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        Grundlagenwissen zu Künstlicher Intelligenz von angehenden Lehrkräften

        Modellbasierte Testentwicklung und Validierung

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        Author(s)
        Schmidt, Jacqueline M.-C.
        Contributor(s)
        Friese, Marianne (editor)
        Seeber, Susan (editor)
        Collection
        Knowledge Unlatched (KU); wbv OpenLibrary 2023
        Language
        German
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        Abstract
        In der Dissertation von Frau Dr.in Schmidt wird ausgehend von der zunehmenden Relevanz von Kunstlicher Intelligenz (KI) im Rahmen digitaler Transformationsprozesse ein Strukturmodell fur KI-bezogene Kompetenzfacetten (angehender) Lehrkrafte im berufsbildenden Bereich entwickelt. Das Wissen zu KI nimmt dabei in Anlehnung an die Professionalisierungsforschung eine zentrale Rolle ein. Im Rahmen der Arbeit wird der Frage nachgegangen, wie das Grundlagenwissen (angehender) Lehrkrafte theoretisch modelliert und empirisch erfasst werden kann. Das entwickelte Testinstrument wurde anhand eines quantitativen Studiendesigns umfassend validiert.
        URI
        https://library.oapen.org/handle/20.500.12657/90140
        Keywords
        Education; Adult & Continuing Education
        DOI
        10.3278/9783763976539
        ISBN
        9783763976539, 9783763976522
        Publisher
        wbv Media
        Publisher website
        https://www.wbv.de/wbv-media.html
        Publication date and place
        2024
        Grantor
        • Knowledge Unlatched
        Imprint
        wbv Media GmbH & Co. KG
        Classification
        Adult education, continuous learning
        Rights
        https://creativecommons.org/licenses/by-sa/4.0/
        • Harvested from KU

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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