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      New digital laboratories of experimental knowledge production: Artificial intelligence and education research

      research-article
      London Review of Education
      UCL Press
      artificial intelligence (AI), algorithms, data, experts, infrastructure
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            Abstract

            Education data scientists, learning engineers and precision education specialists are new experts in knowledge production in educational research. By bringing together data science methodologies and advanced artificial intelligence (AI) systems with disciplinary expertise from the psychological, biological and brain sciences, they are building a new field of AI-based learning science. This article presents an examination of how education research is being remade as an experimental data-intensive science. AI is combining with learning science in new ‘digital laboratories’ where ownership over data, and power and authority over educational knowledge production, are being redistributed to research assemblages of computational machines and scientific expertise.

            Author and article information

            Journal
            lre
            lre
            London Review of Education
            LRE
            UCL Press (UK )
            1474-8479
            21 July 2020
            : 18
            : 2
            : 209-220
            Affiliations
            [1]University of Edinburgh, UK
            Author notes
            Corresponding author: Email: ben.williamson@ 123456ed.ac.uk
            Author information
            https://orcid.org/0000-0001-9356-3213
            Article
            10.14324/LRE.18.2.05
            992eaf61-35dd-454e-aa17-f9f8216b381b
            Copyright © 2020 Williamson

            This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY) 4.0 https://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

            History
            : 17 October 2019
            : 16 March 2020
            Page count
            References: 31, Pages: 13

            Education,Assessment, Evaluation & Research methods,Educational research & Statistics,General education
            experts,infrastructure,algorithms,data,artificial intelligence (AI)

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