significant. These resis suggest that
Ieechipfesming mathenatcol progß may hep stakes
‘derstand cial thinking Det, while eachingeaming.
ical thinking may no help students understand proofs
veer
Keyword: crcl Mining. mata prof, each
ing metho, sessment dre sites
1. Introduction
Critical hiking is one ol he essential caming outcomes
for stants in the 215 century, according lo LEAP [1]
‘The imporance of critical thinking of course ako apps
Computer Science sue. In patil, the ACM
IEEE Compter Science Comiculum Guidelines 2013 [21
recognized eral hiking one of the skills ha tens
ed o develop during ther undergraduate cater Dire
instues may have diferent approaches o include ft
<al linkin ino dei computer scence curculums. For
example. one [3] may design a cecal hiking fussed
ours that stored for engineering or computer scene
students, wile otters (4), [S] may embed cial thinking
«exercises in various Computer Science couse, At our ibe
siste, ciel thinking is required component in
the General Education curriculo As such, our Computer
Science majors would usally take cal king com
om the Philosophy department. Because of the need to
redoce Stent” il required crei hour. we proposed to
incade a Cial Thinking Module (CTN) in our Discrete
Sirucures couse, making this couse sais the erica
hiking regurement of our campus-wide General E
curriculum, Details shout adding the CTM to our Discrete
Simtures course have been published in our previous work
16), Since Fall 2014, sur Computer Science majos no
longer need to take aerial ishing coune from anther
department
"The Discrete Structure coun x a core comme in vor
Computer Science cuiclum. cer al ihe Coie
{opis listed in he fist tre parts ofthe Discrete Sue
(DS) y of Knowledge ta i specie in the ACM
Computer Science Cumiulum Guides 2013 [2 7-78
“Those thee pats are
+ Dats, Relations, and Functions
À DSase Logie
1 DSProof Techniques,
OF these tree par, the DSVPoo! Techniques pu is
sally the mos challenging to tach 10 Computer Sch
ence students. In our experience. stars in our Discrete
Simtres coses ofen struggle the most with understand
ing and onstucting material prof. We believe that
many eter instructors of Discrete Suetures or Discrete
Mathematics also share similar experience since prof i
à motions diet concep for even math majors [7
[Sh For example, Gres and Schneide 19] from Cornell
Poited out tht “Generally speaking, mathematicians and
omputer sient are ot Std with he Level at which
College sents understand math. Students have diiclgy
omstrcting prof, vir reasoning abilities are inadoguste,
and they dont know what consti rigor”
Since the Critical Thinking Module is aed to oor
Discrete Structures couse, we observe some connections
between cial thinking and mathematical prof. In pai
‘le, bo ria thinking and understanding mathematica
ofr require sls for deductive reasoning. eoontting
extended argument. recognizing unstated assumptions. and
“isinguishing non argumentative language fn argumenta.
tive language. These connections natural Ted us 10 won.
de whether teaching erica thinking would help improve
Students’ understanding of profs. or viceversa. Vial
rotated hy this question, we conducted our say in two
onsceutve editions, offered in Fall 2016 and Fall 2017,
fof ou Discrete Sirtres course. Inthe nt iin, we
mere mathematical pe before covering the Creal
ISBN: 1-60132-498-7, CSREA Press ©
An Assessment Study on the Teaching of Critical Thinking and
Mathematical Proofs in a Discrete Structures Course
Hang Dinh
Department of Computer and Information Sciences
Indiana University South Bend
hudinn@iashedu
Abstract Critical shining and mathematical profs are
o Tearing outcomes of Jocs in our Discrete Sucre
forse. Im thi paper. we stay how these wo learning
‘outcome fet euch ther Our study i based on asses
data rm wo eins of ur Disree Structures couse
th mathematical pros being taught before erica ink.
nein he frst edo and taught afer ciel hiking in he
Second en Resalta four data show tht student in the
irs edition performed significantly heuer in understanding
‘proof and beer in critical thinking than students in the
Second elton di. However the difereee bacon the
men scores on understanding profs of de two ens
ds mot statically significant. These resis suggest that
Ieechipfesming mathenatcol progß may hep stakes
‘derstand cial thinking Det, while eachingeaming.
ical thinking may no help students understand proofs
veer
Keyword: crcl Mining. mata prof, each
ing metho, sessment dre sites
1. Introduction
Critical hiking is one ol he essential caming outcomes
for stants in the 215 century, according lo LEAP [1]
‘The imporance of critical thinking of course ako apps
Computer Science sue. In patil, the ACM
IEEE Compter Science Comiculum Guidelines 2013 [21
recognized eral hiking one of the skills ha tens
ed o develop during ther undergraduate cater Dire
instues may have diferent approaches o include ft
<al linkin ino dei computer scence curculums. For
example. one [3] may design a cecal hiking fussed
ours that stored for engineering or computer scene
students, wile otters (4), [S] may embed cial thinking
«exercises in various Computer Science couse, At our ibe
siste, ciel thinking is required component in
the General Education curriculo As such, our Computer
Science majors would usally take cal king com
om the Philosophy department. Because of the need to
redoce Stent” il required crei hour. we proposed to
incade a Cial Thinking Module (CTN) in our Discrete
Sirucures couse, making this couse sais the erica
hiking regurement of our campus-wide General E
curriculum, Details shout adding the CTM to our Discrete
Simtures course have been published in our previous work
16), Since Fall 2014, sur Computer Science majos no
longer need to take aerial ishing coune from anther
department
"The Discrete Structure coun x a core comme in vor
Computer Science cuiclum. cer al ihe Coie
{opis listed in he fist tre parts ofthe Discrete Sue
(DS) y of Knowledge ta i specie in the ACM
Computer Science Cumiulum Guides 2013 [2 7-78
“Those thee pats are
+ Dats, Relations, and Functions
À DSase Logie
1 DSProof Techniques,
OF these tree par, the DSVPoo! Techniques pu is
sally the mos challenging to tach 10 Computer Sch
ence students. In our experience. stars in our Discrete
Simtres coses ofen struggle the most with understand
ing and onstucting material prof. We believe that
many eter instructors of Discrete Suetures or Discrete
Mathematics also share similar experience since prof i
à motions diet concep for even math majors [7
[Sh For example, Gres and Schneide 19] from Cornell
Poited out tht “Generally speaking, mathematicians and
omputer sient are ot Std with he Level at which
College sents understand math. Students have diiclgy
omstrcting prof, vir reasoning abilities are inadoguste,
and they dont know what consti rigor”
Since the Critical Thinking Module is aed to oor
Discrete Structures couse, we observe some connections
between cial thinking and mathematical prof. In pai
‘le, bo ria thinking and understanding mathematica
ofr require sls for deductive reasoning. eoontting
extended argument. recognizing unstated assumptions. and
“isinguishing non argumentative language fn argumenta.
tive language. These connections natural Ted us 10 won.
de whether teaching erica thinking would help improve
Students’ understanding of profs. or viceversa. Vial
rotated hy this question, we conducted our say in two
onsceutve editions, offered in Fall 2016 and Fall 2017,
fof ou Discrete Sirtres course. Inthe nt iin, we
mere mathematical pe before covering the Creal
ISBN: 1-60132-498-7, CSREA Press ©
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1878
CONTENTS
OF
OF
THE SECOND VOLUME.
CHAPTER XIV.
‘ome Names which require a particular Explanation
SecTION 1. Names of Names
2. Relative Terms
Abstract Relative Terms
3. Numbers
4, Privative Terms
5. Time
6. Motion
7. Identity
ein Rok BSNawe eZ
CHAPTER XV.
seflection
CHAPTER XVI.
he Distinction between the Intellectual and Active Powers of the
Human Mind
CHAPTER XIV.
‘ome Names which require a particular Explanation
SecTION 1. Names of Names
2. Relative Terms
Abstract Relative Terms
3. Numbers
4, Privative Terms
5. Time
6. Motion
7. Identity
ein Rok BSNawe eZ
CHAPTER XV.
seflection
CHAPTER XVI.
he Distinction between the Intellectual and Active Powers of the
Human Mind
CHAPTER XVII.
leasurable and Painful Sensations 18
4
CHAPTER XVIII.
“auses of the Pleasurable and Painful Sensations 18
i
CHAPTER XIX.
deas of the Pleasurable and Painful Sensations, and of the Causes 18
of them 9
CHAPTER XX.
he Pleasurable and Painful Sensations, contemplated as passed, or 19
future
vi
CHAPTER XXL.
he Causes of Pleasurable and Painful Sensations, contemplated as 20
passed, or future 1
Secnion 1. The immediate Causes of Pleasurable and
Painful Sensations, contemplated as passed, or 20
as future A
2. The Remote Causes of Pleasurable and Painful
Sensations contemplated as passed, or future 6
Sus-Secr. 1. Wealth, Power, and Dignity, and their
Contraries, contemplated as Causes 20
of our Pleasures and Pains ni
2. Our Fellow-Creatures contemplated 21
as Causes of our Pleasures and Pains 4
leasurable and Painful Sensations 18
4
CHAPTER XVIII.
“auses of the Pleasurable and Painful Sensations 18
i
CHAPTER XIX.
deas of the Pleasurable and Painful Sensations, and of the Causes 18
of them 9
CHAPTER XX.
he Pleasurable and Painful Sensations, contemplated as passed, or 19
future
vi
CHAPTER XXL.
he Causes of Pleasurable and Painful Sensations, contemplated as 20
passed, or future 1
Secnion 1. The immediate Causes of Pleasurable and
Painful Sensations, contemplated as passed, or 20
as future A
2. The Remote Causes of Pleasurable and Painful
Sensations contemplated as passed, or future 6
Sus-Secr. 1. Wealth, Power, and Dignity, and their
Contraries, contemplated as Causes 20
of our Pleasures and Pains ni
2. Our Fellow-Creatures contemplated 21
as Causes of our Pleasures and Pains 4
1.—Friendship
2.—Kindness
3.—Family
4—Country
5.—Party; Class
6.—Mankind
3. The Objects called Sublime and
Beautiful, and their Contraries,
contemplated as Causes of our
Pleasures and Pains
CHAPTER XXII.
otives
Section 1. Pleasurable or Painful States, contemplated as
the Consequents of our own Acts
2. Causes of our Pleasurable and Painful States,
contemplated as the Consequents of our own
Acts
CHAPTER XXIII.
he Acts of our Fellow-creatures, which are Causes of our Pains and 28
Pleasures, contemplated as Consequents of our own Acts 0
2.—Kindness
3.—Family
4—Country
5.—Party; Class
6.—Mankind
3. The Objects called Sublime and
Beautiful, and their Contraries,
contemplated as Causes of our
Pleasures and Pains
CHAPTER XXII.
otives
Section 1. Pleasurable or Painful States, contemplated as
the Consequents of our own Acts
2. Causes of our Pleasurable and Painful States,
contemplated as the Consequents of our own
Acts
CHAPTER XXIII.
he Acts of our Fellow-creatures, which are Causes of our Pains and 28
Pleasures, contemplated as Consequents of our own Acts 0
he Will
atention
CHAPTER XXIV.
