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1. FINAL DEFENSE Technology Research SEPTEMBER 2 2024

2. DEVELOPING FEXAMASTIC: FACULTY EXAMINATION AUTOMATED SCANNING TECHNOLOGY WITH INTEGRATED CAPTURE IN THE BASD DEPARTMENT Researchers Conejar , Arlie Jr. M. Khe, Shan Erik Q. Lava, Angelo P. Mota, Ebander P. Palco , Leonard A. Sedayon, Edriel Avid S. Advisers Prof. Randolf A. Colegio Prof. Patrick Justin L. Ariado

3. Introduction The present manual checking procedure used in educational institutions takes a lot of time, is prone to mistakes, and frequently causes delays in giving students feedback. Checking homework, exams, and papers takes up a lot of teachers' time, and better spent on giving instruction and teaching students (Ault, H. K., & Fraser, A., 2013).

4. Background of the study Malouff & Thorsteinsson (2016) highlight concerns about the manual checking procedure, including time consumption, inconsistent mistakes, unintentional errors, and the potential for subjective grading. Excessive focus on administrative tasks rather than engaging with students could affect fellow teachers' job satisfaction, as noted by Baber (2022) The idea is to introduce and create an innovative scanning prototype that automates the checking process for objective assessments like multiple-choice exams. To free up teachers to concentrate on other important areas of teaching, such individualized instruction and activities, the scanning prototype should be made to reduce errors, provide students with more accurate and immediate feedback, and to eliminate mistakes.

5. Statement of the problem Koster (2017) highlights the drawbacks of manual exam grading, emphasizing its time-consuming nature, potential for subjective grading, and limitations in providing prompt feedback. This underscores the urgent need for automated solutions to improve efficiency and assessment quality in education.

6. General objectives: This study aims to create an innovation of a scanning prototype to test the effectiveness of FEXAMASTIC: Faculty Examination Automated Scanning Technology with Integrated Capture in the BASD department. specific objectives This study envisions to answer the following objectives. Determine the demographic profile of the faculty based on their: 1. Age 2. Subject Taught 3. Type of Checking Examinations 4. Years in Teaching

7. General objectives: This study aims to create an innovation of a scanning prototype to test the effectiveness of FEXAMASTIC: Faculty Examination Automated Scanning Technology with Integrated Capture in the BASD department. specific objectives This study envisions to answer the following objectives. Determine the effectiveness of FEXAMASTIC based on the response of the BASD faculty in terms of: 1. Functionality 5. Safety and Security 2. User-Friendly 6. Practicality 3. Accuracy 7. Accessibility 4. Efficiency 8. Reliability

8. Theoretical framework Diffusion of Innovations Theory Everett Rogers’ (1962) Diffusion of Innovations Theory explains the gradual spread of new technologies, such as FEXAMASTIC, within a society, helping teachers understand factors influencing the acceptance of automated scanning exams and promoting the adoption of efficient technologies for improved results in educational institutions. Technology Acceptance Model (TAM) Fred Davis (1989) introduced the Technology Acceptance Model (TAM) as a systems theory explaining how people adopt technology, focusing on perceived usefulness and ease of use. Applying TAM, FEXAMASTIC research explores how educators perceive and adopt this technology based on its usefulness and ease of use.

9. conceptual framework

10. Significance of the study The findings of this study will be beneficial to the faculty of the BASD department with the concept of scanning applications ( Zipgrade , EvalBee , etc.) with a hardware. By improving speed and accuracy, lowering administrative load, and giving teachers timely and data-driven insights. The study of FEXAMASTIC in a university context has the potential to revolutionize examination operations.

11. SCOPE AND LIMITATIONS This study aims to modernize the process of checking test papers by introducing an automated examination scanning prototype for the Basic Arts and Sciences Department at Technological University of the Philippines-Taguig. The goal is to reduce faculty workload, speed up grading, provide prompt feedback to students, and improve data analysis, thereby supporting the university’s commitment to academic excellence and administrative efficiency. The system also allows students to view their exam scores directly.

12. Chapter II Review of related Literature and studies Ningsih & Mulyono (2019) found that 18 primary school teachers using Kahoot and ZipGrade as digital assessment tools preferred them for making learning enjoyable, being user-friendly, and offering quick feedback. Despite difficulties integrating them into the school system, the overall impact on student engagement and performance was highly positive.

13. Chapter II Review of related Literature and studies Wagstaff (2019) states that modern phones, equipped with advanced technology, can recognize handwriting and learn. Despite this, many teachers still manually grade tests using outdated tools. An efficient solution involves using an app that employs deep learning to analyze test images, assign grades, and track test-takers, saving time and simplifying the grading process.

14. Chapter II Review of related Literature and studies Silao & Luciano (2021) developed an OMR system, called EvalBee , which is a mobile app enabling teachers to efficiently scan and assess answer sheets using phones or tablets, streamlining the grading process. Another article highlights the versatility of OMR systems for multiple-choice exams, replacing manual marking with speedy data collection through scanners or exam reader applications.

15. Chapter II Review of related Literature and studies Sahri (2022) study explores diverse edge detection algorithms for Optical Mark Reading (OMR) sheets, commonly used for multiple-choice answers. It assesses Sobel, Roberts, Prewitt, Canny, and Laplacian of Gaussian ( LoG ) algorithms, finding LoG most effective and Sobel least effective, with Prewitt and Canny performing similarly and Roberts ranking just above Sobel in effectiveness.

16. Chapter II Review of related Literature and studies Cortez (2023) suggests that teachers, facing increased workload due to pandemic challenges, aim to streamline the assessment process by considering ZipGrade , a phone app for efficient grading. The decision will be based on data analysis of a survey gauging the program's effectiveness in reducing manual grading and paperwork.

