How e-learning engagement time affects academic achievement in e-learning environments. A large-scale study of open and distance learners

Mehmet Firat, Aylin Öztürk, İhsan Güneş, Esra Çolak, Melda Beyaz, Köksal Büyük


The literature is considerably rich about engagement and academic achievement in the context of open and distance learning. However, there is limited research that investigates these variables with large scale participants. In this regard, the aim of this research was to investigate causal correlations between e-learning engagement time and academic achievement of open and distance learners according to course subject, dropout, and bounce rate variables. The participants of this study were 323,264 open and distance learners from Anadolu University, Turkey. Throughout this research, open and distance learners’ engagement time levels and their academic achievements are compared. Academic achievement was found to increase significantly when learners engaged more with e-learning materials.


Open and distance learning; Academic achievement; Engagement time; Bounce rate

Full Text:



Anderson, T. (2003). Modes of interaction in distance education: Recent developments and research questions. In M. Moore & W. Anderson (Eds.), Handbook of distance education (pp. 129–144). Mahwah, NJ: Lawrence Erlbaum.

Astin, A. (1985). Achieving educational excellence: A critical assessment of priorities and practices in higher education. San Francisco: Jossey-Bass.

Astin, A. (1993). What matters in college? Four critical years revisited. San Francisco: Jossey-Bass.

Büyüköztürk, Ş. (2005). Handbook of data analysis for the social sciences. Ankara: PegemA.

Chickering, A., & Gamson, Z. (1987). Seven principles for good practice in undergraduate education. AAHE Bulletin, 39(7), 3–7.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.

Djamasbi, S., Gomez, W., Kardzhaliyski, G., Liu, W., Oglesby, F., & McAuliffe, D. (2014). Designing for success: Creating business value with mobile user experience (UX). Retrieved from

Harper, S. R., & Quaye, S. J. (2009). Student engagement in higher education. New York and London: Routledge.

Hu, S., & Kuh, G. D. (2001). Being (dis)engaged in educationally purposeful activities: The influences of student and institutional characteristics. Paper presented at the American Educational Research Association Annual Conference, Seattle, WA.

Krause, K., & Coates, H. (2008). Students’ engagement in first-year university. Assessment and Evaluation in Higher Education, 33(5), 493–505.

Liaw, S. S. (2008). Investigating students’ perceived satisfaction, behavioral intention, and effectiveness of e-learning: A case study of the Blackboard system. Computers & Education, 51(2), 864–873.

McKenna, B. A., & Kopittke, P. M. (2018). Engagement and performance in a first year natural resource science course. Journal of Computer Assisted Learning, 34(3), 233–242.

Moore, M. G. (1989). Editorial: Three types of interaction. American Journal of Distance Education, 3(2), 1–7.

Nguyen, Q., Huptych, M., & Rienties, B. (2018, March). Linking students’ timing of engagement to learning design and academic performance. In Proceedings of the 8th International Conference on Learning Analytics and Knowledge (pp. 141–150). ACM.

Oye, N. A., Iahad, N., Madar, M. J., & Rahim, N. (2012). The impact of e-learning on students’ performance in tertiary institutions. International Journal of Computer Networks and Wireless Communications, 2(2), 121–130.

Özsoy, S., & Özsoy, G. (2013). Effect size reporting in educational research. Elementary Education Online, 12(2), 334–346.

Pace, C. R. (1995). From good practices to good products: Relating good practices in undergraduate education to student achievement. Paper presented at the Association of Institutional Research, Boston.

Sculley, D., Malkin, R. G., Basu, S., & Bayardo, R. J. (2009). Predicting bounce rates in sponsored search advertisements. In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 1325–1334). ACM.

Shadish, W., Cook, T., & Campbell, D. (2002). Experimental and quasi-experimental designs for generalized causal inference. Boston: Houghton Mifflin Company.

Stovall, I. (2003). Engagement and Online Learning. UIS Community of Practice for E-Learning. Retrieved from

Tao, Z., Zhang, B., & Lai, I. K. W. (2018, January). Perceived Online Learning Environment and Students’ Learning Performance in Higher Education: Mediating Role of Student Engagement. In International Conference on Technology in Education (pp. 56–64). Springer, Singapore.

Vache-Haase, T., & Ness, C. M. (1999). Statistical significance testing as it relates to practice: Use within professional psychology: Research and practice. Professional Psychology: Research and Practice, 30, 104–105.

White, D. S., & Le Cornu, A. (2011). Visitors and Residents: A new typology for online engagement. First Monday, 16(9).

Zhang, Z., Li, Z., Liu, H., Cao, T., & Liu, S. (2019). Data-drived Online Learning Engagement Detection via Facial Expression and Mouse Behavior Recognition Technology. Journal of Educational Computing Research.



  • There are currently no refbacks.