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    Intelligent analysis and data visualisation for teacher assistance tools: the case of exploratory learning

    Mavrikis, M. and Geraniou, E. and Gutierrez-Santos, Sergio and Poulovassilis, Alexandra (2019) Intelligent analysis and data visualisation for teacher assistance tools: the case of exploratory learning. British Journal of Educational Technology 50 (6), pp. 2920-2942. ISSN 0007-1013. (In Press)

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    Abstract

    While it is commonly accepted that Learning Analytics tools can support teachers’ awareness and classroom orchestration, not all forms of pedagogy are congruent to the types of data generated by digital technologies or the algorithms used to analyse them. One such pedagogy that has been so far underserved by Learning Analytics is exploratory learning, exemplified by tools such as simulators, virtual labs, microworlds and some interactive educational games. This paper argues that the combination of intelligent analysis of interaction data from such an exploratory learning environment (ELE) and the targeted design of visualisations has the benefit of supporting classroom orchestration and consequently enabling the adoption of this pedagogy to the classroom. We present a case study of learning analytics in the context of an ELE supporting the learning of algebra. We focus on the formative qualitative evaluation of a suite of Teacher Assistance tools. We draw conclusions relating to the value of the tools to teachers and reflect with transferable lessons for future related work.

    Metadata

    Item Type: Article
    Additional Information: This is the peer reviewed version of the article, which has been published in final form at the link above. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
    School: School of Business, Economics & Informatics > Computer Science and Information Systems
    Research Centres and Institutes: Birkbeck Knowledge Lab, Innovation Management Research, Birkbeck Centre for
    Depositing User: Alex Poulovassilis
    Date Deposited: 02 Sep 2019 08:01
    Last Modified: 11 Jun 2021 06:11
    URI: https://eprints.bbk.ac.uk/id/eprint/28715

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