The Effects of E-Learning on Students’ Motivation to Learn in Higher Education
DOI:
https://doi.org/10.24059/olj.v25i3.2336Keywords:
Internal consistency, key aspects of e-learning, motivation to learn, higher education.Abstract
The recent COVID-19 pandemic has forced educational institutions worldwide to adopt e-learning. UAE higher education institutions have implemented e-learning systems and programs to cope with this unprecedented situation. This paper measured the strength of association between key aspects of e-learning systems and programs and students’ motivation to learn in Ajman University (AU). Cronbach’s coefficient alpha was used to test the internal consistency reliability of key aspects of e-learning (EL-8) and students’ motivation to learn (SML-16). Exploratory factor analysis was used to test the validity of, and coherence of patterns in, the data. Parametric and non-parametric methods were used to investigate the strength of association between key aspects of e-learning and students’ motivation to learn in AU. The results indicated that motivation variables were more strongly correlated with both e-teaching materials and e-assessments key aspects relative to others such as e-discussion, and e-grade checking and feedback.
References
Buelow, J. R., Barry, T., & Rich, L. E. (2018). Supporting learning engagement with online students. Online Learning, 22(4), 313–340. https://doi:10.24059/olj.v22i4.1384
Chan, D. K. C., Yang, S. X., & Hamamura, T. (2015). In-lecture learning motivation predicts students’ motivation, intention, and behaviour for after-lecture learning: Examining the trans-contextual model across universities from UK, China, and Pakistan. Motivation and Emotion, 39(6), 908–925. https://doi.org/10.1007/s11031-015-9506-x
Chan, K., Lai, S., Leung, H., & Wan, K. (2016). Engagement in online asynchronous discussions: Roles of students' interests and preferences. Proceedings of the International Conference on e-Learning, ICEL, Jun 2016, 32–36.
Chang, M. M., & Lehman, J. (2002). Learning foreign language through an interactive multimedia program: An experimental study on the effects of the relevance component of the ARCS model. CALICO Journal, 20(1), 81–98.
Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78(1), 98–104.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297–334.
Cundell, A., & Sheepy, E. (2018). Student perceptions of the most effective and engaging online
learning activities in a blended graduate seminar. Online Learning, 22(3), 87–102. https://doi:10.24059/olj.v22i3.1467
Dennen, V. P., & Bagdy, L. M. (2019). From proprietary textbook to custom OER solution: Using learner feedback to guide design and development. Online Learning, 23(3), 4–20. https://doi:10.24059/olj.v23i3.2068
Ellis, R. A., Ginns, P., & Piggott, L. (2009). E-learning in higher education: Some key aspects and their relationship to approaches to study. Higher Education Research & Development, 28, 303−318.
Guo, Y. R., Goh, D., & Luyt, B. (2017). Tertiary students’ acceptance of a game to teach information literacy. Aslib Journal of Information Management, 69(1) 46-63. https://doi.org/10.1108/AJIM-08-2016-0131
Harandi, R. S. (2015). Effects of e-learning on students' motivation. Procedia - Social and Behavioral Sciences 181, 423–430.
Hirumi, A., Sivo, S., & Pounds, K. (2012). Storytelling to enhance teaching and learning: the systematic design, development, and testing of two online courses. International Journal on E-Learning, 11(2) 125–151.
Hoban, J. D., Lawson, S. R., Mazmanian, P. E., Best, A.M., & Seibel, H. R. (2005). The self-directed learning readiness scale: A factor analysis study. Medical Education, 39(4), 370–379. https://doi.org/10.1111/j.1365-2929.2005.02140.x
Imansari, A., Umamah, N., & Na’im, M. (2018). The usage of e-book as learning media through the sigil application in history. IOP Conf. Series: Earth and Environmental Science, 243, 012155. https://doi:10.1088/1755-1315/243/1/012155
Irawan, M. I., Mukhlash, I., Adzkiya, D., Darmadi, & Sanusi. (2019). Development of trigonometric visualization concepts to increase the study motivations of SMK students. International Conference on Mathematics: Pure, Applied and Computation. Journal of Physics: Conf. Series 1218. https://doi:10.1088/1742-6596/1218/1/012049
Karagiannis, I., & Satratzemi, M. (2018). Implementation of an adaptive mechanism in Moodle based on a hybrid dynamic user model. ICL 2018: The Challenges of the Digital Transformation in Education, 377–388.
Keller, J. M. (1987a). Strategies for stimulating the motivation to learn. Performance and Instruction, 26(8), 1–7.
Keller, J. M. (1987b). The systematic process of motivational design. Performance and Instruction, 26(9/10), 1–8.
Keller, J. M. (2008). An integrative theory of motivation, volition, and performance. Technology, Instruction, Cognition, and Learning, 6, 79–104.
Kim, C., Park, S. W., Huynh, N., & Schuermann, R. T. (2017). University students’ motivation, engagement and performance in a large lecture-format general education course. Journal of Further and Higher Education, 41(2), 201–214.
