Abstract

AbstractThe paper argues that learning analytics as a research field can benefit from a theory‐informed shared language to describe sensemaking of learning and teaching data. To make the case for such shared language, first, I critically review prominent sensemaking theories to then demonstrate how studies in learning analytics do not use coherent descriptions of sensemaking, eclectically combining the paradigms that have underlying differences. I then propose a conceptualization of sensemaking that overcomes the differences between these theories and explains how the concepts of activity system, the definition of the situation and affordances can be used to capture individual differences in sensemaking. The paper concludes with a preliminary framework and examples demonstrating its utility in raising new theoretical questions, informing design principles and providing shared language for researchers in learning analytics.Practitioner notesWhat is already known about this topic Sensemaking happens when individuals try to explain unknown situations. Learning analytics uses sensemaking as a lens to understand dashboard use. Systematic analysis of sensemaking is essential for learning analytics. What this paper adds The paper notes that noticing and perceiving are commonly examined in learning analytics on dashboard use. The paper suggests a revision of fundamental assumptions in sensemaking. A paper proposes a toy model of sensemaking that includes operationalization of the definition of the situation, activity where sensemaking happens and processes of noticing and perceiving affordances. Implications for practice and/or policy Learning analytics must examine sensemaking of data about teaching and learning in a systematic manner. Internal perceptions of the social environment and activity that are informed by the data need to be considered in evaluating dashboard use.

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