Informing learning design in online education using learning analytics of student engagement

Nguyen, Quan; Rienties, Bart and Whitelock, Denise (2022). Informing learning design in online education using learning analytics of student engagement. In: Rienties, Bart; Hampel, Regine; Scanlon, Eileen and Whitelock, Denise eds. Open World Learning: Research, Innovation and the Challenges of High-Quality Education. New York, USA: Routledge, pp. 189–207.

DOI: https://doi.org/10.4324/9781003177098-17

Abstract

Designing a curriculum in online and distance education can be challenging because the processes of what, when, and how students study are not always visible to teachers due to the limited opportunities for face-to-face interactions. Chapter 14 demonstrates the applications of learning analytics to understand the extent to which students’ engagement with online learning activities align with how instructors design the course, and the subsequent effect on their academic performance. This data-driven approach provides instructors with an opportunity to reflect on their course design through visualisations of weekly learning activities which highlights the workload and the variety of teaching approaches. Importantly, the analysis of digital traces in a virtual learning environment illuminates how students actually engage with the course materials and how different study patterns affect their academic performance. As an implication, this approach can help instructors pinpoint when and what study materials that students were struggling with. Chapter 14 showcases the potential to generate actionable analytics insights that go beyond the simple prediction of grades, for improving teaching and learning in online education.

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