Influence of Online Learning Platforms on Academic Performance and Student Engagement
DOI:
https://doi.org/10.70062/managementdynamics.v1i2.481Keywords:
Academic Performance, Digital Education, Learning Platforms, Online Learning, Student EngagementAbstract
The rapid transformation of higher education driven by the advancement of digital technologies and the COVID-19 pandemic has accelerated the adoption of online learning platforms across universities worldwide. This study investigates the relationship between the use of online learning platforms, academic performance, and student engagement among university students. Using a cross-sectional survey design, data were collected from students actively participating in online learning environments to analyze how frequency of platform use influences academic outcomes and engagement levels. The results reveal a positive correlation between online learning engagement and academic performance, indicating that students who consistently participate in live sessions, complete assignments, and interact with peers and instructors achieve better academic results. Cognitive and behavioral engagement were found to be the most influential factors contributing to improved learning outcomes, while emotional engagement played a supportive role in maintaining motivation and persistence. Despite these benefits, several challenges were identified, including social isolation, limited face-to-face interaction, and technological barriers that hinder full participation. Comparisons with traditional learning environments highlight that online platforms provide greater flexibility and personalized learning opportunities but lack the immediacy of in-person interaction. Furthermore, differences between local and international contexts underscore the role of infrastructure and institutional readiness in ensuring equitable online learning experiences. The study concludes that effective integration of technology, instructor presence, and collaborative tools can enhance engagement and academic success in digital learning environments. Future research should explore long-term impacts, including the role of gamification and artificial intelligence in sustaining motivation and improving educational outcomes.
References
Abdullah, M. N. L. Y., Li Hsien, O., Nagaratnam, S., & Yik Kuan, H. J. L. (2024). Factors influencing undergraduate students’ engagement in online learning: A PLS-SEM approach. Learning: Research and Practice, 10(2), 233–257. https://doi.org/10.1080/23735082.2024.2348997
Adeoye, B. F., & Oni, A. A. (2024). Digital learning and the teaching-learning environment in the post-pandemic 21st century. In Instructional Technology Theory in the Post-Pandemic Era (pp. 1–41). https://doi.org/10.4018/979-8-3693-7645-4.ch001
Akpen, C. N., Asaolu, S., Atobatele, S., Okagbue, H., & Sampson, S. (2024). Impact of online learning on student's performance and engagement: A systematic review. Discover Education, 3(1), 1–18. https://doi.org/10.1007/s44217-024-00253-0
Alam, A. (2023). Harnessing the power of AI to create intelligent tutoring systems for enhanced classroom experience and improved learning outcomes. Lecture Notes on Data Engineering and Communications Technologies, 171, 571–591. https://doi.org/10.1007/978-981-99-1767-9_42
Aleid, M. A., Morsi, S. A., Shishakly, R., Aldhyani, T. H. H., & Almaiah, M. A. (2024). Modelling and predicting student flexibility in online learning using artificial intelligence approaches. International Journal of Data and Network Science, 8(4), 2255–2266. https://doi.org/10.5267/j.ijdns.2024.6.006
Anistyasari, Y., Hidayati, S. C., & Ekohariadi. (2024). A tree-based model for predicting student achievement in online learning environments. 2024 7th International Conference on Vocational Education and Electrical Engineering: Charting the Course of Artificial Technology in Sustainable Society, ICVEE 2024, 262–267. https://doi.org/10.1109/ICVEE63912.2024.10823659
