New Perspectives in Science Education

Preparatory courses in chemistry play a crucial role in bridging the gap between prior knowledge acquired in school and the disciplinary as well as methodological requirements of university-level chemistry programs. [1] With the increasing integration of generative AI systems into learning and working processes, the question arises as to how propaedeutic courses can be designed to provide both subject-specific support and structured training in the reflective and responsible use of AI. [2-5]

This contribution presents a didactic framework for integrating AI elements into a chemistry preparatory course. Core components include a systematic task design, the use of AI-supported learning methods, the targeted development of critical AI competence ('Critical AI Literacy'), and an accompanying evaluation cycle for empirical monitoring and iterative course improvement. The framework takes into account the typical conditions of propaedeutic formats - such as limited course duration, heterogeneous learner groups, high content density, and varying levels of methodological skills - and illustrates these through concrete examples of task formats, assessment logic, and structured reflection opportunities.

The objective of this project is to develop a practical and transferable model for employing AI not as a substitute for disciplinary learning, but as a didactically controlled tool that fosters subject-specific, methodological, and reflective competencies in the introductory phase of university studies.