Towards strengthening links between learning analytics and assessment: challenges and potentials of a promising new bond

Dragan Gašević, Samuel Greiff, David Williamson Shaffer

Research output: Contribution to journalEditorialOtherpeer-review

39 Citations (Scopus)

Abstract

Learning analytics uses large amounts of data about learner interactions in digital learning environments to understand and enhance learning. Although measurement is a central dimension of learning analytics, there has thus far been little research that examines links between learning analytics and assessment. This special issue of Computers in Human Behavior highlights 11 studies that explore how links between learning analytics and assessment can be strengthened. The contributions of these studies can be broadly grouped into three categories: analytics for assessment (learning analytic approaches as forms of assessment); analytics of assessment (applications of learning analytics to answer questions about assessment practices); and validity of measurement (conceptualization of and practical approaches to assuring validity in measurement in learning analytics). The findings of these studies highlight pressing scientific and practical challenges and opportunities in the connections between learning analytics and assessment that will require interdisciplinary teams to address: task design, analysis of learning progressions, trustworthiness, and fairness – to unlock the full potential of the links between learning analytics and assessment.

Original languageEnglish
Article number107304
Number of pages7
JournalComputers in Human Behavior
Volume134
DOIs
Publication statusPublished - Sept 2022

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