Bai, X., Ola, A., Reese, S., & Eyob, E. (2021). A practical framework to engage students in college teaching. Issues in Information Systems, 22(4), 83–92. https://doi.org/10.48009/4_iis_2021_88-98
Bui, H. P. (2023). L2 teachers’ strategies and students’ engagement in virtual classrooms: A multidimensional perspective. Lecture Notes in Networks and Systems, 617 LNNS, 205–213. https://doi.org/10.1007/978-981-19-9512-5_18
Chakraborty, T., Tripathi, M., & Sharada, V. S. (2024). Continuous revitalizing through reskilling and upskilling among future employees: Role of sustaining growth in online learning platforms. In Revitalizing Student Skills for Workforce Preparation (pp. 37–67). https://doi.org/10.4018/979-8-3693-3856-8.ch002
Darejeh, A., Mashayekh, S., & Marcus, N. (2022). Cognitive-based methods to facilitate learning of software applications via E-learning systems. Cogent Education, 9(1). https://doi.org/10.1080/2331186X.2022.2082085
Dmello, V. J., Jagannathrao, V., Rajendran, A., Bidi, S. B., Ghosh, T., Kaur, J., & Haldorai, K. (2023). Antecedents promoting e-learner’s engagement behavior: Mediating effect of e-learner’s intention to use behavior. Cogent Education, 10(2). https://doi.org/10.1080/2331186X.2023.2226456
Duisenova, M. M., & Zhorabekova, A. N. (2024). Effects of rewards on motivation and student achievement in digital game-based learning in teaching English as a foreign language for primary school pupils in Kazakhstan. Arab World English Journal, 15(3), 125–141. https://doi.org/10.24093/awej/vol15no3.8
Garcia, M. B., Goi, C. L., Shively, K., Maher, D., Rosak-Szyrocka, J., Happonen, A., Bozkurt, A., & Damaševičius, R. (2024). Understanding student engagement in AI-powered online learning platforms: A narrative review of key theories and models. In Cases on Enhancing P-16 Student Engagement With Digital Technologies (pp. 1–30). https://doi.org/10.4018/979-8-3693-5633-3.ch001
Jiang, T., Cao, Y., Gong, S., Liu, X., Wu, Y., & Lang, Y. (2023). Teacher’s autonomy support and high school students' online learning engagement: The roles of autonomous motivation and proactive personality. Journal of Psychological Science, 46(6), 1336–1343. https://doi.org/10.16719/j.cnki.1671-6981.20230608
Junça Silva, A., & Almeida, N. (2023). Can engagement and performance be improved through online training on emotional intelligence? A quasi-experimental approach. International Journal of Educational Management, 37(2), 449–464. https://doi.org/10.1108/IJEM-03-2022-0092
Koć-Januchta, M. M., Schönborn, K. J., Roehrig, C., Chaudhri, V. K., Tibell, L. A. E., & Heller, H. C. (2022). “Connecting concepts helps put main ideas together”: Cognitive load and usability in learning biology with an AI-enriched textbook. International Journal of Educational Technology in Higher Education, 19(1). https://doi.org/10.1186/s41239-021-00317-3
Kuzminykh, I., Ghita, B., & Xiao, H. (2021). The relationship between student engagement and academic performance in online education. ACM International Conference Proceeding Series, 97–101. https://doi.org/10.1145/3485768.3485796
Langat, A. K. (2024). Transition from analogue to digital technology: Examining teaching, learning, and assessment in higher education in Kenya. In Artificial Intelligence, Digital Learning, and Leadership: Redefining Higher Education (pp. 89–117). https://doi.org/10.4018/979-8-3373-0025-2.ch004
Lin, L., & Wang, F. (2023). Research on the relationship between learning engagement and learning performance in online learning. ACM International Conference Proceeding Series, 201–206. https://doi.org/10.1145/3629296.3629327
Liu, L., Ma, W., & Han, G. (2021). A research on the influence of teacher-student interaction on college student engagement in online learning. ACM International Conference Proceeding Series, 214–222. https://doi.org/10.1145/3498765.3498799
Maj, S. P. (2022). A practical new 21st century learning theory for significantly improving STEM learning outcomes at all educational levels. Eurasia Journal of Mathematics, Science and Technology Education, 18(2). https://doi.org/10.29333/EJMSTE/11510