CHAPTER XXV.
atention
CHAPTER XXIV.
CHAPTER XXV.
ANALYSIS
ETc.
ETc.
CHAPTER XIV.
SOME NAMES WHICH REQUIRE A PARTICULAR,
EXPLANATION.
“Quam difficile sit inveteratas, eloquentissimorumque scriptorum authoritate
confirmatas, opiniones, mentibus hominum excutere, non ignoro. Prassertim cum
philosophia vera (id est accurata) orationis non modo fucum, sed etiam omnia fere
omamenta ex professo rejiciat: cumque scientize omnis fundamenta prima non
modo speciosa non sint, sed etiam humila, arida, et pene deformia videantur’—
Hobbes Comput. sive Logica, cap. i 5 1.
We have now seen that, in what we call the mental world,
Consciousness, there are three grand classes of phenomena, the most
familiar of all the facts with which we are acquainted, —sensarions,
IDEAS, and the TRAIN OF IDEAS. We have examined a number of the more
complicated cases of Consciousness; and have found that they all
resolve themselves into the three simple elements, thus enumerated.
We also found it necessary to shew, for what ends, and in what
manner, marks were contrived of sensations and ideas, and by what
combinations they were made to represent, 2 expeditiously, trains of
those states of consciousness. Some marks or names, however, could
not be explained, till some of the more complicated states of
consciousness were unfolded; these also are names so important, and
so peculiar in their mode of signification, that a very complete
understanding of them is required. It is to the consideration of these
remarkable cases of Naming that we now proceed.i
EXPLANATION.
“Quam difficile sit inveteratas, eloquentissimorumque scriptorum authoritate
confirmatas, opiniones, mentibus hominum excutere, non ignoro. Prassertim cum
philosophia vera (id est accurata) orationis non modo fucum, sed etiam omnia fere
omamenta ex professo rejiciat: cumque scientize omnis fundamenta prima non
modo speciosa non sint, sed etiam humila, arida, et pene deformia videantur’—
Hobbes Comput. sive Logica, cap. i 5 1.
We have now seen that, in what we call the mental world,
Consciousness, there are three grand classes of phenomena, the most
familiar of all the facts with which we are acquainted, —sensarions,
IDEAS, and the TRAIN OF IDEAS. We have examined a number of the more
complicated cases of Consciousness; and have found that they all
resolve themselves into the three simple elements, thus enumerated.
We also found it necessary to shew, for what ends, and in what
manner, marks were contrived of sensations and ideas, and by what
combinations they were made to represent, 2 expeditiously, trains of
those states of consciousness. Some marks or names, however, could
not be explained, till some of the more complicated states of
consciousness were unfolded; these also are names so important, and
so peculiar in their mode of signification, that a very complete
understanding of them is required. It is to the consideration of these
remarkable cases of Naming that we now proceed.i
# Under the modest title of an explanation of the meaning of several names, this
chapter presents us with a series of discussions of some of the deepest and most
intricate questions in all metaphysics, Like Plato, the author introduces his analysis
of the most obscure among the complex general conceptions of the human mind, in
the form of an enquiry into the meaning of their names. The title of the chapter
gives a very inadequate notion of the difficulty and importance of the speculations
contained in it, and which make it, perhaps, the profoundest chapter of the book. It
is almost as if a treatise on chemistry were described as an explanation of the
names al, water, potass, sulphuric acid, &c—Ed,
chapter presents us with a series of discussions of some of the deepest and most
intricate questions in all metaphysics, Like Plato, the author introduces his analysis
of the most obscure among the complex general conceptions of the human mind, in
the form of an enquiry into the meaning of their names. The title of the chapter
gives a very inadequate notion of the difficulty and importance of the speculations
contained in it, and which make it, perhaps, the profoundest chapter of the book. It
is almost as if a treatise on chemistry were described as an explanation of the
names al, water, potass, sulphuric acid, &c—Ed,
SECTION I.
NAMES OF NAMES.
It is of great importance to distinguish this class of terms; to
understand well the function which they perform, and to mark the
subdivisions into which they are formed. There is not, however, such
difficulty in the subject as to require great minuteness in the
exposition.
As we have occasion to speak of things; animals, vegetables,
minerals; so we have occasion to speak of the marks, which we are
under the necessity of using, in order to record or to communicate
our thoughts respecting them. We cannot record or communicate our
thoughts respecting names, as man, tree, horse, to walk, to fly, to
eat, to converse, without marks for them. We proceed in the case of
names, as we do in other cases. We form them into classes, some
more, some less, comprehensive, and give a name to each.
We have one name, so general as to include them all; Word. That is
not a name of any thing. It is a name of the marks which we employ
for discourse; and a name of them all. John is a word, mountain is a
word, to run is a word, above is a word, and so on.
They are divided into classes, differently for different purposes. The
grammarian, who regards chiefly the concatenation of words in
sentences, divides them into noun, adjective, pronoun, verb, adverb,
preposition, 4 conjunction; these words are none of them names of
things. Noun is not a name of a “thing;” it is a name of a “class of
It is of great importance to distinguish this class of terms; to
understand well the function which they perform, and to mark the
subdivisions into which they are formed. There is not, however, such
difficulty in the subject as to require great minuteness in the
exposition.
As we have occasion to speak of things; animals, vegetables,
minerals; so we have occasion to speak of the marks, which we are
under the necessity of using, in order to record or to communicate
our thoughts respecting them. We cannot record or communicate our
thoughts respecting names, as man, tree, horse, to walk, to fly, to
eat, to converse, without marks for them. We proceed in the case of
names, as we do in other cases. We form them into classes, some
more, some less, comprehensive, and give a name to each.
We have one name, so general as to include them all; Word. That is
not a name of any thing. It is a name of the marks which we employ
for discourse; and a name of them all. John is a word, mountain is a
word, to run is a word, above is a word, and so on.
They are divided into classes, differently for different purposes. The
grammarian, who regards chiefly the concatenation of words in
sentences, divides them into noun, adjective, pronoun, verb, adverb,
preposition, 4 conjunction; these words are none of them names of
things. Noun is not a name of a “thing;” it is a name of a “class of
words,” as John, James, man, ox, tree, water, love, hatred; the same
is the case with adjective, verb, and so of the rest.
The philosopher makes another division of them, adapted to his
purposes, which has a more particular reference to their mode of
signification. Thus, he divides them into universal, and particular;
concrete, and abstract; positive, and negative; equivocal, and
univocal; relative, and absolute; and so on.
It is very easy to see that the word “universal,” for example, is not
a name of a thing. Things are all individual, not general. The name,
“man,” is a “universal,” because it applies to every individual of a
class; for the same reason the name “ox,” the name “horse,” the
name “dog,” and so on, are universals. The words, “genus” and
“species” are synonymous with “universal;” of course they also are
names of names. Such is the word “number.” “One,” “two,” “one
hundred,” “one thousand,” are “numbers;” in other words, “number”
is a general name for each and all of those other names.
Beside our names for names singly, we have occasion to name
combinations of names. Thus we have the name "predication.” This is
a name for the combination of three words, “subject,” “predicate,” and
“copula.” We have the name “sentence,” which never can be less,
implicitly or explicitly, than a predication, but is often more. The same
is the account of the word “definition.” We have the names “speech,”
“oration,” “sermon,” “conversation,” all of them names for a series of
sentences. We have 5 also names of written discourse, such as a
“volume,” a “book,” a “chapter” a “section,” a "paragraph."
2 A right understanding of the words which are names of names, is of great
importance in philosophy. The tendency was always strong to believe that whatever
receives a name must be an entity or being, having an independent existence of its
‘own; and if no real entity answering to the name could be found, men did not for
that reason suppose that none existed, but imagined that it was something
is the case with adjective, verb, and so of the rest.
The philosopher makes another division of them, adapted to his
purposes, which has a more particular reference to their mode of
signification. Thus, he divides them into universal, and particular;
concrete, and abstract; positive, and negative; equivocal, and
univocal; relative, and absolute; and so on.
It is very easy to see that the word “universal,” for example, is not
a name of a thing. Things are all individual, not general. The name,
“man,” is a “universal,” because it applies to every individual of a
class; for the same reason the name “ox,” the name “horse,” the
name “dog,” and so on, are universals. The words, “genus” and
“species” are synonymous with “universal;” of course they also are
names of names. Such is the word “number.” “One,” “two,” “one
hundred,” “one thousand,” are “numbers;” in other words, “number”
is a general name for each and all of those other names.
Beside our names for names singly, we have occasion to name
combinations of names. Thus we have the name "predication.” This is
a name for the combination of three words, “subject,” “predicate,” and
“copula.” We have the name “sentence,” which never can be less,
implicitly or explicitly, than a predication, but is often more. The same
is the account of the word “definition.” We have the names “speech,”
“oration,” “sermon,” “conversation,” all of them names for a series of
sentences. We have 5 also names of written discourse, such as a
“volume,” a “book,” a “chapter” a “section,” a "paragraph."
