Leveraging Learning Analytics for Assessment and Feedback

This chapter energises the field of learning analytics by presenting research on assessment through recognising the humanness and depth of data analytics and learning.

Ifenthaler, D., & Greiff, S. (2021). Leveraging learning analytics for assessment and feedback. In J. Liebowitz (Ed.), Online learning analytics (pp. 1–18). Auerbach Publications. https://doi.org/10.1201/9781003194620 

This chapter critically reflects the current state of research in learning analytics and educational assessment. Given the omnipresence of technology-enhanced assessment approaches, vast amounts of data are produced in such systems, which open further opportunities for advancing assessment and feedback systems as well as pedagogical assessment practice. A yet-to-be-solved limitation of learning analytics frameworks is the lack of a stronger focus on dynamic or real-time assessment and feedback, as well as the improvement of learning environments. Therefore, a benefits matrix for analytics-enhanced assessment is suggested, which provides examples on how to harness data and analytics for educational assessment. Further, a framework for implementing analytics-enhanced assessment is suggested. The chapter concludes with a critical reflection on current challenges for making use of analytics data for educational assessments. Clearly, stakeholders in the educational arena need to address ethics and privacy issues linked to analytics-enhanced assessments.

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