Keywords
academic performance
e-learning
Motivation
university students
Abstract
The primary objective of this research was to examine the perception of e-learning among university students, in relation to their skills, learning behaviors, and their levels of academic self-efficacy and motivation under an e-learning environment, and its impact on their academic performance. A sample of 200 undergraduate students from a university of education participated in the study. Utilizing a regression model, it was found that students are more at ease and inclined to learn in an e-learning environment, which improves their comprehension of e-learning, self-efficacy, and motivation for academic performance. The results are significant as they demonstrate the impact of students' academic motivations, self-efficacy and their understanding of e-learning towards academic performance. The study suggests that for students to perform academically in an e-learning environment, they must possess strong and sharp minds and be able to acquire digital skills. The outcomes of this research can be used to guide the counseling of students, instructors, and directors to enhance the effective implementation of e-learning.
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Bandura, A., & Wood, R. (1989). Effect of perceived controllability and performance standards on self-regulation of complex decision making. Journal of personality and social psychology, 56(5), 805.
Carini, R. M., Kuh, G. D., & Klein, S. P. (2006). Student engagement and student learning: Testing the linkages. Research in higher education, 47(1), 1-32.
Castillo-Merino, D., & Serradell-López, E. (2014). An analysis of the determinants of students’ performance in e-learning. Computers in Human Behavior, 30, 476-484.
Chou, S. W., & Liu, C. H. (2005). Learning effectiveness in a Web‐based virtual learning environment: a learner control perspective. Journal of computer assisted learning, 21(1), 65-76.
Cidral, W. A., Oliveira, T., Di Felice, M., & Aparicio, M. (2018). E-learning success determinants: Brazilian empirical study. Computers & Education, 122, 273-290.
Coates, H. (2006). Student engagement in campus-based and online education: University connections: Routledge.
Deng, L., & Tavares, N. J. (2013). From Moodle to Facebook: Exploring students' motivation and experiences in online communities. Computers & Education, 68, 167-176.
Eze, S. C., Chinedu-Eze, V. C., & Bello, A. O. (2018). The utilisation of e-learning facilities in the educational delivery system of Nigeria: a study of M-University. International Journal of Educational Technology in Higher Education, 15(1), 1-20.
Fry, K. (2001). E‐learning markets and providers: some issues and prospects. Education+ Training.
Goh, C., Leong, C., Kasmin, K., Hii, P., & Tan, O. (2017). Students’ experiences, learning outcomes and satisfaction in e-learning. Journal of E-learning and Knowledge Society, 13(2).
Henrie, C. R., Halverson, L. R., & Graham, C. R. (2015). Measuring student engagement in technology-mediated learning: A review. Computers & Education, 90, 36-53.
Hodge, B., Wright, B., & Bennett, P. (2018). The role of grit in determining engagement and academic outcomes for university students. Research in Higher Education, 59(4), 448-460.
Hunley, S. A., Krise, J., Rich, T., & Schell, C. (2005). ADOLESCENT COMPUTER USE. Adolescence, 40(158).
Islam, A. N. (2013). Investigating e-learning system usage outcomes in the university context. Computers & Education, 69, 387-399.
Ituma, A. (2011). An evaluation of students’ perceptions and engagement with e-learning components in a campus based university. Active Learning in Higher Education, 12(1), 57-68.
Kiviniemi, M. T. (2014). Effects of a blended learning approach on student outcomes in a graduate-level public health course. BMC medical education, 14(1), 1-7.
Kuh, G. D. (2001). The National Survey of Student Engagement: Conceptual framework and overview of psychometric properties.
Kumashiro, M., Rusbult, C. E., & Finkel, E. J. (2008). Navigating personal and relational concerns: The quest for equilibrium. Journal of Personality and Social Psychology, 95(1), 94.
Laurillard, D. (2006). E-learning in higher education. Changing higher education: The development of learning and teaching, 3, 71-84.
Levy, Y. (2007). Comparing dropouts and persistence in e-learning courses. Computers & education, 48(2), 185-204.
López-Pérez, M. V., Pérez-López, M. C., & Rodríguez-Ariza, L. (2011). Blended learning in higher education: Students’ perceptions and their relation to outcomes. Computers & education, 56(3), 818-826.
Lust, G., Collazo, N. A. J., Elen, J., & Clarebout, G. (2012). Content management systems: Enriched learning opportunities for all? Computers in Human Behavior, 28(3), 795-808.
Lyons, T., & Evans, M. M. (2013). Blended learning to increase student satisfaction: An exploratory study. Internet reference services quarterly, 18(1), 43-53.
Means, B., Toyama, Y., Murphy, R., & Baki, M. (2013). The effectiveness of online and blended learning: A meta-analysis of the empirical literature. Teachers college record, 115(3), 1-47.
Moore, C., & Shulock, N. (2009). Student progress toward degree completion: Lessons from the research literature: California State University, Sacramento, Institute for Higher Education ….
Naveed, Q. N., Muhammed, A., Sanober, S., Qureshi, M. R. N., & Shah, A. (2017). Barriers Effecting Successful Implementation of E-Learning in Saudi Arabian Universities. International Journal of Emerging Technologies in Learning, 12(6).
Olelewe, C. J., & Agomuo, E. E. (2016). Effects of B-learning and F2F learning environments on students' achievement in QBASIC programming. Computers & Education, 103, 76-86.
Parkes, M., Stein, S., & Reading, C. (2015). Student preparedness for university e-learning environments. The Internet and Higher Education, 25, 1-10.
Pham, L., Limbu, Y. B., Bui, T. K., Nguyen, H. T., & Pham, H. T. (2019). Does e-learning service quality influence e-learning student satisfaction and loyalty? Evidence from Vietnam. International Journal of Educational Technology in Higher Education, 16(1), 1-26.
Plant, E. A., Ericsson, K. A., Hill, L., & Asberg, K. (2005). Why study time does not predict grade point average across college students: Implications of deliberate practice for academic performance. Contemporary educational psychology, 30(1), 96-116.
Robbins, S. B., Lauver, K., Le, H., Davis, D., Langley, R., & Carlstrom, A. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological bulletin, 130(2), 261.
Roffe, I. (2002). E‐learning: engagement, enhancement and execution. Quality assurance in education.
Schunk, D. H., & Mullen, C. A. (2012). Self-efficacy as an engaged learner. In Handbook of research on student engagement (pp. 219-235): Springer.
Van der Merwe, D., & Engelbrecht, A. P. (2003). Data clustering using particle swarm optimization. Paper presented at the The 2003 Congress on Evolutionary Computation, 2003. CEC'03.
Wigfield, A., & Cambria, J. (2010). Students’ achievement values, goal orientations, and interest: Definitions, development, and relations to achievement outcomes. Developmental review, 30(1), 1-35.
Woods, R., Baker, J. D., & Hopper, D. (2004). Hybrid structures: Faculty use and perception of web-based courseware as a supplement to face-to-face instruction. The Internet and Higher Education, 7(4), 281-297.
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