2 A right understanding of the words which are names of names, is of great
importance in philosophy. The tendency was always strong to believe that whatever
receives a name must be an entity or being, having an independent existence of its
‘own; and if no real entity answering to the name could be found, men did not for
that reason suppose that none existed, but imagined that it was something
peculiarly abstruse and mysterious, too high to be an object of sense. The meaning
of all general, and especially of all abstract terms, became in this way enveloped in
a mystical haze; and none of these have been more generally misunderstood, or
have been a more copious source of futile and bewildering speculation, than some
of the words which are names of names, Genus, Species, Universal, were long
‘supposed to be designations of sublime hyperphysical realities; number, instead of a
general name of all numerals, was supposed to be the name, if not of a concrete
thing, at least of a single property or attribute.
This class of names was well understood and correctly characterized by Hobbes,
of whose philosophy the distinction between names of names and of things was a
cardinal point.—Ed.
of all general, and especially of all abstract terms, became in this way enveloped in
a mystical haze; and none of these have been more generally misunderstood, or
have been a more copious source of futile and bewildering speculation, than some
of the words which are names of names, Genus, Species, Universal, were long
‘supposed to be designations of sublime hyperphysical realities; number, instead of a
general name of all numerals, was supposed to be the name, if not of a concrete
thing, at least of a single property or attribute.
This class of names was well understood and correctly characterized by Hobbes,
of whose philosophy the distinction between names of names and of things was a
cardinal point.—Ed.
SECTION II.
RELATIVE TERMS.
The explanation of Relative Terms will run to a considerable length.
The mode in which they are employed as marks is peculiar; and has
suggested the belief of something very mysterious in that which is
marked by them. It is therefore necessary to be minute in exhibiting
the combinations of ideas of which they are the names.
One peculiarity of Relative Terms, which it is necessary for us to
begin with noticing, is, that they always exist in pairs. There is no
relative without its correlate, either actual or implied. Thus, we have
Father and Son; Husband and Wife; Master and Servant; Subject and
King; also High and Low; Right and Left; Antecedent and Consequent.
In these cases of relative pairs, the two names are two different
words; in other cases, one word serves for both names. Of this sort
are the words Brother, Sister, Cousin, Friend, Like, Equal, and so on.
When we say that John is brother, we always mean of some one else,
as James, whom we also call brother. We call Jane the sister of Ann,
as we call Ann the sister of Jane. When we say that A is equal to B,
we signify, by the same expression, that B is equal to A; and so on.
It is always to be remembered, that, in speaking, we are only
indicating our own trains; and that of 7 course every word in a mark
of some part of a train. The parts of our trains to which we give
relative names, are either simple, or complex. The simple, are either
the simple sensations, or the ideas of those sensations. The complex,
The explanation of Relative Terms will run to a considerable length.
The mode in which they are employed as marks is peculiar; and has
suggested the belief of something very mysterious in that which is
marked by them. It is therefore necessary to be minute in exhibiting
the combinations of ideas of which they are the names.
One peculiarity of Relative Terms, which it is necessary for us to
begin with noticing, is, that they always exist in pairs. There is no
relative without its correlate, either actual or implied. Thus, we have
Father and Son; Husband and Wife; Master and Servant; Subject and
King; also High and Low; Right and Left; Antecedent and Consequent.
In these cases of relative pairs, the two names are two different
words; in other cases, one word serves for both names. Of this sort
are the words Brother, Sister, Cousin, Friend, Like, Equal, and so on.
When we say that John is brother, we always mean of some one else,
as James, whom we also call brother. We call Jane the sister of Ann,
as we call Ann the sister of Jane. When we say that A is equal to B,
we signify, by the same expression, that B is equal to A; and so on.
It is always to be remembered, that, in speaking, we are only
indicating our own trains; and that of 7 course every word in a mark
of some part of a train. The parts of our trains to which we give
relative names, are either simple, or complex. The simple, are either
the simple sensations, or the ideas of those sensations. The complex,
are either those clusters of simple ideas which we call the ideas of
objects, because they correspond with clustered sensations; or they
are the clusters which the mind puts together arbitrarily for its own
purposes.
If it is asked, why we give names in pairs? The general answer
immediately suggests itself; it is because the things named present
themselves in pairs; that is, are joined by association. But as many
things are joined in pairs by association, which do not receive relative
names, the cause may still be inquired of the classification. What is
the reason that some pairs do, while many more do not, receive
relative names? The cause is the same by which we are guided in
imposing other names. As the various combinations of ideas are far
too numerous for naming, and we are obliged to make a selection, we
name those which we find it of most importance to have named,
omitting the rest. It is a question of convenience, solved by
experience. It will be seen more distinctly hereafter that relative
names are one of the contrivances for epitomising; and that they
enable us to express ourselves with fewer words than we should be
able to do without them.3
3 No part of the Analysis is more valuable than the simple explanation here given
of a subject which has seemed so mysterious to some of the most enlightened and
penetrating philosophers, down even to the present time. The only difference
between relative names and any others consist in their being given in pairs; and the
reason of their being given in pairs is not the existence between two things, of a
mystical bond called a Relation, and supposed to have a kind of shadowy and
abstract realty, but a very simple peculiarity in the concrete fact which the two
names are intended to mark.
In order to make quite clear the nature of this peculiarity, it wil be desirable to
advert once more to the double mode of signification of concrete general names,
viz. that while they denote (or are names of) objects, they connote some fact
relating to those objects. The fact connoted by any name, relative or not, is always
of the same nature; it is some bodily or mental feeling, or some set of bodily or
objects, because they correspond with clustered sensations; or they
are the clusters which the mind puts together arbitrarily for its own
purposes.
If it is asked, why we give names in pairs? The general answer
immediately suggests itself; it is because the things named present
themselves in pairs; that is, are joined by association. But as many
things are joined in pairs by association, which do not receive relative
names, the cause may still be inquired of the classification. What is
the reason that some pairs do, while many more do not, receive
relative names? The cause is the same by which we are guided in
imposing other names. As the various combinations of ideas are far
too numerous for naming, and we are obliged to make a selection, we
name those which we find it of most importance to have named,
omitting the rest. It is a question of convenience, solved by
experience. It will be seen more distinctly hereafter that relative
names are one of the contrivances for epitomising; and that they
enable us to express ourselves with fewer words than we should be
able to do without them.3
3 No part of the Analysis is more valuable than the simple explanation here given
of a subject which has seemed so mysterious to some of the most enlightened and
penetrating philosophers, down even to the present time. The only difference
between relative names and any others consist in their being given in pairs; and the
reason of their being given in pairs is not the existence between two things, of a
mystical bond called a Relation, and supposed to have a kind of shadowy and
abstract realty, but a very simple peculiarity in the concrete fact which the two
names are intended to mark.
In order to make quite clear the nature of this peculiarity, it wil be desirable to
advert once more to the double mode of signification of concrete general names,
viz. that while they denote (or are names of) objects, they connote some fact
relating to those objects. The fact connoted by any name, relative or not, is always
of the same nature; it is some bodily or mental feeling, or some set of bodily or
mental feelings, accompanying or produced by the object. But in the case of the
ordinary names of objects, this fact concerns one object only, or rather only that
one object and the sentient mind. The peculiarity in the case of relative names is,
that the fact connoted concems two objects, and cannot be understood without
thinking of them both. It is a phenomenon in which two objects play a part. There is
no greater mystery in a phenomenon which concerns two objects, than in a
phenomenon which concerns only one. For example; the fact connoted by the word
cause, is a fact in which the thing which is the cause, is implicated along with
another thing which is the effect, The facts connoted by the word parent, and also
by the word son or daughter, are a long series of phenomena of which both the
parent and the child are parts; and the series of phenomena would not be that
which the name parent expresses, unless the child formed a part of it, nor would it
be that which the name son or daughter expresses, unless the parent formed a part
of it. Now, when in a series of phenomena of any interest to us two objects are
implicated, we naturally give names expressive of it to both the objects, and these
are relative names, The two correlative names denote two different objects, the
cause and the effect, or the parent and son; but though what they denote is
diferent, what they connote is in a certain sense the same: both names connote
the same set of facts, considered as giving one name to the one object, another
name to the other. This set of facts, which is connoted by both the correlative
names, was called by the old logicians the ground of the relation, fundamentum
relationis The fundamentum of any relation is the facts, fully set out, which are the
reason of giving to two objects two correlative names. In some cases both objects
seem to receive the same name; in the relation of likeness, both objects are said to
be like; in the relation of equality, both are said to be equal, But even here the
duality holds, on a stricter examination: for the first object (A) is not said to be like,
absolutely, but to be like the second object (B); the second is not said to be like
absolutely, but to be like the first, Now though "like” is only one name, “lke A” is
not the same name as “lke B,” so that there is really, in this case also, a pair of
names.
From these considerations we see that objects are said to be related, when there
is any fact, simple or complex, either apprehended by the senses or otherwise, in
which they both figure. Any objects, whether physical or mental, are related, or are
in a relation, to one another, in virtue of any complex state of consciousness into
which they both enter; even if it be a no more complex state of consciousness than
that of merely thinking of them together. And they are related to each other in as
many different ways, or in other words, they stand in as many distinct relations to
ordinary names of objects, this fact concerns one object only, or rather only that
one object and the sentient mind. The peculiarity in the case of relative names is,
that the fact connoted concems two objects, and cannot be understood without
thinking of them both. It is a phenomenon in which two objects play a part. There is
no greater mystery in a phenomenon which concerns two objects, than in a
phenomenon which concerns only one. For example; the fact connoted by the word
cause, is a fact in which the thing which is the cause, is implicated along with
another thing which is the effect, The facts connoted by the word parent, and also
by the word son or daughter, are a long series of phenomena of which both the
parent and the child are parts; and the series of phenomena would not be that
which the name parent expresses, unless the child formed a part of it, nor would it
be that which the name son or daughter expresses, unless the parent formed a part
of it. Now, when in a series of phenomena of any interest to us two objects are
implicated, we naturally give names expressive of it to both the objects, and these
are relative names, The two correlative names denote two different objects, the
cause and the effect, or the parent and son; but though what they denote is
diferent, what they connote is in a certain sense the same: both names connote
the same set of facts, considered as giving one name to the one object, another
name to the other. This set of facts, which is connoted by both the correlative
names, was called by the old logicians the ground of the relation, fundamentum
relationis The fundamentum of any relation is the facts, fully set out, which are the
reason of giving to two objects two correlative names. In some cases both objects
seem to receive the same name; in the relation of likeness, both objects are said to
be like; in the relation of equality, both are said to be equal, But even here the
duality holds, on a stricter examination: for the first object (A) is not said to be like,
absolutely, but to be like the second object (B); the second is not said to be like
absolutely, but to be like the first, Now though "like” is only one name, “lke A” is
not the same name as “lke B,” so that there is really, in this case also, a pair of
names.
