Exploring the Effect of Online Course Design on Students’ Knowledge Transfer and Retention through Learning Analytics
Abstract
There is a vast amount of data collected on e-learning platforms that can provide insight and guidance to both learners and educators. However, this data is rarely used for evaluation and understanding the learning process. Hence, to fill this gap in the literature this study explored the effect of online course design on students’ transfer and retention of knowledge through learning analytics. The aim was to reveal study behaviours of participants over a short time while exploring their academic performance. Using a mixed method approach, this research is conducted in two different countries in a limited time. The results showed that the more times students visited the learning module and the longer these visits, the higher the students’ transfer knowledge scores in this module. Most importantly, the only variable found to be a significant predictor of students’ transfer learning outcome was the number of sessions in the module website.
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Barnett, S. M., & Ceci, S. J. (2002). When and where do we apply what we learn?: A taxonomy for far transfer. Psychological bulletin, 128(4), 612.
Bloom, B. S. (1956). Taxonomy of educational objectives: The classification of educational goals. Cognitive domain.
Brennenraedts, R., Bekkers, R., & Verspagen, B. (2006). The different channels of university-industry knowledge transfer: Empirical evidence from Biomedical Engineering. Eindhoven: Eindhoven Centre for Innovation Studies, The Netherlands.
Chen, Z., Xu, M., Garrido, G., & Guthrie, M. W. (2020). Relationship between students’ online learning behavior and course performance: What contextual information matters? Physical Review Physics Education Research, 16(1), 010138.
Gašević, D., Dawson, S., Rogers, T., & Gasevic, D. (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.
Gašević, D., Dawson, S., & Siemens, G. (2015). Let’s not forget: Learning analytics are about learning. TechTrends, 59(1), 64-71.
Ibrahim, M., Callaway, R., & Gulbahar, Y. (2019). Utilizing Learning Analytics in Measuring Students’ Learning Outcomes: Re-examining an Online Course Grounded in the Cognitive-Affective Theory of Learning with Media (CATLM). E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education.
Ifenthaler, D., & Widanapathirana, C. (2014). Development and validation of a learning analytics framework: Two case studies using support vector machines. Technology, Knowledge and Learning, 19(1-2), 221-240.
Law, J. K., Thome, P. A., Lindeman, B., Jackson, D. C., & Lidor, A. O. (2018). Student use and perceptions of mobile technology in clinical clerkships–Guidance for curriculum design. The American Journal of Surgery, 215(1), 196-199.
Lockyer, L., & Dawson, S. (2012). Where learning analytics meets learning design. Proceedings of the 2nd International Conference on Learning Analytics and Knowledge.
Lockyer, L., Heathcote, E., & Dawson, S. (2013). Informing pedagogical action: Aligning learning analytics with learning design. American Behavioral Scientist, 57(10), 1439-1459.
Loh, C. S., Sheng, Y., & Ifenthaler, D. (2015). Serious games analytics: Theoretical framework. In Serious games analytics (pp. 3-29). Springer.
Low, R., & Sweller, J. (2005). The modality principle in multimedia
learning. The Cambridge handbook of multimedia learning, 147, 158.
Mah, D.-K., Yau, J. Y.-K., & Ifenthaler, D. (2019). Epilogue: Future directions on learning analytics to enhance study success. In Utilizing learning analytics to support study success (pp. 313-321). Springer.
Martin, F., & Ndoye, A. (2016). Using learning analytics to assess student learning in online courses. Journal of University Teaching & Learning Practice, 13(3), 7.
McGuinness, C. (1990). Talking about thinking: The role of metacognition in teaching thinking. Lines of thinking, 2, 310-312.
Muljana, P. S., & Luo, T. (2020). Utilizing learning analytics in course design: voices from instructional designers in higher education. Journal of Computing in Higher Education, 1-29.
O’Reilly, N. M., Robbins, P., & Scanlan, J. (2019). Dynamic capabilities and the entrepreneurial university: a perspective on the knowledge transfer capabilities of universities. Journal of Small Business & Entrepreneurship, 31(3), 243-263.
Redmond, W., & Macfadyen, L. (2020). A Framework to Leverage and Mature Learning Ecosystems. International Journal of Emerging Technologies in Learning (iJET), 15(5), 75-99.
Rienties, B., Toetenel, L., & Bryan, A. (2015). " Scaling up" learning design: impact of learning design activities on LMS behavior and performance. Proceedings of the Fifth International Conference on Learning Analytics and Knowledge.
Schmitz, M., Van Limbeek, E., Greller, W., Sloep, P., & Drachsler, H. (2017). Opportunities and challenges in using learning analytics in learning design. European conference on technology enhanced learning.
Schumacher, C., & Ifenthaler, D. (2018). Features students really expect from learning analytics. Computers in Human Behavior, 78, 397-407.
Schunk, D. H. (2012). Learning theories an educational perspective sixth edition. Pearson.
Sharifi, H., Liu, W., & Ismail, H. S. (2014). Higher education system and the ‘open’knowledge transfer: a view from perception of senior managers at university knowledge transfer offices. Studies in higher education, 39(10), 1860-1884.
Strang, K. D. (2017). Beyond engagement analytics: which online mixed-data factors predict student learning outcomes? Education and information technologies, 22(3), 917-937.
Viberg, O., Hatakka, M., Bälter, O., & Mavroudi, A. (2018). The current landscape of learning analytics in higher education. Computers in Human Behavior, 89, 98-110.
Webber, K. L., Krylow, R. B., & Zhang, Q. (2013). Does involvement really matter? Indicators of college student success and satisfaction. Journal of College Student Development, 54(6), 591-611.
West, D., Heath, D., & Huijser, H. (2016). Let's talk learning analytics: A framework for implementation in relation to student retention. Online Learning, 20(2), 1-21.
West, D., Huijser, H., Lizzio, A., Toohey, D., Miles, C., Searle, B., & Bronnimann, J. (2015). Learning Analytics: Assisting Universities with Student Retention Project Outcome: Institutional Analytics Case Studies.
Wolff, A., Zdrahal, Z., Nikolov, A., & Pantucek, M. (2013). Improving retention: predicting at-risk students by analysing clicking behaviour in a virtual learning environment. Proceedings of the third international conference on learning analytics and knowledge.
Wong, B. T. M. (2017). Learning analytics in higher education: an analysis of case studies. Asian Association of Open Universities Journal.
Yukselturk, E., & Bulut, S. (2007). Predictors for student success in an online course. Journal of Educational Technology & Society, 10(2), 71-83.
DOI: https://doi.org/10.51383/jesma.2022.28
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