17. Chapter II Review of related Literature and studies Ware (2019) found that employing OMR sheets for assessing learners' total marks, particularly through an online platform, enhances user-friendliness for both students and teachers, providing instant feedback on assessments. Loke (2018) utilized SOMR, a specialized software, to convert survey data into computer-readable text, emphasizing the importance of thorough field completion and the use of soft pencils, while acknowledging occasional errors due to printing or scanning issues.

18. Chapter III Research methodology Research Design This study employed a quantitative descriptive research design, utilizing methods like surveys and questionnaires to gather demographic information and assess preferences on factors like functionality, user-friendliness, accuracy, efficiency, safety, security, practicality, accessibility, and reliability. This approach aims to identify trends, attitudes, opinions, and behaviors within a population.

19. Chapter III Research methodology Population and Sample of the Study The respondents of the study will be coming from the BASD Faculty members of the Technological University of the Philippines-Taguig. Random sampling is used to ensure that every respondent in the BASD Department has an equal chance of being included in the sample to prevent biases in the data gathering. We will be choosing 15 BASD Faculty members to evaluate the prototype. Respondents No. of Respondents BASD Faculty Members 15 Total: 15

20. Chapter III Research methodology Research Instrument A modified questionnaire, derived from a previous study, was employed in this research. The questionnaire underwent validation by a thesis adviser to eliminate biases and ensure its relevance. It includes a Likert scale with 7 items (strongly agree, agree, somewhat agree, neutral, somewhat disagree, disagree, strongly disagree) , allowing respondents to indicate their agreement level with statements related to the study variable.

21. Chapter III Research methodology Method of Study Verification Phase During verification, researchers will collect necessary specifications to understand the prototype's design and functionality, utilizing a single hardware, the scanner, and a dedicated system for storing and viewing examination results. Coding Phase During the coding phase, researchers will create two codes: one for the hardware's integrated capture and another for the database system storing examination information.

22. Chapter III Research methodology Method of Study Validation Phase During the validation phase, researchers will initially test the prototype and system for compatibility issues and bugs before obtaining feedback from selected respondents. If there are no major issues, the researchers will then evaluate the prototype and system based on respondent feedback.

23. Chapter III Research methodology Data Gathering Procedure The following are the steps of gathering data: 1. Validate the questionnaire to a thesis adviser to avoid biases and irrelevance. 2. Determine the respondents. 3. Determine the target population. 4. Determine the sample size. 5. Identify who will be testing the prototype. 6. Give the questionnaires to the respondents. 7. Test out the prototype to the respondents. 8. Collect data. 9. Interpret data. 10. Gather and Interpret the result.

24. Chapter III Research methodology Statistical Treatment of Data This will be the formula used in determining the mean score of the different variables: • x̄ = sample mean • ∑ xn = sum of each value in the sample • n = number of values in the population

25. Chapter IV PRESENTATION, ANALYSIS AND INTERPRETATION OF DATA Demographic Profile of the Respondents According to the figure above most of our respondents are faculty teachers.

26. Chapter IV PRESENTATION, ANALYSIS AND INTERPRETATION OF DATA Demographic Profile of the Respondents According to the figure above most of the respondents age are 26-30.

27. Chapter IV PRESENTATION, ANALYSIS AND INTERPRETATION OF DATA Demographic Profile of the Respondents According to the figure above most of our respondents taught GEC Subjects.

28. Chapter IV PRESENTATION, ANALYSIS AND INTERPRETATION OF DATA Demographic Profile of the Respondents According to the figure above most of our respondents do manual checking.

29. Chapter IV PRESENTATION, ANALYSIS AND INTERPRETATION OF DATA Demographic Profile of the Respondents According to the figure above most of our respondents are 1-5 years of teaching.

30. Chapter IV PRESENTATION, ANALYSIS AND INTERPRETATION OF DATA Demographic Profile of the Respondents According to the figure above most of our respondents have 1-5 years of experience in the industry.

31. Chapter IV PRESENTATION, ANALYSIS AND INTERPRETATION OF DATA

32. Chapter V Summary of findings, conclusions and recommendations Summary of Findings The research shows that the prototype is effective in several areas but with varying degrees. It scores highest in functionality (6.0), indicating it meets most intended functions. Practicality is slightly lower at 5.99, suggesting usefulness with some limitations. Efficiency stands at 5.91, reflecting timely performance but room for optimization. Reliability is rated at 5.50, showing occasional inconsistencies. It is somewhat user-friendly (5.40) but could be more intuitive. Safety and security score 5.32, indicating satisfactory protection with room for improvement. Accessibility is at 5.30, suggesting broad availability but potential for more inclusivity. Accuracy is the lowest at 4.94, pointing to adequate performance but significant room for improvement.

33. Chapter V Summary of findings, conclusions and recommendations Conclusion Based on the findings of the study the prototype exhibits a generally effective performance in its fundamental functionality, accomplishing most of its intended functions, as per the study's conclusions. Still, there are several areas where performance and user experience may be improved. In conclusion, even though the prototype has good functionality and is generally useful, there is room for development in these areas, which might greatly increase the prototype’s efficiency, user satisfaction, and overall value.

34. Chapter V Summary of findings, conclusions and recommendations Recommendations: Based on the results and conclusions drawn from this study, there are several recommendations can be used to further enhance the prototype: Higher Raspberry Pi 4 Model-B System Unit Laser Bed Short Time Frame Customizable Exam High End Stabilized Camera

35. THANK YOU!