From these considerations we see that objects are said to be related, when there
is any fact, simple or complex, either apprehended by the senses or otherwise, in
which they both figure. Any objects, whether physical or mental, are related, or are
in a relation, to one another, in virtue of any complex state of consciousness into
which they both enter; even if it be a no more complex state of consciousness than
that of merely thinking of them together. And they are related to each other in as
many different ways, or in other words, they stand in as many distinct relations to
one another, as there are specifically distinct states of consciousness of which they
both form parts. As these may be innumerable, the possible relations not only of
any one thing with others, but of any one thing with the same other, are infinitely
‘numerous and various. But they may all be reduced to a certain number of general
heads of classification, constituting the different kinds of Relation: each of which
requires examination apart, to ascertain what, in each case, the state of
consciousness, the cluster or train of sensations or thoughts, really is, in which the
‘two objects figure, and which is connoted by the correlative names. This
examination the author accordingly undertakes: and thus, under the guise of
explaining names, he analyses all the principal cases which the world and the
human mind present, of what are called Relations between things—Ed,
8 L The only, or at least the principal, occasions, for naming simple
sensations, or simple ideas, in pairs, seem to be these:
1 When we take them into simultaneous view, as such and such;
2. When we take them into simultaneous view, as antecedent and
consequent.
II. The principal occasions on which we name the complex ideas,
called objects, in pairs, are these four:
9 1. When we speak of them as having an order in space;
2. When we speak of them as having an order in time;
3. When we speak of them as agreeing or disagreeing in quantity;
4. As agreeing or disagreeing in quality.
IIL. The occasions on which we name the complex ideas of our own
formation in pairs, are,
10 1, When we speak of them as composed of the same or different
simple ideas;
2. When we speak of them as antecedent and consequent.
both form parts. As these may be innumerable, the possible relations not only of
any one thing with others, but of any one thing with the same other, are infinitely
‘numerous and various. But they may all be reduced to a certain number of general
heads of classification, constituting the different kinds of Relation: each of which
requires examination apart, to ascertain what, in each case, the state of
consciousness, the cluster or train of sensations or thoughts, really is, in which the
‘two objects figure, and which is connoted by the correlative names. This
examination the author accordingly undertakes: and thus, under the guise of
explaining names, he analyses all the principal cases which the world and the
human mind present, of what are called Relations between things—Ed,
8 L The only, or at least the principal, occasions, for naming simple
sensations, or simple ideas, in pairs, seem to be these:
1 When we take them into simultaneous view, as such and such;
2. When we take them into simultaneous view, as antecedent and
consequent.
II. The principal occasions on which we name the complex ideas,
called objects, in pairs, are these four:
9 1. When we speak of them as having an order in space;
2. When we speak of them as having an order in time;
3. When we speak of them as agreeing or disagreeing in quantity;
4. As agreeing or disagreeing in quality.
IIL. The occasions on which we name the complex ideas of our own
formation in pairs, are,
10 1, When we speak of them as composed of the same or different
simple ideas;
2. When we speak of them as antecedent and consequent.
Whatever it may be necessary to remark, respecting relative terms,
will occur in the consideration of these several cases.
I. 1. We speak of two sensations, as Same or Different, Like or
Unlike.
These words are Relatives of the double signification; each
individual of the pair has the same name. When we say that sensation
A is the “same” with 11 sensation B, we mean that B also is the
“same” with A; “different,” “like,” and “unlike,” have the same double
application.
Another ambiguity needs to be noted in the word “same.” When
there are two things, they are not the same thing; for “same,” in the
strict sense of the word, means one thing, and that only. Here it
means a great degree of likeness, a sense in which, with respect to
sensations and ideas, it is very frequently used.
Of two sensations, or two ideas, we, in truth, can only say, that
they are like or unlike; or, that the one comes first, the other after it.
It is now necessary to attend very carefully to what happens, when
we say that two sensations are like, or that they are unlike.
First of all, we have the two sensations. But what is it to have two
sensations? It is merely to be conscious of a change. But to be
conscious of a change in sensation, is sensation. It is an essential part
of the process. Without it we should not be sentient beings. To have
sensation, and not to be conscious of any change, is to have but one
sensation continued. We have already seen that this is a state which
seems incapable of being distinguished from that of having no
sensation. At any rate, what we mean by a sentient being, is not a
being with one unvaried sensation, but a being with sensations
continually varied; the varying being a necessary part of the having
will occur in the consideration of these several cases.
I. 1. We speak of two sensations, as Same or Different, Like or
Unlike.
These words are Relatives of the double signification; each
individual of the pair has the same name. When we say that sensation
A is the “same” with 11 sensation B, we mean that B also is the
“same” with A; “different,” “like,” and “unlike,” have the same double
application.
Another ambiguity needs to be noted in the word “same.” When
there are two things, they are not the same thing; for “same,” in the
strict sense of the word, means one thing, and that only. Here it
means a great degree of likeness, a sense in which, with respect to
sensations and ideas, it is very frequently used.
Of two sensations, or two ideas, we, in truth, can only say, that
they are like or unlike; or, that the one comes first, the other after it.
It is now necessary to attend very carefully to what happens, when
we say that two sensations are like, or that they are unlike.
First of all, we have the two sensations. But what is it to have two
sensations? It is merely to be conscious of a change. But to be
conscious of a change in sensation, is sensation. It is an essential part
of the process. Without it we should not be sentient beings. To have
sensation, and not to be conscious of any change, is to have but one
sensation continued. We have already seen that this is a state which
seems incapable of being distinguished from that of having no
sensation. At any rate, what we mean by a sentient being, is not a
being with one unvaried sensation, but a being with sensations
continually varied; the varying being a necessary part of the having
more sensations than one; and the varying, and the being conscious
of the variation, being not two things, but one and the same thing.
Having two sensations, therefore, is not only having sensation, but
the only 12 thing which can, in strictness, be called having sensation;
and the having two, and knowing they are two, which are not two
things, but one and the same thing, is not only sensation, and nothing
else than sensation, but the only thing which can, in strictness, be
called sensation. The having a new sensation, and knowing that it is
new, are not two things, but one and the same thing.4
4 The author is here endeavouring to express the most fundamental fact ofthe
consciousness—the necessity of change, or transition from one state to another in
order to our being conscious, He approaches very near to, without exactly touching,
‘the inference that all consciousness, all sensation, all knowledge must be of
doubles; the state passed from and the state passed to, are equally recognised by
us. Opening the eyes to the light, for the first time, we know a contrast,—a present
light, a past privation—but for the one we should not have known the other. Any
single thing is unknowable by us; ts relative opposite is apart of its very existence.
In a former Page it is stated that relative names are one of the conveniences of
epitomising. This is a narrow view to take of them. They are an essential part of
language; they are demanded by the intrinsic relativity of all nameable things. If we
have a thing called "light" we have also another thing but for which light could not
be known by us, “dark.” It is expedient to have names for both elements of the
‘mutually dependent couple. And so everywhere. Language would be insufficient for
its purposes if it did not provide the means of expressing the correlative (called also
the negative) of every thing named.
The case between sensation and sensation, resembles that
between sensation and idea. How do I know that an idea is not a
sensation? Who ever thought of asking the question? Is not the
having an idea, 13 and the knowing it as an idea, the same thing? The
having without the knowing is repugnant. The misfortune is, that the
word, know, has associations linked with it, which have nothing to do
of the variation, being not two things, but one and the same thing.
Having two sensations, therefore, is not only having sensation, but
the only 12 thing which can, in strictness, be called having sensation;
and the having two, and knowing they are two, which are not two
things, but one and the same thing, is not only sensation, and nothing
else than sensation, but the only thing which can, in strictness, be
called sensation. The having a new sensation, and knowing that it is
new, are not two things, but one and the same thing.4
4 The author is here endeavouring to express the most fundamental fact ofthe
consciousness—the necessity of change, or transition from one state to another in
order to our being conscious, He approaches very near to, without exactly touching,
‘the inference that all consciousness, all sensation, all knowledge must be of
doubles; the state passed from and the state passed to, are equally recognised by
us. Opening the eyes to the light, for the first time, we know a contrast,—a present
light, a past privation—but for the one we should not have known the other. Any
single thing is unknowable by us; ts relative opposite is apart of its very existence.
In a former Page it is stated that relative names are one of the conveniences of
epitomising. This is a narrow view to take of them. They are an essential part of
language; they are demanded by the intrinsic relativity of all nameable things. If we
have a thing called "light" we have also another thing but for which light could not
be known by us, “dark.” It is expedient to have names for both elements of the
‘mutually dependent couple. And so everywhere. Language would be insufficient for
its purposes if it did not provide the means of expressing the correlative (called also
the negative) of every thing named.
The case between sensation and sensation, resembles that
between sensation and idea. How do I know that an idea is not a
sensation? Who ever thought of asking the question? Is not the
having an idea, 13 and the knowing it as an idea, the same thing? The
having without the knowing is repugnant. The misfortune is, that the
word, know, has associations linked with it, which have nothing to do
with this case, but which intrude themselves along with the word, and
make a complexity, where otherwise there would be none.
This is a matter which deserves the greatest attention. One of the
most unfortunate cases of the illusions, which the close association of
ideas with words has produced, is created by ideas clinging to words
when they ought to be disjoined from them, and mixing themselves
by that means with the ideas under consideration, when they ought
to be considered wholly distinct from them. Nothing was of more
importance, than that the phenomenon, to which we are just now
directing our attention, the very first ingredient in the great mental
composition, should be accurately understood, and nothing mixed up
with it which did not truly belong to it.
