academic staff proposal pres PPT23rd.pptx

academic staff proposal

1. ACADEMIC STAFF INFORMATION COMMUNICATION TECHNOLOGY (ICT) COMPETENCE AND E-TEACHING IN KAMPALA INTERNATIONAL UNIVERSITY - WESTERN CAMPUS, UGANDA Supervisor: Dr. Tukur Muhammad Robiah Ajoke Abdulrahman AKINOLA (2020-01-00289)

2. Outline of the Presentations Introduction Objectives General Objectives Research Hypothesis Chapter Four Data Presentation, Analysis, And Interpretation Discussion Of Findings, Conclusions, And Recommendations

3. CHAPTER ONE Introduction At the higher education level, online learning is not new, but not all universities have implemented online learning yet. Therefore, this proposed study would focus on academic staff's Information, and Communication Technology (ICT) competence and e-teaching at Kampala International University Western Campus Uganda.

4. PROBLEM STATEMENT The technological era necessitates re-evaluating e-teaching methods to enhance traditional classroom education. The COVID-19 lockdown forced global educational institutions to adopt remote teaching, highlighting the crucial role of academic staff's ICT competence (Source?). This study examines the ICT proficiency of academic staff at Kampala International University (KIU-WC) in Uganda and its impact on online instruction.

5. Objectives of the study are divided into two, namely general and specific objectives. General Objectives This research work is intended to evaluate ICT competence among Academic staff of (KIU-WC) and e-teaching Specific Study Objectives To investigate the academic staff’s perception of ICT and E-teaching at KIU-WC Uganda. Objectives of the Study

6. 2. To find out academic staff ICT competence and E-teaching at KIU-WC Uganda. 3. To ascertain academic staff’s usage of ICT and E-teaching at KIU-WC Uganda. Null Hypothesis H 1 : There is no significant impact of Academic staff’s perception of ICT on E-teaching in KIU-WC. H 2 : There is no significant impact of academic staff's ICT competency rating on E-teaching in KIU-WC. H 3 : There is no significant impact of ICT use on E-teaching in KIU-WC . Objectives of the Study Count.

7. CONCEPTUAL FRAMEWORK Independent Variable Independent Variable Intervening Variables

8. Introduction This chapter presents the results about the background characteristics of the academic staff, as well as the dependent and independent variables. The chapter is presented in the following sub-headings: Demographic characteristics of the respondents, answering of research questions, the testing of the research hypothesis, and providing an overview of the outcomes. As a consequence, the outputs and outcomes are shown in the tables. DATA PRESENTATION, ANALYSIS, AND INTERPRETATION

9. Response Rate Initially, the researcher aimed to collect data from 150 academic staff members from the selected university for the questionnaire survey. However, complete data was ultimately collected from 90 academic staff members. DATA PRESENTATION, ANALYSIS, AND INTERPRETATION COUNT.

10. Demographic Characteristics of the Respondents (academic staff) This section provides information about the academic staff, including their gender, age, level of education, position held within the school, number of years worked at the university, and field of specialization. The data on these background characteristics is presented in Table 4.1. DATA PRESENTATION, ANALYSIS, AND INTERPRETATION COUNT.

11. Table 4.1: Academic Staff Demographic Characteristics Items Categories Frequency Percentage Gender Male 61 67.8   Female 29 32.2   Total 90 100.0 Age Group Below 30 years 7 7.8   30-40 years 46 51.6   40-50 years 29 32.2           50 years and above 8 8.9   Total 90 100.0 Highest level of Education Bachelor’s Degree 7 7.8   Master’s Degree 52 57.8   Doctorate Degree 31 34.4   Total 90 100.0 DATA PRESENTATION, ANALYSIS, AND INTERPRETATION COUNT.

