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Applying a Learning Analytics Lifecycle Framework to Identify Gaps in Digital Learning Design: A Worked Example in

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Summary
This summary is machine-generated.

Learning analytics in health professions education (HPE) offer potential for improving digital learning environments. However, educators often struggle to effectively use data, highlighting the need for structured frameworks to guide implementation and maximize benefits for learners and educators.

Keywords:
data analyticsdigital learning environmentsinstructional designlearning analytics frameworkonline learning

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Area of Science:

  • Digital learning environments
  • Health professions education (HPE)
  • Learning analytics

Background:

  • Learning analytics involve analyzing digital footprints to improve educational design and teaching.
  • Educators have not fully utilized available learning analytics data from digital platforms.
  • Existing research indicates a gap in capitalizing on learning analytics in HPE.

Purpose of the Study:

  • To adapt a learning analytics lifecycle framework for evaluating digital learning in HPE.
  • To identify implementation gaps and opportunities in the eduCAST orthopaedic surgery training platform.
  • To develop transferable recommendations for educators in HPE regarding learning analytics.

Main Methods:

  • Adapted an established learning analytics lifecycle framework.
  • Evaluated eduCAST, a video-based online orthopaedic surgery training website.
  • Analyzed demographic and engagement data of 141 registered users via website analytics.

Main Results:

  • Limitations and opportunities were identified in planning, data scope, analysis techniques, and educator actions.
  • Generic website analytics showed low correlation between traffic and meaningful engagement.
  • Analytics provided limited insights for website refinement, yielding 'data mysteries' rather than 'data stories.'

Conclusions:

  • Educators in HPE often show diminishing investment across the learning analytics lifecycle.
  • Learning analytics frameworks can guide the design, implementation, evaluation, and sustainability of digital learning.
  • Thoughtful use of learning analytics can enhance learner outcomes, support educators, and inform program refinement.