There is no doubt that in one of its senses, knowledge is
synonymous with sensation, If I am asked what is my knowledge of
pain? I answer, the feeling of it, the having it. The blind man has not
the knowledge of colours; the meaning is, he has not the sensations:
if deaf also, he is without the knowledge, that is, the sensations, of
sounds: suppose him void of all other sensations, you suppose him
void of knowledge. In many cases, however, we arrive at knowledge,
by certain steps; by something of a process. The word, know, is most
frequently applied to those cases. When we know, by mere sensation,
we say we see, we hear, and so on; when we know by mere ideas, 14
or rather ideation, if we could use such a word, we say we conceive,
we think. The word know, therefore, being almost constantly joined
with the idea of a process, it is exceedingly difficult, when we apply it
to sensation, not to have the idea of a process at the same time; and
thus exceedingly difficult to conceive that sensation, and knowing, in
this case, are purely synonymous.
make a complexity, where otherwise there would be none.
This is a matter which deserves the greatest attention. One of the
most unfortunate cases of the illusions, which the close association of
ideas with words has produced, is created by ideas clinging to words
when they ought to be disjoined from them, and mixing themselves
by that means with the ideas under consideration, when they ought
to be considered wholly distinct from them. Nothing was of more
importance, than that the phenomenon, to which we are just now
directing our attention, the very first ingredient in the great mental
composition, should be accurately understood, and nothing mixed up
with it which did not truly belong to it.
There is no doubt that in one of its senses, knowledge is
synonymous with sensation, If I am asked what is my knowledge of
pain? I answer, the feeling of it, the having it. The blind man has not
the knowledge of colours; the meaning is, he has not the sensations:
if deaf also, he is without the knowledge, that is, the sensations, of
sounds: suppose him void of all other sensations, you suppose him
void of knowledge. In many cases, however, we arrive at knowledge,
by certain steps; by something of a process. The word, know, is most
frequently applied to those cases. When we know, by mere sensation,
we say we see, we hear, and so on; when we know by mere ideas, 14
or rather ideation, if we could use such a word, we say we conceive,
we think. The word know, therefore, being almost constantly joined
with the idea of a process, it is exceedingly difficult, when we apply it
to sensation, not to have the idea of a process at the same time; and
thus exceedingly difficult to conceive that sensation, and knowing, in
this case, are purely synonymous.
As the knowing I have an idea, is merely having the idea; as the
having a sensation, and knowing I have a sensation; the knowing, for
example, that I have the pain of the toothache, and the having that
pain; are not two things, but one and the same thing; so the having a
change of sensation, and knowing I have it, are not two things but
one and the same thing.
Having a change, I have occasion to mark that change. The change
has taken place in a train of feelings. I call the first part by one name,
the last by another, and the marking of the change is effected.
Suppose that, without any organ of sense but the eye, my first
sensation is red, my next green. The whole process is sensation. Yet
the green is not the red. What we call making the distinction,
therefore, has taken place, and it is involved in the sensation.
My names, green, and red, thus applied, are absolute names. The
one has no reference to the other. Suppose that after green, I have
the sensations, blue, yellow, violet, white, black; and that I mark
them respectively by these names. These are still absolute names.
Each marks a particular sensation, and does nothing more. But, now,
suppose that, after my sensations red, green, blue, &c, I have the
sensation 15 red again; that I recognise it as like the sensation I had
first, and that I have a desire to mark that recognition; it remains to
explain what are the steps of this process.
Having the sensation a second time needs no explanation; it is the
same thing as having it the first. But what happens in recognising that
it is similar to a former sensation?
Beside the Sensation, in this case, there is an Idea. The idea of the
former sensation is called up by, that is, associated with, the new
sensation. As having a sensation, and a sensation, and knowing them,
that is, distinguishing them, are the same thing; and having an idea,
having a sensation, and knowing I have a sensation; the knowing, for
example, that I have the pain of the toothache, and the having that
pain; are not two things, but one and the same thing; so the having a
change of sensation, and knowing I have it, are not two things but
one and the same thing.
Having a change, I have occasion to mark that change. The change
has taken place in a train of feelings. I call the first part by one name,
the last by another, and the marking of the change is effected.
Suppose that, without any organ of sense but the eye, my first
sensation is red, my next green. The whole process is sensation. Yet
the green is not the red. What we call making the distinction,
therefore, has taken place, and it is involved in the sensation.
My names, green, and red, thus applied, are absolute names. The
one has no reference to the other. Suppose that after green, I have
the sensations, blue, yellow, violet, white, black; and that I mark
them respectively by these names. These are still absolute names.
Each marks a particular sensation, and does nothing more. But, now,
suppose that, after my sensations red, green, blue, &c, I have the
sensation 15 red again; that I recognise it as like the sensation I had
first, and that I have a desire to mark that recognition; it remains to
explain what are the steps of this process.
Having the sensation a second time needs no explanation; it is the
same thing as having it the first. But what happens in recognising that
it is similar to a former sensation?
Beside the Sensation, in this case, there is an Idea. The idea of the
former sensation is called up by, that is, associated with, the new
sensation. As having a sensation, and a sensation, and knowing them,
that is, distinguishing them, are the same thing; and having an idea,
and an idea, is knowing them; so, having an idea and a sensation,
and distinguishing the one from the other, are the same thing. But, to
know that I have the idea and the sensation, in this case, is not all; I
observe, that the sensation is like the idea. What is this observation of
likeness? Is it any thing but that distinguishing of one feeling from
another, which we have recognised to be the same thing as having
two feelings? As change of sensation is sensation; as change, from a
sensation to an idea, differs from change to a sensation, in nothing
but this, that the second feeling in the latter change is an idea, not a
sensation; and as the passing from one feeling to another is
distinguishing; the whole difficulty seems to be resolved; for
undoubtedly the distinguishing differences and similarities, is the
same thing; a similarity being nothing but a slight difference.s As 16
change from red to green, and knowing the change, or from a
sensation of sight, to one of any other of the senses, the most
different, is all sensation; so change from one shade of red to
another, is assuredly sensation. Its being a different shade consists in
my feeling of it, that is, in my sensation.
E More properly Similariy is “agreement in difference.” Difference or
discrimination is one thing, one element of knowledge or cognition; Similarity or
agreement in difference is another thing, the second or completing element of
knowledge. The two work together in closest intimacy, but they should nether be
Iooked upon as the same fact, nor as merely a various shading of the same fact.
Without difference there would be no similarity; but similarity is difference and
something more. At their roots or first origins, the two processes lie in almost
undistinguishable closeness; but in thelr developments they run wide apart. No fact
or attribute is known, or mentally possessed, without the union of many shocks of
difference with many shocks of identity, or agreement in dference—B.
Passing from red to red, red, red, through a succession of
distinguishable shades, is one train of pure sensation: passing from
red to green, blue, tasting, smelling, hearing, touching, is another
and distinguishing the one from the other, are the same thing. But, to
know that I have the idea and the sensation, in this case, is not all; I
observe, that the sensation is like the idea. What is this observation of
likeness? Is it any thing but that distinguishing of one feeling from
another, which we have recognised to be the same thing as having
two feelings? As change of sensation is sensation; as change, from a
sensation to an idea, differs from change to a sensation, in nothing
but this, that the second feeling in the latter change is an idea, not a
sensation; and as the passing from one feeling to another is
distinguishing; the whole difficulty seems to be resolved; for
undoubtedly the distinguishing differences and similarities, is the
same thing; a similarity being nothing but a slight difference.s As 16
change from red to green, and knowing the change, or from a
sensation of sight, to one of any other of the senses, the most
different, is all sensation; so change from one shade of red to
another, is assuredly sensation. Its being a different shade consists in
my feeling of it, that is, in my sensation.
E More properly Similariy is “agreement in difference.” Difference or
discrimination is one thing, one element of knowledge or cognition; Similarity or
agreement in difference is another thing, the second or completing element of
knowledge. The two work together in closest intimacy, but they should nether be
Iooked upon as the same fact, nor as merely a various shading of the same fact.
Without difference there would be no similarity; but similarity is difference and
something more. At their roots or first origins, the two processes lie in almost
undistinguishable closeness; but in thelr developments they run wide apart. No fact
or attribute is known, or mentally possessed, without the union of many shocks of
difference with many shocks of identity, or agreement in dference—B.
Passing from red to red, red, red, through a succession of
distinguishable shades, is one train of pure sensation: passing from
red to green, blue, tasting, smelling, hearing, touching, is another
train of pure sensation; that these are not the same trains, but
different trains, consists in their being felt to be so; they would not be
different, but for the feeling: and that a feeling is different, and
known to be so, are not two things, but one and the same thing.
Having two such trains, I want marks to distinguish them. For this
purpose, I invent the words “same,” “similar,” and their contraries; by
means of which, my object is attained. I call the parts of a train, such
as the first, “same,” or “similar;” those of a train like the last,
“different,” “dissimilar.”
By these relative terms, we name the sensations in pairs. When we
say, same, we mean that sensations 17 A, and B, are the same;
different, that A, and B, are different; like and unlike, the same. By
these words we have four pairs of relative terms.
A B.
same same
different different
like like
unlike unlike.
The feeling is perfectly analogous in the case of the ideas of those
sensations; and the naming is the same. Thus the idea of red, green,
and so on, and the ideas of the different shades of red are
distinguished from one another by the ideas themselves. To have
ideas different and ideas distinguished, are synonymous expressions;
different and distinguished, meaning exactly the same thing.
The sensations above mentioned, and their ideas, have the same
absolute names: thus, red is at once the name of the sensation, and
the name of the idea; green, at once the name of the sensation and
the idea; sweet, at once the name of the sensation and the idea. The
different trains, consists in their being felt to be so; they would not be
different, but for the feeling: and that a feeling is different, and
known to be so, are not two things, but one and the same thing.
Having two such trains, I want marks to distinguish them. For this
purpose, I invent the words “same,” “similar,” and their contraries; by
means of which, my object is attained. I call the parts of a train, such
as the first, “same,” or “similar;” those of a train like the last,
“different,” “dissimilar.”
By these relative terms, we name the sensations in pairs. When we
say, same, we mean that sensations 17 A, and B, are the same;
different, that A, and B, are different; like and unlike, the same. By
these words we have four pairs of relative terms.