Manjeese, C. (2022). Divulging the efficacy of e-learning through the eyes of university students: Lessons from a third world perspective. Physics and Chemistry of the Earth, 127, 103187. https://doi.org/10.1016/j.pce.2022.103187
Patra, B. N., Rina, K., & Padhy, S. K. (2021). Colossal breed and backlash of the 'Sesame Street': Brunt of COVID-19 pandemic in the 'high-tech' era of learning on children and adolescents and suggestions. Psychiatria Danubina, 33(4), 600–603. https://doi.org/10.24869/PSYD.2021.600
Paulsen, J., & McCormick, A. C. (2020). Reassessing disparities in online learner student engagement in higher education. Educational Researcher, 49(1), 20–29. https://doi.org/10.3102/0013189X19898690
Soffer, T., Kahan, T., & Nachmias, R. (2019). Patterns of students' utilization of flexibility in online academic courses and their relation to course achievement. International Review of Research in Open and Distributed Learning, 20(3), 202–220. https://doi.org/10.19173/irrodl.v20i4.3949
Sun, P. P., & Zhang, L. J. (2024). Investigating the effects of Chinese university students’ online engagement on their EFL learning outcomes. Asia-Pacific Education Researcher, 33(4), 747–757. https://doi.org/10.1007/s40299-023-00800-7
Vargas, R. M., & Kalman, J. (2018). The construction of flexibility in a virtual program at a public Colombian distance education university. Revista de Educación a Distancia, 58. https://doi.org/10.6018/red/58/8
Vetrivel, S. C., Arun, V. P., Maheswari, R., & Saravanan, T. P. (2024). Technology integration in online learning platforms: Blended learning gamification. In Transdisciplinary Teaching and Technological Integration for Improved Learning: Case Studies and Practical Approaches (pp. 219–247). https://doi.org/10.4018/979-8-3693-8217-2.ch011
Wang, S., Bao, J., Liu, Y., & Zhang, D. (2024). The impact of online learning engagement on college students’ academic performance: The serial mediating effect of inquiry learning and reflective learning. Innovations in Education and Teaching International, 61(6), 1416–1430. https://doi.org/10.1080/14703297.2023.2236085
Wei, Y., Li, J., Yin, P., Shi, Y., & Yin, Y. (2024). Research on the impact of teaching presence, facilitating conditions, and academic self-efficacy on university students' online learning engagement. 2024 4th International Conference on Educational Technology, ICET 2024, 190–194. https://doi.org/10.1109/ICET62460.2024.10868052
Wiseman, P. J., Kennedy, G. E., & Lodge, J. M. (2016). Models for understanding student engagement in digital learning environments. ASCILITE 2016 - Conference Proceedings - 33rd International Conference of Innovation, Practice and Research in the Use of Educational Technologies in Tertiary Education: Show Me the Learning, 666–671. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065156354&partnerID=40&md5=e4fe0e06ace535c094cb0b79744fc525
Wiseman, P. J., Lodge, J. M., Arguel, A., & Kennedy, G. E. (2019). The changing nature of student engagement during a digital learning task. ASCILITE 2017 - Conference Proceedings - 34th International Conference of Innovation, Practice and Research in the Use of Educational Technologies in Tertiary Education, 433–440. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072045394&partnerID=40&md5=ebd4b3f16093c9511b388581574a7452
Xu, F., Jin, B., Xu, Y., Liu, B., Li, X., & Wang, Y. (2017). Does learning stickiness of students on network educational platform affect students' academic performance? Proceedings - 6th International Conference of Educational Innovation Through Technology, EITT 2017, 2018-March, 120–125. https://doi.org/10.1109/EITT.2017.37
Zou, X., & Yu, Z. (2022). Student perceptions of factors influencing engagement in online courses on Tencent Meeting. International Journal of Online Pedagogy and Course Design, 12(1). https://doi.org/10.4018/IJOPCD.311442
