References
Al-Azawei, A., Parslow, P., & Lundqvist, K. (2016). Investigating the effect of learning styles in a blended E-learning system: An extension of the technology acceptance model (TAM). Australasian Journal of Educational Technology. https://doi.org/10.14742/ajet.2741
Al-Fraihat, D., Joy, M., Masa’deh, R., et al. (2020). Evaluating E-learning systems success: An empirical study. Computers in Human Behavior, 102, 67–86. https://doi.org/10.1016/j.chb.2019.08.004
Alghabban, W. G., & Hendley, R. (2022). Perceived Level of Usability as an Evaluation Metric in Adaptive E-learning. SN Computer Science, 3(3). https://doi.org/10.1007/s42979-022-01138-5
Ali, W. G. M. (2012). Factors affecting nursing student’s satisfaction with E-learning experience in King Khalid University. Saudi Arabia. Dimension, 5, 13-18.
Aljaraideh, Y., & Al Bataineh, K. (2019). Jordanian Students’ Barriers of Utilizing Online Learning: A Survey Study. International Education Studies, 12(5), 99. https://doi.org/10.5539/ies.v12n5p99
Al‐Maskari, A., & Sanderson, M. (2010). A review of factors influencing user satisfaction in information retrieval. Journal of the American Society for Information Science and Technology, 61(5), 859–868. Portico. https://doi.org/10.1002/asi.21300
Almusharraf, N., & Khahro, S. (2020). Students Satisfaction with Online Learning Experiences during the COVID-19 Pandemic. International Journal of Emerging Technologies in Learning (IJET), 15(21), 246. https://doi.org/10.3991/ijet.v15i21.15647
Alqahtani, M. A., Alamri, M. M., Sayaf, A. M., et al. (2022). Exploring student satisfaction and acceptance of E-learning technologies in Saudi higher education. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.939336
Al-Rahmi, A. M., Shamsuddin, A., Alturki, U., et al. (2021). The Influence of Information System Success and Technology Acceptance Model on Social Media Factors in Education. Sustainability, 13(14), 7770. https://doi.org/10.3390/su13147770
Baherimoghadam, T., Hamedani, S., mehrabi, M., et al. (2021). The effect of learning style and general self-efficacy on satisfaction of e-Learning in dental students. BMC Medical Education, 21(1). https://doi.org/10.1186/s12909-021-02903-5
Benabbes, K., Housni, K., Hmedna, B., et al. (2023). A New Hybrid Approach to Detect and Track Learner’s Engagement in e-Learning. IEEE Access, 11, 70912–70929. https://doi.org/10.1109/access.2023.3293827
Bhuasiri, W., Xaymoungkhoun, O., Zo, H., et al. (2012). Critical success factors for E-learning in developing countries: A comparative analysis between ICT experts and faculty. Computers & Education, 58(2), 843–855. https://doi.org/10.1016/j.compedu.2011.10.010
Cazan, A.-M., Cocoradă, E., & Maican, C. I. (2016). Computer anxiety and attitudes towards the computer and the internet with Romanian high-school and university students. Computers in Human Behavior, 55, 258–267. https://doi.org/10.1016/j.chb.2015.09.001
Chang, C.-S., Liu, E. Z.-F., Sung, H.-Y., et al. (2013). Effects of online college student’s Internet self-efficacy on learning motivation and performance. Innovations in Education and Teaching International, 51(4), 366–377. https://doi.org/10.1080/14703297.2013.771429
Chen, L.-H., & Kuo, Y.-F. (2011). Understanding E-learning service quality of a commercial bank by using Kano’s model. Total Quality Management & Business Excellence, 22(1), 99–116. https://doi.org/10.1080/14783363.2010.532345
Chen, W. S., & Tat Yao, A. Y. (2016). An Empirical Evaluation of Critical Factors Influencing Learner Satisfaction in Blended Learning: A Pilot Study. Universal Journal of Educational Research, 4(7), 1667–1671. https://doi.org/10.13189/ujer.2016.040719
Christensen, J. M. (2021). Student Preferences and Decisions for Online or In-Person Class Sessions in Blended Learning [PhD thesis]. Brigham Young University.