A B.
same same
different different
like like
unlike unlike.
The feeling is perfectly analogous in the case of the ideas of those
sensations; and the naming is the same. Thus the idea of red, green,
and so on, and the ideas of the different shades of red are
distinguished from one another by the ideas themselves. To have
ideas different and ideas distinguished, are synonymous expressions;
different and distinguished, meaning exactly the same thing.
The sensations above mentioned, and their ideas, have the same
absolute names: thus, red is at once the name of the sensation, and
the name of the idea; green, at once the name of the sensation and
the idea; sweet, at once the name of the sensation and the idea. The
relative terms, it is obvious, have the same extent of application.
Same, different, like, and unlike, are names of pairs of ideas, as well
as pairs of sensations.
It seems, therefore, to be made clear, that, in applying to the
simple sensations and ideas their absolute names, which are names
of classes, as red, green, sweet, bitter; and also applying to them
names which denote them in pairs, as such and such; there is nothing
whatsoever but having the sensations, having the ideas, and making
marks for them.6
§ The author commences his survey of Relations with the most universal of them
all. Likeness and Unlikeness; and he examines these as subsisting between simple
sensations or ideas; for whatever be the true theory of likeness or unlikeness as
between the simple elements, the same, in essentials, will serve for the likenesses
or unlikenesses of the wholes compounded of them.
Examining, then, what constitutes likeness between two sensations (meaning two
exactly similar sensations experienced at different times); he says, that to feel the
‘two sensations to be alike, is one and the same thing with having the two
sensations. Their being alike is nothing but their being felt to be alike; their being
unlike is nothing but their being felt to be unlike. The feeling of unlikeness is merely
that feeling of change, in passing from the one to the other, which makes them two,
and without which we should not be conscious of them at all. The feeling of
likeness, is the being reminded of the former sensation by the present, that is,
having the idea of the former sensation called up by the present, and distinguishing
them as sensation and idea.
It does not seem to me that this mode of describing the matter explains anything,
or leaves the likenesses and unlikenesses of our simple feelings less an ultimate fact
than they were before. All it amounts to is, that likeness and unlikeness are
themselves only a matter of feeling: and that when we have two feelings, the
feeling of their likeness or unlikeness is inextricably interwoven with the fact of
having the feelings. One of the conditions, under which we have feelings, is that
they are like and unlike: and in the case of simple feelings, we cannot separate the
likeness or unlikeness from the feelings themselves. It is by no means certain,
however, that when we have two feelings in immediate succession, the feeling of
Same, different, like, and unlike, are names of pairs of ideas, as well
as pairs of sensations.
It seems, therefore, to be made clear, that, in applying to the
simple sensations and ideas their absolute names, which are names
of classes, as red, green, sweet, bitter; and also applying to them
names which denote them in pairs, as such and such; there is nothing
whatsoever but having the sensations, having the ideas, and making
marks for them.6
§ The author commences his survey of Relations with the most universal of them
all. Likeness and Unlikeness; and he examines these as subsisting between simple
sensations or ideas; for whatever be the true theory of likeness or unlikeness as
between the simple elements, the same, in essentials, will serve for the likenesses
or unlikenesses of the wholes compounded of them.
Examining, then, what constitutes likeness between two sensations (meaning two
exactly similar sensations experienced at different times); he says, that to feel the
‘two sensations to be alike, is one and the same thing with having the two
sensations. Their being alike is nothing but their being felt to be alike; their being
unlike is nothing but their being felt to be unlike. The feeling of unlikeness is merely
that feeling of change, in passing from the one to the other, which makes them two,
and without which we should not be conscious of them at all. The feeling of
likeness, is the being reminded of the former sensation by the present, that is,
having the idea of the former sensation called up by the present, and distinguishing
them as sensation and idea.
It does not seem to me that this mode of describing the matter explains anything,
or leaves the likenesses and unlikenesses of our simple feelings less an ultimate fact
than they were before. All it amounts to is, that likeness and unlikeness are
themselves only a matter of feeling: and that when we have two feelings, the
feeling of their likeness or unlikeness is inextricably interwoven with the fact of
having the feelings. One of the conditions, under which we have feelings, is that
they are like and unlike: and in the case of simple feelings, we cannot separate the
likeness or unlikeness from the feelings themselves. It is by no means certain,
however, that when we have two feelings in immediate succession, the feeling of
their likeness is not a third feeling which follows instead of being involved in the
‘two. This question is expressly left open by Mr Herbert Spencer, in his “Principles of
Psychology;” and 1 am not aware that any philosopher has conclusively resolved it.
We do not get rid of any difficulty by calling the feeling of likeness the same thing
with the two feelings that are alike: we have equally to postulate likeness and
unlikeness as primitive facts—as an inherent distinction among our sensations; and
whichever form of phraseology we employ makes no difference in the ulterior
developments of psychology. It is of no practical consequence whether we say that
a phenomenon is resolved into sensations and ideas, or into sensations, ideas, and
their resemblances, since under the one expression as under the other the
resemblance must be recognised as an indispensable element in the compound.
When we pass from resemblance between simple sensations and ideas, to
resemblance between complex wholes, the process, though not essentially different,
is more complicated, for it involves a comparison of part with part, element with
element, and therefore a previous discrimination of the elements, When we judge
that an external object, compounded of a number of attributes, is like another
external object; since they are not, usually, alike in all their attributes, we have to
take the two objects into simultaneous consideration in respect to each of their
various attributes one after another: their colour, to observe whether that is similar;
their size, whether that is similar; their figure, their weight, and so on. It comes at
last to a perception of likeness or unlikeness between simple sensations: but we
reduce it to this by attending separately to one of the simple sensations forming the
one cluster, and to one of those forming the other cluster, and if possible adjusting
our organs of sense so as to have these two sensations in immediate juxtaposition:
as when we put two objects, of which we wish to compare the colour, side by side,
so that our sense of sight may pass directly from one of the two sensations of
colour to the other. This act of attention directed successively to single attributes,
blunts our feeling of the other attributes of the objects, and enables us to feel the
likeness of the single sensations almost as vividly as if we had nothing but these in
our mind. Having fet this likeness, we say that the sensations are like, and that the
two objects are like in respect of those sensations: and continuing the process we
pronounce them to be either lke or unlike in each of the other sensations which we
receive from them.—£d.
18 2. The only other relative terms applicable to simple sensations
and ideas, are those which denote them as Antecedent and
‘two. This question is expressly left open by Mr Herbert Spencer, in his “Principles of
Psychology;” and 1 am not aware that any philosopher has conclusively resolved it.
We do not get rid of any difficulty by calling the feeling of likeness the same thing
with the two feelings that are alike: we have equally to postulate likeness and
unlikeness as primitive facts—as an inherent distinction among our sensations; and
whichever form of phraseology we employ makes no difference in the ulterior
developments of psychology. It is of no practical consequence whether we say that
a phenomenon is resolved into sensations and ideas, or into sensations, ideas, and
their resemblances, since under the one expression as under the other the
resemblance must be recognised as an indispensable element in the compound.
When we pass from resemblance between simple sensations and ideas, to
resemblance between complex wholes, the process, though not essentially different,
is more complicated, for it involves a comparison of part with part, element with
element, and therefore a previous discrimination of the elements, When we judge
that an external object, compounded of a number of attributes, is like another
external object; since they are not, usually, alike in all their attributes, we have to
take the two objects into simultaneous consideration in respect to each of their
various attributes one after another: their colour, to observe whether that is similar;
their size, whether that is similar; their figure, their weight, and so on. It comes at
last to a perception of likeness or unlikeness between simple sensations: but we
reduce it to this by attending separately to one of the simple sensations forming the
one cluster, and to one of those forming the other cluster, and if possible adjusting
our organs of sense so as to have these two sensations in immediate juxtaposition:
as when we put two objects, of which we wish to compare the colour, side by side,
so that our sense of sight may pass directly from one of the two sensations of
colour to the other. This act of attention directed successively to single attributes,
blunts our feeling of the other attributes of the objects, and enables us to feel the
likeness of the single sensations almost as vividly as if we had nothing but these in
our mind. Having fet this likeness, we say that the sensations are like, and that the
two objects are like in respect of those sensations: and continuing the process we
pronounce them to be either lke or unlike in each of the other sensations which we
receive from them.—£d.
18 2. The only other relative terms applicable to simple sensations
and ideas, are those which denote them as Antecedent and
Consequent.
19 I have sensation red, sensation green. Why I mark them red,
and green, or as “different,” has already been seen. What happens in
marking them 20 as “antecedent” and “consequent” comes next to be
considered.
A sensation, the moment it ceases, is gone for ever. When I have
two sensations, therefore, A, and B, one first, the other following,
sensation A is gone, before sensation B exists. But though sensation A
is gone, its idea is not gone. Its idea, called up by association, exists
along with sensation B, or the idea of sensation B. My knowing that
the idea of sensation A is the idea of sensation A, is my having the
idea. Having it, and knowing it, are not two things, but one and the
same thing. Having the idea of sensation A, that is, having the idea of
the immediate antecedent of sensation B, seems, also, to be the
same thing with knowing it as the idea of that antecedent. Having
sensation A, and after it sensation B, is mere sensation; and having
the idea of sensation A, the immediate antecedent, called up by
sensation B, the immediate consequent, is knowing it for that
antecedent. The links of the train are three; 1, sensation A; 2,
sensation B; 3, the idea of sensation A, in a certain order with B,
called up by sensation B; and after this, namin.
The case appears mysterious, solely, from the want of words to
express it clearly; and our confirmed habit of inattention to the
process. Suppose, that 21 instead of two sensations, A and B, we
have three, A, B, and C, in immediate succession. I recognise A, as
the antecedent of B; B, as the antecedent of C. What is the process?
‘The idea of sensation A, is associated with sensation B; and the idea
of sensation B, is associated with sensation C. But sensation C, is not
associated with the idea of sensation B solely, it is associated also
19 I have sensation red, sensation green. Why I mark them red,
and green, or as “different,” has already been seen. What happens in
marking them 20 as “antecedent” and “consequent” comes next to be
considered.
