New Perspectives in Science Education

Edition 14

Accepted Abstracts

Teaching Chemistry with AI: Insights into the Potential and Limits of ChatGPT in Lesson Planning

Michele Brott, University of Potsdam (Germany)

Abstract

The integration of artificial intelligence (AI) into education is advancing rapidly, driven by its potential to support and innovate teaching practices. The presented study “Chemistry Teaching Designed by Artificial Intelligence (CUKI)” investigates how AI, specifically ChatGPT, can assist pre-service teachers in lesson planning within chemistry education [1]. Initiated in response to the release of ChatGPT in late 2022, the project focuses on following key questions: What criteria can measure the quality of lesson plans effectively? Can ChatGPT create pedagogically high-quality chemistry lessons? How does the planning competence of users influence the outcomes? And how do pre-service teachers perceive their own skills compared to those of the AI? This presentation will outline the results of both the pilot study and the follow-up study, in which pre-service chemistry teacher first independently planned a chemistry lesson and subsequently used ChatGPT to design a lesson. The quality of these lesson plans was analyzed and examined for correlations. The respective research designs and the theory-based criteria set [e.g. 2] used for evaluating the lesson plans will also be presented. In addition, the students were surveyed about their attitudes towards AI and experiences with using ChatGPT [3]. They were also asked to evaluate both their own lesson plans and those generated with the AI. Finally, the self-assessments were compared with the external evaluations. Lastly guidelines for effective prompting to achieve high-quality results in the field of chemistry lesson planning will be presented. The presentation aims to provide insights into how AI tools can be integrated into pre-service teacher education.

Keywords

AI in Education, Chemistry Lesson Planning, ChatGPT in Teacher Traiing, Measuring Plannning Quality

 

REFERENCES

[1] Brott, M., Egerer, C. (2024): Kann ein Chatbot die Vorbereitung für den Chemieunterricht übernehmen? Eine Analyse der Qualität von Unterrichtsplanungen von ChatGPT und Chemielehramtsstudierenden. In: MNU Journal 77(2), S. 104-110

[2] König, J.; Krepf, M.; Bremerich-Vos, A.; Buchholtz, C.: Meeting Cognitive Demands of Lesson Planning: Introducing the CODE-PLAN Model to Describe and Analyze Teachers’ Planning Competence. The Teacher Educator, 56:4, 466-487.

[3] Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340

 

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