Chuang, S.-C., Lin, F.-M., & Tsai, C.-C. (2015). An exploration of the relationship between Internet self-efficacy and sources of Internet self-efficacy among Taiwanese university students. Computers in Human Behavior, 48, 147–155. https://doi.org/10.1016/j.chb.2015.01.044
Clemes, M. D., Gan, C. E. C., & Kao, T.-H. (2008). University Student Satisfaction: An Empirical Analysis. Journal of Marketing for Higher Education, 17(2), 292–325. https://doi.org/10.1080/08841240801912831
Closson, R. B., & Stokes, C. (n.d.). Increasing Adult Learner Engagement in E-learning Courses through Learner Case Writing. Encyclopedia of Information Communication Technologies and Adult Education Integration, 971–984. https://doi.org/10.4018/978-1-61692-906-0.ch059
Cocea, M., & Weibelzahl, S. (2009). Log file analysis for disengagement detection in e-Learning environments. User Modeling and User-Adapted Interaction, 19(4), 341–385. https://doi.org/10.1007/s11257-009-9065-5
Engelbrecht, E. (2005). Adapting to changing expectations: Post-graduate students’ experience of an E-learning tax program. Computers & Education, 45(2), 217–229. https://doi.org/10.1016/j.compedu.2004.08.001
Eze, S. C., Chinedu-Eze, V. C. A., Okike, C. K., et al. (2020). Factors influencing the use of E-learning facilities by students in a private Higher Education Institution (HEI) in a developing economy. Humanities and Social Sciences Communications, 7(1). https://doi.org/10.1057/s41599-020-00624-6
Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School Engagement: Potential of the Concept, State of the Evidence. Review of Educational Research, 74(1), 59–109. https://doi.org/10.3102/00346543074001059
Gantasala, V. P., Gantasala, S. B., Al Tawil, T. N., et al. (2021). Quality of learning experience, student satisfaction and perceived overall experience in the COVID-19 context. Journal of Applied Research in Higher Education, 14(1), 507–520. https://doi.org/10.1108/jarhe-12-2020-0440
Gardner, J., & Brooks, C. (2018). Student success prediction in MOOCs. User Modeling and User-Adapted Interaction, 28(2), 127–203. https://doi.org/10.1007/s11257-018-9203-z
Gašević, D., Dawson, S., Rogers, T., et al. (2016). Learning analytics should not promote one size fits all: The effects of instructional conditions in predicting academic success. The Internet and Higher Education, 28, 68–84. https://doi.org/10.1016/j.iheduc.2015.10.002
Gupta, V., & Jain, N. (2017). Harnessing information and communication technologies for effective knowledge creation. Journal of Enterprise Information Management, 30(5), 831–855. https://doi.org/10.1108/jeim-10-2016-0173
Halverson, L. R., & Graham, C. R. (2019). Learner Engagement in Blended Learning Environments: A Conceptual Framework. Online Learning, 23(2). https://doi.org/10.24059/olj.v23i2.1481
Hoi, V. N., & Le Hang, H. (2021). The structure of student engagement in online learning: A bi‐factor exploratory structural equation modelling approach. Journal of Computer Assisted Learning, 37(4), 1141–1153. Portico. https://doi.org/10.1111/jcal.12551
Hollenbeck, C. R., Zinkhan, G. M., & French, W. (2005). Distance Learning Trends and Benchmarks: Lessons from an Online MBA Program. Marketing Education Review, 15(2), 39–52. https://doi.org/10.1080/10528008.2005.11488904
Hong, J.-C., Lee, Y.-F., & Ye, J.-H. (2021). Procrastination predicts online self-regulated learning and online learning ineffectiveness during the coronavirus lockdown. Personality and Individual Differences, 174, 110673. https://doi.org/10.1016/j.paid.2021.110673
Hu, P. J.-H., & Hui, W. (2012). Examining the role of learning engagement in technology-mediated learning and its effects on learning effectiveness and satisfaction. Decision Support Systems, 53(4), 782–792. https://doi.org/10.1016/j.dss.2012.05.014
Jafari Navimipour, N., & Zareie, B. (2015). A model for assessing the impact of E-learning systems on employees’ satisfaction. Computers in Human Behavior, 53, 475–485. https://doi.org/10.1016/j.chb.2015.07.026
Kember, D., & Ginns, P. (2012). Evaluating teaching and learning: A practical handbook for colleges, universities and the scholarship of teaching. Routledge, 66, 375-377. https:/doi.org/10.1007/s10734- 012-9557-9. https://doi.org/10.1007/s10734-012-9557-9
Kew, S. N., & Tasir, Z. (2021). Learning Analytics in Online Learning Environment: A Systematic Review on the Focuses and the Types of Student-Related Analytics Data. Technology, Knowledge and Learning, 27(2), 405–427. https://doi.org/10.1007/s10758-021-09541-2
Kılıç-Çakmak, E., Karataş, S., & Ocak, M. (2009). An analysis of factors affecting community college students' expecta-tions on E-learning. Quarterly Review of Distance Education, 10(4), 351-361.