12. Position in the University Teaching Assistant 7 7.8   Assistant Lecturer 52 57.8   Lecturer 23 25.6   Senior Lecturer 5 5.6   Associate Professor/Professor 3 3.3   Total 90 100.0 Number of years worked at the University Below 5 years 36 40   5 -10 years 45 50   11 years and above 9 10   Total 90 100.0 Field of Specialty Education 18 20.0   Biomedical 31 34.4   Engineering 9 10.0   DATA PRESENTATION, ANALYSIS, AND INTERPRETATION COUNT.

13. Field of Specialty Health Sciences 8 8.9   Information Technology 11 12.2     Pharmacy 13 14.4   Total 90 100 Items Categories Frequency Percentage DATA PRESENTATION, ANALYSIS, AND INTERPRETATION COUNT.

14. The analysis of the gender category revealed that the majority (67.8%) were male, while females comprised 32.2% of the sample. This indicates that a higher percentage and majority of the academic staff were male. However, views were representative across both gender groups, indicating adequate gender inclusion and balance within the university. Regarding the age groups of the academic staff, the results indicated that the majority fell within the age range of 30-40 years (51.6%), followed by 25.6% that were of years between 40-50 years, followed by 15.6% that were less than 30 years. DATA PRESENTATION, ANALYSIS, AND INTERPRETATION COUNT.

15. The presence of academic staff above 50 years (7.8%) indicates the institution's inclusivity in hiring experienced educators. Statistics on the highest educational level revealed that a greater proportion of the academic staff (57.8%) have a master’s degree, followed by 34.4% who have a Doctorate, and the percentage of responders with a bachelor's degree is just 7.8%. These results suggest that staff were from different levels of educational qualification. Therefore, the views were representative of staff from different levels of education. DATA PRESENTATION, ANALYSIS, AND INTERPRETATION COUNT.

16. Objective 1: To investigate the academic staff’s perception of ICT and E-teaching at KIU-WC Uganda. S/No Academic staff’s perception of ICT F (%) SD D U A SA Mean B1 I believe that ICT can significantly affect my professional development F (%) 0 (0) 0 (0) 4 (4.4) 30 (33.3) 56 (62.2) 4.57 B2 I believe that if using ICT in my class it would make my instruction more effective F (%) 0 (0) 0 (0) 3 (3.3) 35 (38.9) 52 (57.8) 4.54 B3 I believe that using proper ICT applications promotes students’ engagement F (%) 0 (0) 0 (0) 1 (1.1) 39 (43.3) 50 (55.6) 4.54 B4 ICT promotes students’ critical thinking F (%) 0 (0) 0 (0) 11 (12.2) 41 (45.6) 38 (42.2) 4.3 B5 ICT applications are impressive and can substantially contribute to student’s learning F (%) 1 (1.1) 0 (0) 3 (3.3) 39 (43.3) 47 (52.2) 4.46 B6 ICT enhances students’ performance and it has positive impact on academic staffs’ teaching skills F (%) 0 (0) 0 (0) 4 (4.4) 37 (41.1) 49 (54.4) 4.50 B7 ICT makes teaching and learning easier and reduces stress F (%) 0 (0) 0 (0) 1 (1.1) 29 (32.2) 60 (66.7) 4.65   GRAND MEAN             4.89   Remarks: good perception               Table 4.2: Frequencies, Percentages, and Means for Academic staff’s perception Considering the descriptive statistics as shown in table 4.2, respondents showed positive perception of ICT among academic staffs (mean = 4.89) using five-point Likert-type Scale. DATA PRESENTATION, ANALYSIS, AND INTERPRETATION COUNT.

17. Academic staff’s perception of ICT Descriptive Statistic Std. Error Mean 4.51 0.04 95% Confidence Interval for Mean Lower Bound 4.43   Upper Bound 4.59   5% Trimmed Mean 4.54   Median 4.57   Variance 0.14   Std. Deviation 0.38   Minimum 3.29   Maximum 5.00   Range 1.71   Interquartile Range 0.57   Skewness -0.80 0.25 Kurtosis 0.32 0.50 Table 4.3: Summary Statistics on Academic staff’s perception of ICT Figure 4.3: Histogram showing distribution for Academic staff perception of ICT This inference could be commemorated with the results generated from table 4.3, which showed Academic staff perception (ASP) of the use of ICT to enhance e-teaching, the summary statistics showed a mean value of 4.57, with negative skewness of -0.080. This infer a good ASP towards the use of ICT. Withal, the visual representation on ASP of ICT was also depicted using a histogram (figure 4.1) DATA PRESENTATION, ANALYSIS, AND INTERPRETATION COUNT.

