Education Sciences (Nov 2023)

In Search of Alignment between Learning Analytics and Learning Design: A Multiple Case Study in a Higher Education Institution

  • Lisa-Angelique Lim,
  • Amara Atif,
  • Keith Heggart,
  • Nicole Sutton

DOI
https://doi.org/10.3390/educsci13111114
Journal volume & issue
Vol. 13, no. 11
p. 1114

Abstract

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Learning design (LD) has increasingly been recognized as a significant contextual element for the interpretation and adoption of learning analytics (LA). Yet, few studies have explored how instructors integrate LA feedback into their learning designs, especially within open automated feedback (AF) systems. This research presents a multiple-case study at one higher education institution to unveil instructors’ pilot efforts in using an open AF system to align LA and LD within their unique contexts, with the goal of delivering personalized feedback and tailored support. A notable finding from these cases is that instructors successfully aligned LA with LD for personalized feedback through checkpoint analytics in highly structured courses. Moreover, they relied on checkpoint analytics as an evaluation mechanism for evaluating impact. Importantly, students perceived a stronger sense of instructors’ support, reinforcing previous findings on the effectiveness of personalized feedback. This study contributes essential empirical insights to the intersection of learning analytics and learning design, shedding light on practical ways educators align LA and LD for personalized feedback and support.

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