Reflections on Different Learning Analytics Indicators for Supporting Study Success

Authors

  • Dirk Ifenthaler Curtin University University of Mannheim
  • Jane Yin-Kim Yau University of Mannheim

DOI:

https://doi.org/10.3991/ijai.v2i2.15639

Keywords:

learning analytics, study success, analytics methods, student-at-risk, dropout

Abstract


Common factors, which are related to study success include students’ sociodemographic factors, cognitive capacity, or prior academic performance, and individual attributes as well as course related factors such as active learning and attention or environmental factors related to supportive academic and social embeddedness. In addition, there are various stages of a learner’s learning journey from the beginning when commencing learning until its completion, as well as different indicators or variables that can be examined to gauge or predict how successfully that journey can or will be at different points during that journey, or how successful learners may complete the study and thereby acquiring the intended learning outcomes. The aim of this research is to gain a deeper understanding of not only if learning analytics can support study success, but which aspects of a learner’s learning journey can benefit from the utilisation of learning analytics. We, therefore, examined different learning analytics indicators to show which aspect of the learning journey they were successfully supporting. Key indicators may include GPA, learning history, and clickstream data. Depending on the type of higher education institution, and the mode of education (face-to-face and/or distance), the chosen indicators may be different due to them having different importance in predicting the learning outcomes and study success.

Author Biographies

Dirk Ifenthaler, Curtin University University of Mannheim

Dirk Ifenthaler is Professor and Chair of Learning, Design and Technology at the University of Mannheim, Germany and UNESCO Deputy Chair of Data Science in Higher Education Learning and Teaching at Curtin University, Australia. His research focuses on the intersection of cognitive psychology, educational technology, data analytics and organisational learning (www.ifenthaler.info).

Jane Yin-Kim Yau, University of Mannheim

Jane Yin-Kim Yau is a Researcher in Learning Analytics & Mobile Learning at the Chair for Learning, Design and Technology at the University of Mannheim, Germany.

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Published

2020-07-06

How to Cite

Ifenthaler, D., & Yau, J. Y.-K. (2020). Reflections on Different Learning Analytics Indicators for Supporting Study Success. International Journal of Learning Analytics and Artificial Intelligence for Education (iJAI), 2(2), pp. 4–23. https://doi.org/10.3991/ijai.v2i2.15639

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Papers