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Data Mining and Analytics in the Context of Workplace Learning: Benefits and Affordances

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Methods for Researching Professional Learning and Development

Part of the book series: Professional and Practice-based Learning ((PPBL,volume 33))

Abstract

Technology-based innovations in workplace learning have significantly altered both the scale and resolution of measurements for supporting learning processes in organisations. The increased availability of vast and highly varied amounts of data from settings in the context of workplace learning is overwhelming. This chapter outlines standards in data mining with a specific focus on data from workplace learning. Further, different data mining and analytics methodologies, such as Support Vector Machines or Decision Trees, are presented. An emphasis is shifted to the understanding of learning analytics which are a socio-technical data-mining and analytic practice in educational contexts. The chapter closes with an outlook on how data mining and analytics may provide benefits for future workplace learning scenarios.

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Authors and Affiliations

  1. Learning, Design and Technology, University of Mannheim, Mannheim, Germany

    Dirk Ifenthaler

  2. UNESCO Deputy Chair on Data Science in Higher Education Learning and Teaching, Curtin University, Perth, WA, Australia

    Dirk Ifenthaler

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  1. Dirk Ifenthaler
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Editors and Affiliations

  1. Institute of Educational Science, Paderborn University, Paderborn, Germany

    Michael Goller

  2. Centre for Transformative Innovation, Swinburne University of Technology, Melbourne, VIC, Australia

    Eva Kyndt

  3. Department of Education, University of Jyväskylä, Jyväskylä, Finland

    Susanna Paloniemi

  4. Department of Education, University of Oslo, Blindern, Oslo, Norway

    Crina Damşa

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Ifenthaler, D. (2022). Data Mining and Analytics in the Context of Workplace Learning: Benefits and Affordances. In: Goller, M., Kyndt, E., Paloniemi, S., Damşa, C. (eds) Methods for Researching Professional Learning and Development. Professional and Practice-based Learning, vol 33. Springer, Cham. https://doi.org/10.1007/978-3-031-08518-5_14

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