Volume 11, Issue 3 (12-2024)
Human Information Interaction 2024, 11(3): 113-130 |
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Bagheri N, Kian M, Gramipour M, Ali Azimi A, Mahdavi Nesab Y. Evaluation of the E-Learning System at Kharazmi University Based on the HELAM Conceptual Model. Human Information Interaction 2024; 11 (3)
URL: http://hii.khu.ac.ir/article-1-3170-en.html
URL: http://hii.khu.ac.ir/article-1-3170-en.html
Faculty of Psychology and Educational Sciences, Kharazmi University, Tehran, Iran
Abstract: (3928 Views)
Objective: Virtual classes, virtual schools, smart schools, and virtual universities, and generally, electronic learning, are considered reliable capacities and capabilities for developing academic skills. The aim of this study is to evaluate the e-learning program at Kharazmi University using the HELAM conceptual model.
Method: This research is practical in terms of its objective and descriptive-survey in terms of method. A quantitative approach was used to collect data. The statistical population consisted of postgraduate students at Kharazmi University. The sample size was 536 postgraduate students, and stratified random sampling was used. A standardized researcher-made questionnaire was used for data collection. The main structure of the questionnaire is based on the HELAM model, along with an additional “overall satisfaction” factor, which was adapted and translated using specialized literature and relevant research. For data analysis, various statistical tests including one-sample t-test and one-way ANOVA in SPSS, and confirmatory factor analysis in R software were used.
Findings: The results indicated that the status of Kharazmi University’s e-learning program, evaluated using the HELAM conceptual model and its seven aspects (student attitude, instructor attitude, system quality, content quality, service quality, support issues, and overall satisfaction), is significantly above the community average with over 99% confidence. Moreover, the support issues aspect showed a significant difference compared to other dimensions, followed by content quality and service quality, which are close to each other and separated from other sub-scales, while system quality, instructor attitude, overall satisfaction, and student attitude have the lowest mean rankings.
Conclusion: Managers and experts at the Information and Communication Technology Center of Kharazmi University should take measures to improve system quality, instructor attitude, overall satisfaction, and student attitude aspects to enhance their performance in parallel with support issues.
Method: This research is practical in terms of its objective and descriptive-survey in terms of method. A quantitative approach was used to collect data. The statistical population consisted of postgraduate students at Kharazmi University. The sample size was 536 postgraduate students, and stratified random sampling was used. A standardized researcher-made questionnaire was used for data collection. The main structure of the questionnaire is based on the HELAM model, along with an additional “overall satisfaction” factor, which was adapted and translated using specialized literature and relevant research. For data analysis, various statistical tests including one-sample t-test and one-way ANOVA in SPSS, and confirmatory factor analysis in R software were used.
Findings: The results indicated that the status of Kharazmi University’s e-learning program, evaluated using the HELAM conceptual model and its seven aspects (student attitude, instructor attitude, system quality, content quality, service quality, support issues, and overall satisfaction), is significantly above the community average with over 99% confidence. Moreover, the support issues aspect showed a significant difference compared to other dimensions, followed by content quality and service quality, which are close to each other and separated from other sub-scales, while system quality, instructor attitude, overall satisfaction, and student attitude have the lowest mean rankings.
Conclusion: Managers and experts at the Information and Communication Technology Center of Kharazmi University should take measures to improve system quality, instructor attitude, overall satisfaction, and student attitude aspects to enhance their performance in parallel with support issues.
Keywords: Evaluation, E-learning, Kharazmi University, Quantitative research, HELAM conceptual model
Type of Study: Applicable |
Subject:
Special
References
1. Alhabeeb, A., & Rowley, J. (2018). E-learning critical success factors: Comparing perspectives from academic staff and students. Computers & Education, 127, 1-12. [DOI:10.1016/j.compedu.2018.08.007]
2. Altbach, P. G. (2016). Global perspectives on higher education (p. 303). Baltimore: Johns Hopkins University Press. [DOI:10.56021/9781421419268]
3. Anarinejad, A, & Mohammadi, M. (2014). The practical indicators for evaluation of e-learning in higher education in Iran. Interdisciplinary journal of virtual learning in medical sciences (IJVLMS), 5(1), 11-25. SID. https://sid.ir/paper/249931/en
4. Conn, S. R., Roberts, R. L., & Powell, B. M. (2009). Attitudes and satisfaction with a hybrid model of counseling supervision. Journal of Educational Technology & Society, 12(2), 298-306.
5. DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of management information systems, 19(4), 9-30. [DOI:10.1080/07421222.2003.11045748]
6. Diwakar, S., Radhamani, R., Sujatha, G., Sasidharakurup, H., Shekhar, A., Achuthan, K., ... & Nair, B. (2019). Usage and diffusion of biotechnology virtual labs for enhancing university education in India's urban and rural areas. In Virtual reality in education: breakthroughs in research and practice (pp. 433-453). IGI Global. [DOI:10.4018/978-1-5225-8179-6.ch022]
7. Emmert-Streib, F., & Dehmer, M. (2019). Evaluation of regression models: Model assessment, model selection and generalization error. Machine learning and knowledge extraction, 1(1), 521-551. [DOI:10.3390/make1010032]
8. Geramipour, Masoud. (2014). Theoretical Principle and Application of Measurement Theories in Behavioral Sciences. Tehran: Tamaddone elmi.
9. Kakaee, F., & Hakimzadeh, R. (2016). Evaluation of the quality of the e-learning program of the master's course in information technology engineering at Shiraz University. Information and communication technology quarterly in educational sciences. Information and communication technology quarterly in educational sciences 6, (3(Successive 23)), 110-85.
10. Kian, M., & Riahy nia, N.(2013). The use of the Internet in teaching-learning activities. media magazine,24(3).
11. Kian, M. .(2015). Examining the role and use of virtual social networks for students, Education and Learning Technology Quarterly, 1(3)
12. Khadivi, A., & Vaziri, A. (2015). Designing and compiling a model for evaluating the effectiveness and performance of faculty members of Islamic Azad Universities in East Azerbaijan province. Productivity management 9, (3(34) Fall), 174-161.
13. Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and psychological measurement, 30(3), 607-610. [DOI:10.1177/001316447003000308]
14. Mahmoudi, M., & Mostashiri, E. (2015). Analysis of the practical indicators of e-learning evaluation in Iran's higher education (case study: virtual faculty of the Holy Quran University of Sciences and Education). Higher education letter, 9(35), 77-96.
15. Muthuraman, S. (2018). Quality of blended learning education in higher education. The Online Journal of Distance Education and e-Learning, 6(4), 48.
16. Narenji Thani, F., POURKARIMI, J., & HEJAZI, S.. (2021). Identifying the components of e-learning system at University of Tehran. Journal of technology of education (Journal of technology and education), 15(2 (58) ), 321-337. SID. https://sid.ir/paper/402379/en [DOI:10.52547/mpes.15.2.255]
17. Ozkan, S., & Koseler, R. (2009). Multi-dimensional students' evaluation of e-learning systems in the higher education context: An empirical investigation. Computers & Education, 53(4), 1285-1296. [DOI:10.1016/j.compedu.2009.06.011]
18. Prihartini, N., Soemitro, H. L., & Hendradjaya, B. (2016, October). Identifying aspects of web e-learning in LMS-based for requirement engineering process modeling. In 2016 International Conference on Data and Software Engineering (ICoDSE) (pp. 1-6). IEEE. [DOI:10.1109/ICODSE.2016.7936134]
19. Pritalia, G. L., Budiyanto, S. D., Dewi, L. T., & Kusrohmaniah, S. (2018). Critical factor of e-learning component using HELAM and AHP. In MATEC Web of Conferences (Vol. 218, p. 03020). EDP Sciences. [DOI:10.1051/matecconf/201821803020]
20. Rastegarpour, H., & Gorjizadeh, S. (2012). Evaluation of the effectiveness of e-learning courses in Tarbiat Modares university from the users' perspectives. Information and communication technology in educational sciences, 2(3 (7)), 5-30. SID. https://sid.ir/paper/175366/en
21. Rezaee, A, & Zahedi, M. (2018). The role of modern technologies in the development of e-learning (looking at the opportunities and challenges facing universities and higher education institutions). Journal of research in education systems, 12(40 ), 207-224. SID. https://sid.ir/paper/137615/en
22. Ryan, S., Scott, B., Freeman, H., & Patel, D. (2013). The virtual university: The internet and resource-based learning. Routledge. [DOI:10.4324/9781315042022]
23. Saadipour, E. (2014). Research methods in psychology and educational sciences. Tehran: Dowran.
24. Salarzehi, H., Amiri, Y., & Ramezani, A. (2012). Identifying and ranking the success measurement components of e-learning systems of universities with the approach of fuzzy network analysis. Interdisciplinary Journal of Virtual Learning in Medical Sciences, 3 (4(Successive 11)), 44.
25. Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1993). The nature and determinants of customer expectations of service. Journal of the academy of Marketing Science, 21, 1-12. [DOI:10.1177/0092070393211001]
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