Questions as Data: Illuminating the Potential of Learning Analytics through Questioning an Emergent Field

Jon Mason, Weiqin Chen, Tore Hoel

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    In providing a meta-analysis of a series of workshop papers and questions arising on the emergent field of learning analytics, this paper contributes to the ongoing formation of a shared research agenda. The first ICCE Learning Analytics workshop in 2014 demonstrated the effectiveness of a focused questioning session for collecting relevant data beyond the content of the papers themselves. In December 2014, approximately 40 participants attended the workshop held in Nara, Japan, and contributed to the collection of open research questions. Six papers were presented covering topics including scope; interoperability standards; privacy and control of individual data, extracting data from learning content and processes; and the development of conceptual frameworks. These papers established a base from which the group generated a set of questions that invite further investigation. Utilising the first stage of the Question Formulation Technique, a pedagogical approach designed to stimulate student inquiry, a prominent finding from the workshop that questions emerging from focused inquiry provide a useful set of data in their own right. With an explicit workshop focus on learning analytics interoperability, this paper reports on the emergent issues identified in the workshop and the kinds of questions associated with each issue in the context of current research in the field of learning analytics. The study considers the complexity arising from the fact that data associated with learning is itself becoming a digital learning resource while also enabling analysis of learner behaviours and systems usage.
    Original languageEnglish
    Article number12
    Pages (from-to)1-14
    Number of pages14
    JournalResearch and Practice in Technology Enhanced Learning
    Publication statusPublished - 21 May 2016


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