18. Objective 2: To find out academic staff ICT competence and E-teaching at KIU-WC Uganda. S/No Competency ratings 2 F (%) Completely insufficient (1) Insufficient (2) Neutral (3) Sufficient (4) Completely Sufficient (4) Mean B2.1 Rate your ability to use word processing for your personal and professional needs F (%)   0 (0)   1 (1.1)   3 (3.3)   55 (61.1)   31 (34.4)   4.29 B2.2 Rate your ability to use spreadsheets (e.g. Excel) for your personal and professional needs F (%)   0 (0)   4 (4.4)   10 (11.1)   54 (60.0)   22 (24.4)   4.04 B2.3 Rate your ability to use the presentation software (e.g. PowerPoint) for your personal and professional needs F (%) 0 (0) 0 (0) 5 (5.6) 59 (65.6) 26 (28.9) 4.23 B2.4 Rate your ability to search information and material on the Internet for your personal and professional needs F (%)   0 (0)   0 (0)   0 (0)   43 (47.8)   47 (52.2)   4.52   GRAND MEAN             4.27 Using the descriptive analysis as shown in table 4.4., respondents showed that the ICT competency of academic staffs in KIU-WC is very high at mean outcome = 4.42 which is close to 4 corresponding to agree on a five-point Likert-type Scale. DATA PRESENTATION, ANALYSIS, AND INTERPRETATION COUNT.

19. This submission shows that academic staff ICT competency level is high. This assertion is further explained using summary statistics presented in table 4.6. Meanwhile, the visual presentation of the submission is depicted in figure 4.2. Table 4.6: Summary Statistics on Academic staff ICT competency ratings. Academic staff ICT competency ratings Descriptive Statistic Std. Error Mean 4.44 0.04 95% Confidence Interval for Mean Lower bound 4.37   Upper bound 4.52   5% Trimmed Mean 4.46   Median 4.40   Variance; 0.13   Std. Deviation 0.35   Minimum 3.60   Maximum 5.00   Range 1.40   Interquartile Range 0.60   Skewness -0.46 0.25 Kurtosis -0.41 0.50 Figure 4.2: Histogram and a normal curve showing the distribution of Academic Staff ICT Competency ratings

20. Objective 3: To ascertain academic staff’s usage of ICT and E-teaching at KIU-WC Uganda. Table 4.7: Frequencies, Percentages, and Means for ICT Use S/No Academic Staffict Use F (%) SD D U A SA Mean B3.1 I use ICT to communicate e.g. on email F (%) 0 (0) 0 (0) 5 (5.6) 44 (48.9) 41 (45.6) 4.40 B3.2 I use computers and the Internet to prepare and enhance my instruction F (%) 0 (0) 0 (0) 4 (4.4) 36 (38.9) 51 (56.7) 4.52 B3.3 The use of ICT has positively influenced my students and their performance F (%) 0 (0) 0 (0) 9 (10.0) 49 (54.4) 32 (35.6) 4.26 B3.4 I use ICT for knowledge management F (%) 0 (0) 1 (1.1) 4 (4.4) 42 (46.7) 43 (47.8) 4.41 B3.5 I use ICT to support the instruction and illustration process in the classroom F (%) 0 (0) 2 (2.2) 7 (7.8) 49 (54.4) 32 (35.6) 4.23 B3.6 There is sufficient computer and internet access to enhance my teaching and service delivery F (%) 1 (1.1) 6 (6.7) 22 (24.4) 40 (44.4) 21 (23.3) 3.82 B3.7 ICT Equipment training makes my use of ICT facilities easy for teaching F (%) 0 (0) 3 (3.3) 6 (6.7) 42 (46.7) 39 (43.3) 4.43 B3.8 There is ICT technical support at KIU F (%) 0 (0) 1 (1.1) 17 (18.9) 39 (43.3) 33 (36.7) 4.16 B3.9 I would like to receive training about the integration of ICT in my class F (%) 1 (1.1) 6 (6.7) 8 (8.9) 34 (37.8) 41 (45.6) 4.20 B3.10 During class, I make use of the projector to present slides or a particular software regarding my subject matter F (%)   1 (1.1)   1 (1.1) 1 (1.1) 32 (35.6)   55 (61.1)   4.54   GRAND MEAN               Using the descriptive analysis as shown in table 4.7., respondents showed that effective use of ICT by academic staffs in teaching and other professional activities at mean outcome = 4.30 which is close to 4 on a five-point Likert-type Scale. DATA PRESENTATION, ANALYSIS, AND INTERPRETATION COUNT.

