Network Analytics to Unveil Links of Learning Strategies, Time Management, and Academic Performance in a Flipped Classroom


  • Mladen Rakovic Monash University
  • Nora'ayu Ahmad Uzir Universiti Teknologi MARA
  • Wannisa Matcha Prince of Songkla University
  • Brendan Eagan University of Wisconsin
  • Jelena Jovanović University of Belgrade
  • David Williamson Shaffer University of Wisconsin
  • Abelardo Pardo University of South Australia
  • Dragan Gašević Monash University



learning analytics, learning strategies, self-regulated learning, time management, research paper


Preparatory learning tasks are considered critical for student success in flipped classroom courses. However, less is
known regarding which learning strategies students use and when they use those strategies in a flipped classroom
course. In this study, we aimed to address this research gap. In particular, we investigated mutual connections
between learning strategies and time management, and their combined effects on students’ performance in flipped
classrooms. To this end, we harnessed a network analytic approach based on epistemic network analysis (ENA) to
analyze student trace data collected in an undergraduate engineering course (N = 290) with a flipped classroom
design. Our findings suggest that high-performing students effectively used their study time and enacted learning
strategies mainly linked to formative and summative assessment tasks. The students in the low-performing group
enacted less diverse learning strategies and typically focused on video watching. We discuss several implications
for research and instructional practice.


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How to Cite

Rakovic, M., Ahmad Uzir, N., Matcha, W., Eagan, B., Jovanović, J., Williamson Shaffer, D., Pardo, A., & Gašević, D. (2023). Network Analytics to Unveil Links of Learning Strategies, Time Management, and Academic Performance in a Flipped Classroom. Journal of Learning Analytics, 1-23.



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