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What Students Can Learn About Artificial Intelligence – Recommendations for K-12 Computing Education

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Towards a Collaborative Society Through Creative Learning (WCCE 2022)

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 685))

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Abstract

Technological advances in the context of digital transformation are the basis for rapid developments in the field of artificial intelligence (AI). Although AI is not a new topic in computer science (CS), recent developments are having an immense impact on everyday life and society. In consequence, everyone needs competencies to be able to adequately and competently analyze, discuss and help shape the impact, opportunities, and limits of artificial intelligence on their personal lives and our society. As a result, an increasing number of CS curricula are being extended to include the topic of AI. However, in order to integrate AI into existing CS curricula, what students can and should learn in the context of AI needs to be clarified. This has proven to be particularly difficult, considering that so far CS education research on central concepts and principles of AI lacks sufficient elaboration. Therefore, in this paper, we present a curriculum of learning objectives that addresses digital literacy and the societal perspective in particular. The learning objectives can be used to comprehensively design curricula, but also allow for analyzing current curricula and teaching materials and provide insights into the central concepts and corresponding competencies of AI.

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Authors and Affiliations

  1. TUM School of Social Sciences and Technology, Computing Education Research Group, Technical University of Munich, Munich, Germany

    Tilman Michaeli

  2. Computing Education Research Group, Freie Universität Berlin, Berlin, Germany

    Ralf Romeike & Stefan Seegerer

Authors
  1. Tilman Michaeli
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  2. Ralf Romeike
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  3. Stefan Seegerer
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Correspondence to Tilman Michaeli .

Editor information

Editors and Affiliations

  1. School of Education, La Trobe University, Deepdene, VIC, Australia

    Therese Keane

  2. Education and Social Research Institute, Manchester Metropolitan University, Manchester, UK

    Cathy Lewin

  3. University of Duisburg-Essen, Essen, Germany

    Torsten Brinda

  4. Istituto Tecnologie Didattiche, Consiglio Nazioanale delle Ricerche, Genoa, Genova, Italy

    Rosa Bottino

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Michaeli, T., Romeike, R., Seegerer, S. (2023). What Students Can Learn About Artificial Intelligence – Recommendations for K-12 Computing Education. In: Keane, T., Lewin, C., Brinda, T., Bottino, R. (eds) Towards a Collaborative Society Through Creative Learning. WCCE 2022. IFIP Advances in Information and Communication Technology, vol 685. Springer, Cham. https://doi.org/10.1007/978-3-031-43393-1_19

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  • DOI: https://doi.org/10.1007/978-3-031-43393-1_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-43392-4

  • Online ISBN: 978-3-031-43393-1

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