A sensation, the moment it ceases, is gone for ever. When I have
two sensations, therefore, A, and B, one first, the other following,
sensation A is gone, before sensation B exists. But though sensation A
is gone, its idea is not gone. Its idea, called up by association, exists
along with sensation B, or the idea of sensation B. My knowing that
the idea of sensation A is the idea of sensation A, is my having the
idea. Having it, and knowing it, are not two things, but one and the
same thing. Having the idea of sensation A, that is, having the idea of
the immediate antecedent of sensation B, seems, also, to be the
same thing with knowing it as the idea of that antecedent. Having
sensation A, and after it sensation B, is mere sensation; and having
the idea of sensation A, the immediate antecedent, called up by
sensation B, the immediate consequent, is knowing it for that
antecedent. The links of the train are three; 1, sensation A; 2,
sensation B; 3, the idea of sensation A, in a certain order with B,
called up by sensation B; and after this, namin.
The case appears mysterious, solely, from the want of words to
express it clearly; and our confirmed habit of inattention to the
process. Suppose, that 21 instead of two sensations, A and B, we
have three, A, B, and C, in immediate succession. I recognise A, as
the antecedent of B; B, as the antecedent of C. What is the process?
‘The idea of sensation A, is associated with sensation B; and the idea
of sensation B, is associated with sensation C. But sensation C, is not
associated with the idea of sensation B solely, it is associated also
with the idea of sensation A. It is associated, however, differently with
the one and the other. It is associated with B immediately; it is
associated with A, only through the medium of B; it calls up the idea
of 8, by its own associating power, and the idea of B, calls up the idea
of A. This second state of consciousness is different from the first.
The first is that in consequence of which B receives the name
“Antecedent,” and C the name “Consequent.” When two sensations in
a train are such, that, if one exists, it has the idea of the other along
with it, by its immediate exciting power, and not through any
intermediate idea; the sensation, the idea of which is thus excited, is
called the antecedent, the sensation which thus excites that idea, is
called the consequent.
It is evident that the terms, “antecedent,” and “consequent,” are
not applied in consequence of sensation merely, but in consequence
of sensation joined with ideas. The antecedent sensation, which is
past, must be revived by the consequent sensation, which is present.
It is the peculiarity of this revival which procures it the name. If
revived by any other sensation, it would not have that name.
The Clock strikes three. My feelings are, three sensations of
hearing, in succession. How do I know 22 them to be three successive
sensations? The process in this instance does not seem to be very
difficult to trace. The clock strikes one; this is pure sensation. It
strikes two; this is a sensation, joined with the idea of the preceding
sensation, and the idea of the feeling (also sensation), called change
of sensation, or passage from one sensation to another. After two, the
clock strikes three; there is, here, sensation, and a double
association; the third stroke is sensation; that is associated
immediately with the idea of the second, and through the idea of the
second, with the idea of the first. It is observable, that these
successive associations soon cease to afford distinct ideas; they
the one and the other. It is associated with B immediately; it is
associated with A, only through the medium of B; it calls up the idea
of 8, by its own associating power, and the idea of B, calls up the idea
of A. This second state of consciousness is different from the first.
The first is that in consequence of which B receives the name
“Antecedent,” and C the name “Consequent.” When two sensations in
a train are such, that, if one exists, it has the idea of the other along
with it, by its immediate exciting power, and not through any
intermediate idea; the sensation, the idea of which is thus excited, is
called the antecedent, the sensation which thus excites that idea, is
called the consequent.
It is evident that the terms, “antecedent,” and “consequent,” are
not applied in consequence of sensation merely, but in consequence
of sensation joined with ideas. The antecedent sensation, which is
past, must be revived by the consequent sensation, which is present.
It is the peculiarity of this revival which procures it the name. If
revived by any other sensation, it would not have that name.
The Clock strikes three. My feelings are, three sensations of
hearing, in succession. How do I know 22 them to be three successive
sensations? The process in this instance does not seem to be very
difficult to trace. The clock strikes one; this is pure sensation. It
strikes two; this is a sensation, joined with the idea of the preceding
sensation, and the idea of the feeling (also sensation), called change
of sensation, or passage from one sensation to another. After two, the
clock strikes three; there is, here, sensation, and a double
association; the third stroke is sensation; that is associated
immediately with the idea of the second, and through the idea of the
second, with the idea of the first. It is observable, that these
successive associations soon cease to afford distinct ideas; they
hardly do so beyond the second stage. When the clock strikes, we
may have distinct ideas of the strokes, as far as three, hardly farther;
we must then have recourse to namin, and call the strokes, four, five,
six, and so on: otherwise we should be wholly unable to tell how
often the clock had struck.
In the preceding pairs of relative terms, we have found only one
name for each pair. Thus, when we say of A and B, that A is similar to
B, we say also, that B is similar to A. We have now an instance of a
pair of relative terms, consisting not of the same, but of different
names. If we call A antecedent, we call B consequent. The first class
were called by the ancient logicians, synonymous, the second
heteronymous; we may call them more intelligibly, single-worded, and
double-worded, relatives.
7 The next relation which the author examines is that of succession, or
Antecedent and Consequent. And here again we have one of the universal
conditions to which all our feelings or states of consciousness are subject.
Whenever we have more feelings than one, we must have them either
simultaneously or in succession; and when we are conscious of having them in
succession, we cannot in any way separate or isolate the succession from the
feelings themselves, The author attempts to carry the analysis somewhat farther, He
says that when we have two sensations in the order of antecedent and consequent,
the consequent calls up the idea of the antecedent; and that this fact, that a
sensation calls up the idea of another sensation directly, and not through an
intermediate idea, constitutes that other sensation the antecedent of the sensation
which reminds us of its not a consequence of the one sensation’s having
preceded the other, but is literally all we mean by the one sensations having
preceded the other, There seem to be grave objections to this doctrine. In the first
place, there is no law of association by which a consequent calls up the idea of ts
antecedent. The law of successive association is that the antecedent calls up the
idea of the consequent, but not conversely; as is seen in the difficulty of repeating
backwards even a form of words with which we are very familia, We get round from
the consequent to the antecedent by an indirect process, through the medium of
other ideas; or by going back, at each step, to the beginning of the train, and
may have distinct ideas of the strokes, as far as three, hardly farther;
we must then have recourse to namin, and call the strokes, four, five,
six, and so on: otherwise we should be wholly unable to tell how
often the clock had struck.
In the preceding pairs of relative terms, we have found only one
name for each pair. Thus, when we say of A and B, that A is similar to
B, we say also, that B is similar to A. We have now an instance of a
pair of relative terms, consisting not of the same, but of different
names. If we call A antecedent, we call B consequent. The first class
were called by the ancient logicians, synonymous, the second
heteronymous; we may call them more intelligibly, single-worded, and
double-worded, relatives.
7 The next relation which the author examines is that of succession, or
Antecedent and Consequent. And here again we have one of the universal
conditions to which all our feelings or states of consciousness are subject.
Whenever we have more feelings than one, we must have them either
simultaneously or in succession; and when we are conscious of having them in
succession, we cannot in any way separate or isolate the succession from the
feelings themselves, The author attempts to carry the analysis somewhat farther, He
says that when we have two sensations in the order of antecedent and consequent,
the consequent calls up the idea of the antecedent; and that this fact, that a
sensation calls up the idea of another sensation directly, and not through an
intermediate idea, constitutes that other sensation the antecedent of the sensation
which reminds us of its not a consequence of the one sensation’s having
preceded the other, but is literally all we mean by the one sensations having
preceded the other, There seem to be grave objections to this doctrine. In the first
place, there is no law of association by which a consequent calls up the idea of ts
antecedent. The law of successive association is that the antecedent calls up the
idea of the consequent, but not conversely; as is seen in the difficulty of repeating
backwards even a form of words with which we are very familia, We get round from
the consequent to the antecedent by an indirect process, through the medium of
other ideas; or by going back, at each step, to the beginning of the train, and
repeating it downwards until we reach that particular link. When a consequent
directly recalls its antecedent, itis by synchronous association, when the antecedent
happens to have been so prolonged as to coexist with, instead of merely preceding,
the consequent.
‘The next difficulty is, that although the direct recalling of the idea of a past
sensation by a present, without any intermediate link, does not take place from
consequent to antecedent, it does take place from like to like: a sensation recalls
the idea of a past sensation resembling itself, without the intervention of any other
idea, The author, however, says, that "when two sensations in a train are such that
if one exists, it has the idea of the other along with it by its immediate exciting
power, and not through any intermediate idea; the sensation, the idea of which is
thus excited, is called the antecedent, the sensation which thus excites that idea is
called the consequent.” If this therefore were correct, we should give the names of
antecedent and consequent not to the sensations which really are so, but to those
which recall one another by resemblance,
Thirdly and lastly, to explain antecedence, Le. the succession between two
feelings, by saying that one of the two calls up the idea of the other, that is to say,
is followed by it, is to explain succession by succession, and antecedence by
antecedence. Every explanation of anything by states of our consciousness, includes
as part of the explanation a succession between those states; and it is useless
attempting to analyse that which comes out as an element in every analysis we are
able to make, Antecedence and consequence, as well as likeness and unlikeness,
must be postulated as universal conditions of Nature, inherent in all our feelings
whether of external or of internal consciousness.— Ed.
23 IL. Having shewn what takes place in naming simple sensations,
and simple ıeas, in pairs, both as 24 such and such, and as
antecedent and consequent, we come to the second case of relative
terms, that of naming the clusters, called exreRNAL oBxcTs, in pairs.
The principal occasions of doing so we have said are four.
1. When we speak of them, as they exist in the synchronous order,
that is, the order in space, we use such relative terms as the
following: high, low; east, west; right, left; hind, fore; and so on.
directly recalls its antecedent, itis by synchronous association, when the antecedent
happens to have been so prolonged as to coexist with, instead of merely preceding,
the consequent.
