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Article . 2025
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Zeitschrift SEMINAR
Article . 2025 . Peer-reviewed
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Generative KI-Sprachmodelle im Berufsschulunterricht: Chancen und Herausforderungen für inklusives Lernen in heterogenen Lerngruppen

Anwendung von KI-Sprachmodellen im Berufsschulunterricht bei Lernenden mit sonderpädagogischem Förderbedarf
Authors: Anastasia-Gloria Roloff; Stephanie Grundmann;

Generative KI-Sprachmodelle im Berufsschulunterricht: Chancen und Herausforderungen für inklusives Lernen in heterogenen Lerngruppen

Abstract

Der Beitrag analysiert die Einsatzmöglichkeiten generativer KI-Sprachmodelle (LLM) im inklusiven Berufsschulunterricht und diskutiert die damit verbundenen Chancen und Herausforderungen. Large Language Models (LLM) besitzen insbesondere für Lernende mit sonderpädagogischem Förderbedarf Potenziale zur Unterstützung individueller Lernprozesse, jedoch bestehen zugleich Barrieren hinsichtlich der erforderlichen KI-Kompetenzen sowie bei der kritischen Reflexion generierter Inhalte. Vor diesem Hintergrund wird das Dimensionskompetenzraster-Modell, das fünf zentrale Dimensionen für den Einsatz von LLM im Unterricht systematisiert, vorgestellt: Technologisches Wissen, Anwendung von Hard- und Software, Prompt-Erstellung, Quellenbewertung und KI als Lernstrategie. Der Beitrag skizziert didaktische Anpassungsstrategien zur Implementierung von LLM in heterogenen Lerngruppen und zeigt auf, wie diese Technologie zur Förderung von Lernprozessen beitragen kann, ohne bestehende Bildungsungleichheiten zu verstärken.

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Keywords

KI-gestützte Unterrichtsplanung, Inklusiver Unterricht, Lehrkräftequalifizierung, Künstliche Intelligenz in der Bildung, Seiten- und Quereinsteiger im Schuldienst

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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
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