21. Table 4.8: Summary Statistics on ICT Use Academic Staff ICT Use Descriptive Statistic Std. Error Mean 4.36 .044 95% Confidence Interval for Mean Lower Bound 4.27   Upper Bound 4.45   5% Trimmed Mean 4.37   Median 4.33   Variance .18   Std. Deviation .42   Minimum 3.00   Maximum 5.00   Range 2.00   Interquartile Range .67   Skewness -.32 .25 Kurtosis -.06 .50 Figure 4.3: Histogram showing the distribution of Academic Staff ICT Use This assertion is further explained using summary statistics presented in table 4.8. Meanwhile, the result deduced from the summary shows that respondents consistently reported the use of ICT, with minor variations and distribution that is slightly skewed to the left but close to normal. The visual presentation of the submission is depicted in figure 4.3. DATA PRESENTATION, ANALYSIS, AND INTERPRETATION COUNT.

22. Regression Analysis of Academic staff ICT Competence and E-Teaching Regression analysis is a statistical method used to examine the relationship between one dependent variable (often called the outcome or response variable) and one or more independent variables often called predictors or explanatory variables( Skiera , Reiner, Albers 2021) DATA PRESENTATION, ANALYSIS, AND INTERPRETATION COUNT.

23. DATA PRESENTATION, ANALYSIS, AND INTERPRETATION COUNT.

24. Variables**: - **API (Academic staff’s perception of ICT)**: Measures how academic staff perceive ICT. - **AIC (Academic staff’s ICT competency ratings)**: Assesses how competent academic staff are in using ICT. - **IU (ICT use)**: Measures the extent to which ICT is used by academic staff.   **Analysis**: **Multiple Linear Regression**: The dependent variable (ET - E-teaching) is regressed on the three independent variables (API, AIC, IU). DATA PRESENTATION, ANALYSIS, AND INTERPRETATION COUNT.

25. Results**: - **F(3,86) = 6.551, p < .001**: The F-statistic tests whether at least one of the regression coefficients (slopes) is significantly different from zero. The p-value (< .001) indicates that the model is statistically significant. This means that the independent variables collectively predict the dependent variable (ET). - **R² = 0.186**: The R² value, also known as the coefficient of determination, indicates the proportion of variance in the dependent variable that is explained by the independent variables. An R² of 0.186 means that 18.6% of the variability in e-teaching can be explained by academic staff’s perception of ICT, ICT competency ratings, and ICT use. While this indicates a modest amount of explained variance, it suggests that other factors not included in the model also play a significant role in e-teaching.  In summary, the analysis indicates that academic staff’s perception of ICT, ICT competency ratings, and ICT use collectively have a significant impact on e-teaching, but other factors not accounted for in the model also contribute to the variability in e-teaching effectiveness. DATA PRESENTATION, ANALYSIS, AND INTERPRETATION COUNT.

