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KI und Musik in der Lehre - Ein musikwissenschaftliches Projekt der Universität des Saarlandes (UdS)

Authors: Pascal Schmolenzky; Stephanie Klauk;

KI und Musik in der Lehre - Ein musikwissenschaftliches Projekt der Universität des Saarlandes (UdS)

Abstract

Mit der Veröffentlichung von ChatGPT durch das US-amerikanische Unternehmen OpanAi im vergangenen Jahr erhielt der durch die Coronakrise ausgelöste Digitalisierungsschub in der Hochschullehre einen neuen Impuls. Als Reaktion darauf wurde an der Universität des Saarlandes die Initiative "KI in der Lehre" ins Leben gerufen, die Teil des seit 2021 von der Stiftung Innovation in der Hochschullehre geförderten Projekts Digital Teaching Plug-in (DaTa-Pin) bildet. Herausforderungen und Möglichkeiten der Nutzung von KI sollen in innovativen Lehr- und Lernangeboten erprobt und ausgelotet, im Idealfall in Best-Practice-Ansätze überführt werden. Die Besonderheit des von der Fachrichtung Musikwissenschaft betreuten Teilprojekts "KI und Musik" bildet sein multimodaler Ansatz. Im Gegensatz zu vielen anderen geisteswissenschaftlichen Fächern sind dort KI-Anwendungen nicht auf Schrift oder Texte beschränkt, sondern beziehen Ton und Musik mit ein. In diesem Beitrag werden das auf zwei Semester angelegte Teilprojekt und erste Ergebnisse vorgestellt.

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Keywords

Paper, Geisteswissenschaften, KI, Lehre, Musik, Werkzeuge, DHd2024, Musikwissenschaft, Projekte, Posterpräsentation, Ton, Text

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green