Kim, J. E., & Lee, R. K. (2019). Effects of an examiner’s positive and negative feedback on self-assessment of skill performance, emotional response, and self-efficacy in Korea: A quasi-experimental study. BMC Medical Education, 19(142). https://doi.org/10.1186/s12909-019-1595-x
Lim, S. C., & Park, T. (2011). The declining association between earnings and returns: Diminishing value relevance of earnings or noisier markets? Management Research Review, 34(8), 947–960.
Maulana, W. A., Wilujeng, I., & Kuswanto, H. (2019). Learning with the social media assisted science, technology and society approach to improve self-learning motivation. Journal of Physics: Conf. Series, 1233. https://doi:10.1088/1742-6596/1233/1/0120602
Mitchell, E. T. (2019). Using debate in an online asynchronous social policy course. Online Learning, 23(3), 21–33. https://doi:10.24059/olj.v23i3.2050
Paechter, M., & Maier, B. (2010). Online or face-to-face? Students’ experiences and preferences in e-learning. The Internet and Higher Education 13, 292–297.
Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hoagwood, K. (2015). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Adm Policy Ment Health 42, 533–544. https://doi.org/10.1007/s10488-013-0528-y
Prosser, M., Ramsden, P., Trigwell, K., & Martin, E. (2003). Dissonance in experience of teaching and its relation to the quality of student learning. Studies in Higher Education, 28, 37–48.
Pugh, C. (2019). Self-determination: Motivation profiles of bachelor’s degree-seeking students at an online, for-profit university. Online Learning, 23(1), 111–131. doi:10.24059/olj.v23i1.1422
Rahrouh, M., Taleb, N., & Mohamed, E. M. (2018). Evaluating the usefulness of e-learning management system delivery in higher education. Int. J. Economics and Business Research, 16(2), 162–181.
Rice, W. (2015). Moodle e-learning course development (3rd ed.) Packt.
Sadaf, A., Martin, F., & Ahlgrim-Delzell, L. (2019). Student perceptions of the impact of quality Matters-certified online courses on their learning and engagement. Online Learning, 23(4), 214–233. https://doi:10.24059/olj.v23i4.2009
Slater, D. R., & Davies, R. (2020). Student preferences for learning resources on a land-based postgraduate online degree program. Online Learning, 24(1), 140–161. https://doi:10.24059/olj.v24i1.1976
Snow, R. (1990). Aptitude-treatment interaction as a framework for research on individual difference in learning. In P. Ackerman, R. Sternberg, & R. Glaser (Eds.), Learning and individual differences (pp. 13–59). Freeman.
Songül, K., & Hakan, P. (2019). The effects of the flipped classroom model designed according to the ARCS motivation strategies on the students’ motivation and academic achievement levels. Education and Information Technologies 25, 1475–1495. https://doi:10.1007/s10639-019-09985-1
Stark, E. (2019). Examining the role of motivation and learning strategies in student success in online versus face-to-face courses. Online Learning, 23(3), 234–251. https://doi:10.24059/olj.v23i3.1556
Tibi, M. H. (2018). Computer science students’ attitudes towards the use of structured and unstructured discussion forums in online courses. Online Learning, 22(1), 93–106.
https://doi:10.24059/olj.v22i1.995
Tokan, K. M., & Imakulata, M. M. (2019). The effect of motivation and learning behaviour on student achievement. South African Journal of Education, 39(1).
Truhlar, A. M., Williams, K. M., & Walter, M. T. (2018). Case study: Student engagement with course content and peers in synchronous online discussions. Online Learning, 22(4), 289–312. https://doi:10.24059/olj.v22i4.1389
Tseng, H., & Walsh, E. J. (2016). Blended versus traditional course delivery comparing students’ motivation, learning outcomes, and preferences. Quarterly Review of Distance Education, 17(1), 43–52.
Vero, E., & Puka, E. (2017). The importance of motivation in an educational environment. Formazione & Insegnamento XV(1), 57–66. https://doi:107346/-fei-XV-01-17_05
Wan, Z., Wang Y., & Haggerty N., (2008). Why people benefit from e-learning differently: The effects of psychological processes on e-learning outcomes. Information & Management, 45(8), 513–521.
YiLi, L., & Tsai, C. (2017). Accessing online learning material: Quantitative behavior patterns and their effects on motivation and learning performance Author links open overlay panel. Computers & Education, 114, 286–297. https://doi.org/10.1016/j.compedu.2017.07.007
Zheng, C., Liang, J. C., Li, M., & Tsai, C-C. (2018). The relationship between English language learners’ motivation and online self-regulation: A structural equation modelling approach. System, 76, 144–157.
Downloads
Published
Issue
Section
License
As a condition of publication, the author agrees to apply the Creative Commons – Attribution International 4.0 (CC-BY) License to OLJ articles. See: https://creativecommons.org/licenses/by/4.0/.
This licence allows anyone to reproduce OLJ articles at no cost and without further permission as long as they attribute the author and the journal. This permission includes printing, sharing and other forms of distribution.
Author(s) hold copyright in their work, and retain publishing rights without restrictions