‘The next difficulty is, that although the direct recalling of the idea of a past
sensation by a present, without any intermediate link, does not take place from
consequent to antecedent, it does take place from like to like: a sensation recalls
the idea of a past sensation resembling itself, without the intervention of any other
idea, The author, however, says, that "when two sensations in a train are such that
if one exists, it has the idea of the other along with it by its immediate exciting
power, and not through any intermediate idea; the sensation, the idea of which is
thus excited, is called the antecedent, the sensation which thus excites that idea is
called the consequent.” If this therefore were correct, we should give the names of
antecedent and consequent not to the sensations which really are so, but to those
which recall one another by resemblance,
Thirdly and lastly, to explain antecedence, Le. the succession between two
feelings, by saying that one of the two calls up the idea of the other, that is to say,
is followed by it, is to explain succession by succession, and antecedence by
antecedence. Every explanation of anything by states of our consciousness, includes
as part of the explanation a succession between those states; and it is useless
attempting to analyse that which comes out as an element in every analysis we are
able to make, Antecedence and consequence, as well as likeness and unlikeness,
must be postulated as universal conditions of Nature, inherent in all our feelings
whether of external or of internal consciousness.— Ed.
23 IL. Having shewn what takes place in naming simple sensations,
and simple ıeas, in pairs, both as 24 such and such, and as
antecedent and consequent, we come to the second case of relative
terms, that of naming the clusters, called exreRNAL oBxcTs, in pairs.
The principal occasions of doing so we have said are four.
1. When we speak of them, as they exist in the synchronous order,
that is, the order in space, we use such relative terms as the
following: high, low; east, west; right, left; hind, fore; and so on.
It is necessary to carry along with us a correct idea of what is
meant by synchronous order, that is, the order of simultaneous, in
contradistinction to that of successive, existence. The synchronous
order is much more complex than the successive. The successive 25
order is all, as it were, in one direction. The synchronous is in every
possible direction. The following seems to be the best mode of
conceiving it.
Take a single particle of matter as a centre. Other particles may be
aggregated to it, in the line of every possible radius; and as the radii
diverge, and other lines, tending to the centre, may be continually
interposed, to any number, particles may be aggregated in those
numberless directions. They may also be aggregated in those
directions to a less or a greater extent. And they may be aggregated
to an equal extent in every direction; or to a greater extent in some of
the directions, a less extent in others. In the first case of aggregation
they compose a globe; in the last, any other shape.
Every one of the particles in this aggregate, has a certain order;
first with respect to the centre particle; next with respect to every
other particle. This order is also called, the Position of the particle. In
such an aggregate, therefore, the positions are innumerable. It is
thence observable, that position is an exceedingly complex idea; for
the position of each of those particles is its order with respect to
every one of the other innumerable particles; it includes, therefore,
innumerable ingredients. Hence it is not wonderful that, while viewed
in the lump, it should seem obscure and mysterious.
Of positions, thus numberless, it is a small portion, only that have
names. Bulk is a name for an aggregate of particles, greater, or less.
Figure is only a modification, or case, of bulk; it is more or fewer
particles in such and such directions.
meant by synchronous order, that is, the order of simultaneous, in
contradistinction to that of successive, existence. The synchronous
order is much more complex than the successive. The successive 25
order is all, as it were, in one direction. The synchronous is in every
possible direction. The following seems to be the best mode of
conceiving it.
Take a single particle of matter as a centre. Other particles may be
aggregated to it, in the line of every possible radius; and as the radii
diverge, and other lines, tending to the centre, may be continually
interposed, to any number, particles may be aggregated in those
numberless directions. They may also be aggregated in those
directions to a less or a greater extent. And they may be aggregated
to an equal extent in every direction; or to a greater extent in some of
the directions, a less extent in others. In the first case of aggregation
they compose a globe; in the last, any other shape.
Every one of the particles in this aggregate, has a certain order;
first with respect to the centre particle; next with respect to every
other particle. This order is also called, the Position of the particle. In
such an aggregate, therefore, the positions are innumerable. It is
thence observable, that position is an exceedingly complex idea; for
the position of each of those particles is its order with respect to
every one of the other innumerable particles; it includes, therefore,
innumerable ingredients. Hence it is not wonderful that, while viewed
in the lump, it should seem obscure and mysterious.
Of positions, thus numberless, it is a small portion, only that have
names. Bulk is a name for an aggregate of particles, greater, or less.
Figure is only a modification, or case, of bulk; it is more or fewer
particles in such and such directions.
These things being explained, it now remains to 26 shew, of what
copies of sensations, peculiarly combined, the complex ideas in
question are composed.
The simplest case of position, or synchronous order, is that of two
or more particles in one direction. Let us take the particle, conceived
as the centre particle, in a preceding supposition, and let us
aggregate to it a number of particles, all in the direction of a single
radius, one by one. We have first the centre particle, and one other, in
juxta-position. This is the simplest case of synchronous order, and this
is the simplest of all positions. Let us next aggregate a second
particle; we have now the centre particle, and two more. The position
of the first of the aggregated particles with respect to the centre
particle is contact, or juxta-position; that of the second is not juxta-
position, but position at the distance of a particle; the next which is
aggregated, is at the distance of two; the next of three particles, and
so on, to any extent.
Particles thus aggregated, all in the direction of a single radius from
the first, constitute a line of less or greater length, according to the
number of aggregated particles.
Line is a word of great importance; because it is by that, chiefly, we
express ourselves concerning synchronous order; or frame names for
positions. Now it happens, that Line has a duplicity of meaning, most
unfortunate, because it has confounded two meanings, which it is of
the highest importance to preserve distinct.
We have already remarked the distinction between concrete, and
abstract, terms; and explained wherein the difference of their
signification consists. We have 27 also observed, that though in very
many cases, the concrete term, and the abstract term, are different
words, as good and goodness, true and truth, there are many others
copies of sensations, peculiarly combined, the complex ideas in
question are composed.
The simplest case of position, or synchronous order, is that of two
or more particles in one direction. Let us take the particle, conceived
as the centre particle, in a preceding supposition, and let us
aggregate to it a number of particles, all in the direction of a single
radius, one by one. We have first the centre particle, and one other, in
juxta-position. This is the simplest case of synchronous order, and this
is the simplest of all positions. Let us next aggregate a second
particle; we have now the centre particle, and two more. The position
of the first of the aggregated particles with respect to the centre
particle is contact, or juxta-position; that of the second is not juxta-
position, but position at the distance of a particle; the next which is
aggregated, is at the distance of two; the next of three particles, and
so on, to any extent.
Particles thus aggregated, all in the direction of a single radius from
the first, constitute a line of less or greater length, according to the
number of aggregated particles.
Line is a word of great importance; because it is by that, chiefly, we
express ourselves concerning synchronous order; or frame names for
positions. Now it happens, that Line has a duplicity of meaning, most
unfortunate, because it has confounded two meanings, which it is of
the highest importance to preserve distinct.
We have already remarked the distinction between concrete, and
abstract, terms; and explained wherein the difference of their
signification consists. We have 27 also observed, that though in very
many cases, the concrete term, and the abstract term, are different
words, as good and goodness, true and truth, there are many others
in which the concrete and abstract terms are the same; and this is the
case, unhappily, with the word Truth itself, which is used in the
concrete sense, as well as the abstract. Thus we call a proposition, a
‘Truth; in which phrase, the word Truth, means “True Proposition;” and
in this sense we talk of eternal truths, meaning, Propositions, always
true. “Property,” is another word, which is sometimes concrete,
sometimes abstract. Thus, a man calls his horse, his field, his house,
his property. In such phrases the word is concrete. He also says, he
has a property in such and such things. In these phrases, it is
abstract.
Of this ambiguity, the word Line is an instance. It is applied as well
to what we call a physical line, as to what we call a mathematical line.
In the first case, it is a concrete, or connotative term; in the second
case, it is an abstract or non-connotative term. Let us then conceive
clearly the two meanings. The purest idea of a physical line, is that
which we have already formed; the aggregate of particle after
particle, in the direction of a radius. When this aggregate of particles
in this order is called a line, the word, line, is connotative; it marks or
notes the direction, but it also marks or connotes the particles; it
means the particles and the direction both; it is, in short, the concrete
term. When it is used as the abstract term, the connotation is left out.
It marks the direction without marking the particles.
It is here necessary to call to mind, that abstract 28 terms derive
their meaning wholly from their concretes; and that by themselves
they have absolutely no meaning at all. I know a green tree, a sweet
apple, a hard stone, but greenness without something green,
hardness without something hard, are just nothing at all.
The same, in its abstract sense, is the case with line, though we
have not words by which we can convey the conception with equal
case, unhappily, with the word Truth itself, which is used in the
concrete sense, as well as the abstract. Thus we call a proposition, a
‘Truth; in which phrase, the word Truth, means “True Proposition;” and
in this sense we talk of eternal truths, meaning, Propositions, always
true. “Property,” is another word, which is sometimes concrete,
sometimes abstract. Thus, a man calls his horse, his field, his house,
his property. In such phrases the word is concrete. He also says, he
has a property in such and such things. In these phrases, it is
abstract.
Of this ambiguity, the word Line is an instance. It is applied as well
to what we call a physical line, as to what we call a mathematical line.
In the first case, it is a concrete, or connotative term; in the second
case, it is an abstract or non-connotative term. Let us then conceive
clearly the two meanings. The purest idea of a physical line, is that
which we have already formed; the aggregate of particle after
particle, in the direction of a radius. When this aggregate of particles
in this order is called a line, the word, line, is connotative; it marks or
notes the direction, but it also marks or connotes the particles; it
means the particles and the direction both; it is, in short, the concrete
term. When it is used as the abstract term, the connotation is left out.
It marks the direction without marking the particles.
It is here necessary to call to mind, that abstract 28 terms derive
their meaning wholly from their concretes; and that by themselves
they have absolutely no meaning at all. I know a green tree, a sweet
apple, a hard stone, but greenness without something green,
hardness without something hard, are just nothing at all.
The same, in its abstract sense, is the case with line, though we
have not words by which we can convey the conception with equal
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knowledge seekers. We believe that every book holds a new world,
offering opportunities for learning, discovery, and personal growth.
That's why we are dedicated to bringing you a diverse collection of
books, ranging from classic literature and specialized publications to
self-development guides and children's books.
More than just a book-buying platform, we strive to be a bridge
connecting you with timeless cultural and intellectual values. With an
elegant, user-friendly interface and a smart search system, you can
quickly find the books that best suit your interests. Additionally,
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