KI und Sprachbildung im MINT-Unterricht

Einblicke in die Entwicklung von sprachbildenden Unterrichtsmaterialien zum Thema „Kunststoffe“ mit Unterstützung von Large Language Models

Abstract

Linguistically responsive teaching requires the combination of language and subject teaching, which calls for either dual expertise or close cooperation within the teaching staff. Organisational hurdles often prevent this, which is why language aspects are neglected in subject lessons. Artificial intelligence (AI) can provide support here, for example by creating semi-authentic texts that combine technical and linguistic requirements and are adapted to different learning levels. This article presents a STEM teaching unit on the topic of plastics for the third grade middle school (ISCED level 2) that was developed as part of a BMBWF1 project. The materials were created using generative AI, evaluated in terms of design-based research and positively received in the two evaluation rounds focussing first on learners’ grasp of the content and then on the potential of the AI-supported materials to promote subject and language learning.