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    Künstliche Intelligenz in der Hochschulbildung

    Chancen und Grenzen des KI-gestützten Lernens und Lehrens

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    Contributor(s)
    Schmohl, Tobias (editor)
    Watanabe, Alice (editor)
    Schelling, Kathrin (editor)
    Language
    German
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    Abstract
    Der Einsatz von Künstlicher Intelligenz erfährt in hochschuldidaktischen Kontexten wachsendes Interesse. Durch individualisierte Lernwege ergeben sich für Studierende und Dozierende neue Lern-Lehr-Möglichkeiten. Der Band befasst sich jedoch auch mit den daraus resultierenden Gefahren: Es sind Demarkationslinien zu ziehen, wenn es um Datenschutz oder ethische Bedenken geht. Die Autor*innen des Bandes nehmen verschiedene Sichtweisen ein, um eine multidisziplinäre Betrachtung der neuen Problemstellungen, die die Anwendung von KI im Hochschulkontext mit sich bringt, zu ermöglichen.
    URI
    https://library.oapen.org/handle/20.500.12657/62276
    Keywords
    Künstliche Intelligenz; Hochschulbildung; Technologiegestütztes Lernen; Didaktik; Technik; Ethik; Multidisziplinarität; Bildung; Medien; Digitale Medien; Bildungsforschung; Informatik; Universität; Pädagogik; Artificial Intelligence; University Education; Technology-enhanced Learning; Didactics; Technology; Ethics; Multidisciplinarity; Education; Media; Digital Media; Educational Research; Computer Sciences; University; Pedagogy
    DOI
    10.14361/9783839457696
    ISBN
    9783839457696, 9783837657692, 9783743557697, 9783839457696
    Publisher
    transcript Verlag
    Publisher website
    https://www.transcript-verlag.de/
    Publication date and place
    Bielefeld, 2023
    Imprint
    transcript Verlag
    Series
    Hochschulbildung: Lehre und Forschung, 4
    Classification
    Media studies
    Philosophy and theory of education
    Digital and information technologies: social and ethical aspects
    Pages
    286
    Rights
    https://creativecommons.org/licenses/by-sa/4.0/
    • Imported or submitted locally

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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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