26. Introduction In this chapter, we discussed the findings of the study in the context of existing literature on Academic staff’s ICT competence and E-teaching in KIU-WC. Our results align with several published works that highlight the significance of various factors in shaping the outcomes of e-teaching DISCUSSION OF FINDINGS, CONCLUSIONS, AND RECOMMENDATIONS  

27. Research Objective One: To Investigate The Academic Staff’s Perception of ICT and E-teaching at KIU-WC Uganda . The findings revealed a significant positive relationship between academic staff's perception of ICT and e-teaching, consistent with previous studies. Abbasi et al. (2021) and Muchiri and Were (2016) found that academic staff generally have positive attitudes towards using technology, recognizing its potential to enhance education quality by making learning more interactive and engaging. DISCUSSION OF FINDINGS, CONCLUSIONS, AND RECOMMENDATIONS  

28. The study confirmed the hypothesis that academic staff’s perception of ICT significantly impacts e-teaching at KIU-WC. Bierne and Titko (2020) and Mishal Al-Shammari (2016) also highlighted the importance of infrastructure, training, and resources to maximize e-teaching effectiveness, while Heggart and Annakis (2018) emphasized that positive perceptions and confidence in ICT enhance its integration and effectiveness. DISCUSSION OF FINDINGS, CONCLUSIONS, AND RECOMMENDATIONS  

29. Research Objective Two: To find out Academic staff ICT Competence and E-Teaching at KIU-WC Uganda. The study revealed a significant correlation between academic staff's ICT competence and e-teaching effectiveness, aligning with previous research. Kimmons and Hall (2018) found that higher ICT proficiency among teachers correlates with increased use of student-centered teaching approaches and digital tools, enhancing engagement and learning outcomes. Fernández- Batanero et al. (2021) highlighted that many university teachers have low levels of digital competence, emphasizing the need for comprehensive training programs focused on both technological and pedagogical aspects of digital teaching. The study underscores the importance of ongoing professional development and institutional support to promote digital teaching competence. DISCUSSION OF FINDINGS, CONCLUSIONS, AND RECOMMENDATIONS  

30. Research Objective Three: To ascertain academic staff’s usage of ICT and E-teaching at KIU-WC Uganda. The findings indicate a significant correlation between academic staff’s usage of ICT and the effectiveness of e-teaching at KIU-WC Uganda, consistent with previous studies. Daramola (2023) found that lecturers in Nigerian colleges utilize ICT resources for teaching. Mugizi and Rwothumio (2023) noted that universities with better content management and integration capabilities successfully implement e-learning, though experimentation negatively impacted e-learning implementation. Rodríguez-Abitia and Bribiesca-Correa (2021) highlighted the positive impact of ICT usage by academic staff on teaching methodologies and student engagement, enhancing the learning experience through interactive instruction. DISCUSSION OF FINDINGS, CONCLUSIONS, AND RECOMMENDATIONS  

31. 1. Academic staff’s perceptions of ICT significantly impact their willingness and ability to integrate technology into their teaching. Positive perceptions lead to more effective e-teaching, while negative perceptions can hinder adoption. 2. Effective e-teaching requires a certain level of ICT competency. Higher competency ratings correlate with more innovative use of e-teaching tools, underscoring the need for continuous training and professional development. Conclusion

32. The study faced limitations including a lack of comparative analysis across different educational levels and geographical regions. Future research should explore student perceptions, the impact of emerging technologies like AI (Artificial Intelligence) and VR ( virtual reality) on e-teaching, and how these innovations can enhance educational practices. 3. The usage of ICT tools in e-teaching relies on both staff competency and perception. Competent staff with a positive view of ICT are more likely to use these tools effectively, enhancing student engagement and learning outcomes. Overcoming barriers like resource shortages and resistance to change is essential for successful ICT integration. Limitations and Suggestions for Further Research

33. To maximize e-teaching benefits, institutions should provide comprehensive training, ongoing support, and promote a positive attitude towards ICT, thereby improving the quality and effectiveness of education Recommendations

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