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      Personalization in Australian K-12 classrooms: how might digital teaching and learning tools produce intangible consequences for teachers’ workplace conditions?

      research-article
      Australian Educational Researcher
      Springer Netherlands
      Personalisation, Teachers, Human rights, Algorithmic bias, Data

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          Abstract

          Recent negotiations of ‘data’ in schools place focus on student assessment and NAPLAN. However, with the rise in artificial intelligence (AI) underpinning educational technology, there is a need to shift focus towards the value of teachers’ digital data. By doing so, the broader debate surrounding the implications of these technologies and rights within the classroom as a workplace becomes more apparent to practitioners and educational researchers. Drawing on the Australian Human Rights Commission’s Human Rights and Technology final report, this conceptual paper focusses on teachers’ rights alongside emerging technologies that use or provide predictive analytics or artificial intelligence, also called ‘personalisation’. The lens of Postdigital positionality guides the discussion. Three potential consequences are presented as provocations: (1) What might happen if emerging technology uses teachers’ digital data that represent current societal inequality? (2) What might happen if insights provided by such technology are inaccurate, insufficient, or unrepresentative of our teachers? (3) What might happen if the design of the AI system itself is discriminatory? This conceptual paper argues for increased discourse about technologies that use or provide predictive analytics complemented by considering potential consequences associated with algorithmic bias.

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          Most cited references53

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          The Privacy Paradox: Personal Information Disclosure Intentions versus Behaviors

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            Big Data, new epistemologies and paradigm shifts

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              The social power of algorithms

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                Author and article information

                Contributors
                Janine.arantes@vu.edu.au
                Journal
                Aust Educ Res
                Aust Educ Res
                Australian Educational Researcher
                Springer Netherlands (Dordrecht )
                0311-6999
                2210-5328
                28 April 2022
                28 April 2022
                : 1-18
                Affiliations
                GRID grid.1019.9, ISNI 0000 0001 0396 9544, Victoria University, ; Footscray, Australia
                Author information
                http://orcid.org/0000-0002-0301-5780
                Article
                530
                10.1007/s13384-022-00530-7
                9047619
                06d7d608-eb21-417d-af76-96d839de82aa
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 7 April 2021
                : 5 April 2022
                Funding
                Funded by: Victoria University
                Categories
                Article

                personalisation,teachers,human rights,algorithmic bias,data
                personalisation, teachers, human rights, algorithmic bias, data

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