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Towards artificial intelligence-based assessment systems

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  • Rose Luckin

    (Rose Luckin is Professor of Learner Centred Design, UCL Knowledge Lab, Institute of Education, University College London, 23–29 Emerald Street, London WC1N 3QS, UK.)

Abstract

‘Stop and test’ assessments do not rigorously evaluate a student's understanding of a topic. Artificial intelligence-based assessment provides constant feedback to teachers, students and parents about how the student learns, the support they need and the progress they are making towards their learning goals.

Suggested Citation

  • Rose Luckin, 2017. "Towards artificial intelligence-based assessment systems," Nature Human Behaviour, Nature, vol. 1(3), pages 1-3, March.
    • Handle: RePEc:nat:nathum:v:1:y:2017:i:3:d:10.1038_s41562-016-0028
    DOI: 10.1038/s41562-016-0028
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    Cited by:

    1. Aithal, Sreeramana & Aithal, Shubhrajyotsna, 2020. "Conceptual Analysis on Higher Education Strategies for various Tech-Generations," MPRA Paper 104025, University Library of Munich, Germany.
    2. Ramona Simut & Ciprian Simut & Daniel Badulescu & Alina Badulescu, 2024. "Artificial Intelligence and the Modelling of Teachers’ Competencies," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 26(65), pages 181-181, February.
    3. Aithal, Sreeramana & Aithal, Shubhrajyotsna, 2020. "Promoting Faculty and Student-Centered Research and Innovation based Excellence Model to Reimage Universities," MPRA Paper 101751, University Library of Munich, Germany.

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