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Adopting Learning Analytics to Inform Postgraduate Curriculum Design: Recommendations and Research Agenda.

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This study explores using Learning Analytics (LA) to understand student sentiment and support university curriculum design. It offers recommendations for optimizing LA integration into teaching and proposes a future research agenda.

Keywords:
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Area of Science:

  • Educational Technology
  • Higher Education Pedagogy
  • Learning Analytics

Background:

  • Student sentiment is crucial for effective university curriculum design.
  • Learning Analytics (LA) offers potential for enhancing student learning experiences and supporting pedagogical inquiry.
  • Limited research exists on the practical adoption and application of LA in supporting teacher inquiry.

Purpose of the Study:

  • To investigate the longitudinal use of LA to support teacher inquiry over four years.
  • To capture postgraduate student sentiment within a Master of Science in Business Analytics program.
  • To provide evidence-based recommendations for optimizing LA integration in curriculum design and delivery.

Main Methods:

  • A four-year longitudinal study conducted between 2016 and 2020.
  • Integration of Learning Analytics with the stages of teacher inquiry.
  • Sentiment analysis of postgraduate students in a Business Analytics program.

Main Results:

  • The study reports on the sustained use of LA to facilitate teacher inquiry across four academic cycles.
  • Evidence-based recommendations are provided for enhancing LA's role in curriculum development.
  • Insights into improving the assimilation of LA into educational practices are presented.

Conclusions:

  • LA can effectively support teacher inquiry and inform curriculum design.
  • Optimizing LA integration requires attention to curriculum assimilation strategies.
  • A future research agenda is proposed to advance LA adoption in higher education.