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Updated: Oct 2, 2025

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Learning analytics dashboard: a tool for providing actionable insights to learners.

Teo Susnjak1, Gomathy Suganya Ramaswami1, Anuradha Mathrani1

  • 1School of Mathematical and Computational Sciences, Massey University, Auckland, New Zealand.

International Journal of Educational Technology in Higher Education
|February 23, 2022
PubMed
Summary

This study addresses limitations in current learning analytics (LA) dashboards by proposing an advanced model. It integrates machine learning for predictive and prescriptive insights, enhancing learner engagement and behavioral change.

Keywords:
Actionable insightsCounterfactualsDashboardExplainable AILearner analyticsModel interpretability

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Area of Science:

  • Educational Technology
  • Data Science
  • Human-Computer Interaction

Background:

  • Current learning analytics (LA) dashboards often lack actionable insights.
  • Many dashboards utilize only descriptive analytics, limiting their effectiveness.
  • Operationalizing LA dashboards presents challenges for educational institutions.

Purpose of the Study:

  • To investigate current LA dashboarding approaches and their limitations.
  • To propose an advanced LA dashboard integrating machine learning for predictive and prescriptive analytics.
  • To enhance learner understanding and trust in predictive models.

Main Methods:

  • Analysis of recent LA dashboards for insight generation capabilities.
  • Development of a novel dashboard integrating descriptive, predictive, and prescriptive analytics.
  • Demonstration of machine learning interpretability for user trust and regulatory compliance.

Main Results:

  • Most existing LA dashboards offer limited descriptive analytics.
  • The proposed dashboard integrates machine learning for advanced predictive and prescriptive capabilities.
  • Interpretability features enhance user trust and regulatory adherence.

Conclusions:

  • Advanced LA dashboards can drive learner behavioral change through data-driven advice.
  • Integrating machine learning and interpretability addresses current gaps in LA dashboarding.
  • The novel dashboard offers a comprehensive approach to learning analytics, currently in trials.