Kizilcec, R. F., Pérez-Sanagustín, M., & Maldonado, J. J. (2017). Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses. Computers & Education, 104, 18–33. https://doi.org/10.1016/j.compedu.2016.10.001
Krithika L.B, & Lakshmi Priya GG. (2016). Student Emotion Recognition System (SERS) for E-learning Improvement Based on Learner Concentration Metric. Procedia Computer Science, 85, 767–776. https://doi.org/10.1016/j.procs.2016.05.264
Kumar, K. L., & Owston, R. (2016). Evaluating E-learning accessibility by automated and student-centered methods. Educational Technology Research and Development, 64(2), 263–283. https://doi.org/10.1007/s11423-015-9413-6
Kumar, P., Saxena, C., & Baber, H. (2021). Learner-content interaction in E-learning- the moderating role of perceived harm of COVID-19 in assessing the satisfaction of learners. Smart Learning Environments, 8(1). https://doi.org/10.1186/s40561-021-00149-8
Kumar, R. (2022). E-learning programs in executive education: effects of perceived quality and perceived value on self-regulation and motivation. Higher Education, Skills and Work-Based Learning, 12(6), 1025–1039. https://doi.org/10.1108/heswbl-07-2022-0149
Lee, B. C., Yoon, J. O., and Lee, I. (2009). Learners’ acceptance of E-learning in South Korea: Theories and results. Comput. Educ. 53, 1320-1329. https://doi.org/10.1016/j.compedu.2009.06.014
Lee, J.-W. (2010). Online support service quality, online learning acceptance, and student satisfaction. The Internet and Higher Education, 13(4), 277–283. https://doi.org/10.1016/j.iheduc.2010.08.002
Liaw, S.-S., & Huang, H.-M. (2013). Perceived satisfaction, perceived usefulness and interactive learning environments as predictors to self-regulation in E-learning environments. Computers & Education, 60(1), 14–24. https://doi.org/10.1016/j.compedu.2012.07.015
Martin, F., & Bolliger, D. U. (2018). Engagement Matters: Student Perceptions on the Importance of Engagement Strategies in the Online Learning Environment. Online Learning, 22(1). https://doi.org/10.24059/olj.v22i1.1092
Matthew, U. O., Kazaure, J. S., & Okafor, N. U. (2021). Contemporary development in E-learning education, cloud compu-ting technology & internet of things. EAI Endorsed Transactions on Cloud Systems, 7(20), e3-e3.
Mota, F. P. B., & Cilento, I. (2020). Competence for internet use: Integrating knowledge, skills, and attitudes. Computers and Education Open, 1, 100015. https://doi.org/10.1016/j.caeo.2020.100015
Namoun, A., & Alshanqiti, A. (2020). Predicting Student Performance Using Data Mining and Learning Analytics Techniques: A Systematic Literature Review. Applied Sciences, 11(1), 237. https://doi.org/10.3390/app11010237
Orvis, K. A., Fisher, S. L., & Wasserman, M. E. (2009). Power to the people: Using learner control to improve trainee reactions and learning in web-based instructional environments. Journal of Applied Psychology, 94(4), 960–971. https://doi.org/10.1037/a0014977
Panigrahi, R., Srivastava, P. R., & Panigrahi, P. K. (2020). Effectiveness of E-learning: the mediating role of student engagement on perceived learning effectiveness. Information Technology & People, 34(7), 1840–1862. https://doi.org/10.1108/itp-07-2019-0380
Ruthotto, I., Kreth, Q., Stevens, J., et al. (2020). Lurking and participation in the virtual classroom: The effects of gender, race, and age among graduate students in computer science. Computers & Education, 151, 103854. https://doi.org/10.1016/j.compedu.2020.103854
Safsouf, Y., Mansouri, K., & Poirier, F. (2020). An Analysis to Understand the Online Learners’ Success in Public Higher Education in Morocco. Journal of Information Technology Education: Research, 19, 087–112. https://doi.org/10.28945/4518
Sampson, P., Leonard, J., Ballenger, J., & Coleman, J. (2010). Student satisfaction of online courses for educational leader-ship. Available online: https://eric.ed.gov/?id=EJ914153 (accessed on 2 September 2023).
Sun, P.-C., Tsai, R. J., Finger, G., et al. (2008). What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & Education, 50(4), 1183–1202. https://doi.org/10.1016/j.compedu.2006.11.007
Tarhini, A., Hone, K., & Liu, X. (2014). The effects of individual differences on E-learning users’ behaviour in developing countries: A structural equation model. Computers in Human Behavior, 41, 153–163. https://doi.org/10.1016/j.chb.2014.09.020
Taylor, P. S. (2007). Can clickers cure crowded classes? Maclean’s, 120(26,27), 73.
Thandevaraj, E. J., Gani, N. A. N., & Nasir, M. K. M. (2021). A Review of Psychological Impact on Students Online Learning during Covid-19 in Malaysia. Creative Education, 12(06), 1296–1306. https://doi.org/10.4236/ce.2021.126097
Wisloski, J. (2011). Online education study: As enrollment rises, institutions see online education as a ‘critical part’ of growth, Online Education Information. Available online: https://www.geteducated.com/latest-onlinE-learning-news-and-research/461-online-education-study-increasing-enrollment (accessed on 2 June 2023).
Wixom, B. H., & Todd, P. A. (2005). A Theoretical Integration of User Satisfaction and Technology Acceptance. Information Systems Research, 16(1), 85–102. https://doi.org/10.1287/isre.1050.0042
Yeh, Y.C, & Chu, L.-H. (2018). The mediating role of self-regulation on harmonious passion, obsessive passion, and knowledge management in E-learning. Educational Technology Research and Development, 66(3), 615–637. https://doi.org/10.1007/s11423-017-9562-x
Zhao, Y., Wang, N., Li, Y., et al. (2021). Do cultural differences affect users’ e‐learning adoption? A meta‐analysis. British Journal of Educational Technology, 52(1), 20–41. Portico. https://doi.org/10.1111/bjet.13002
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