Künstliche Intelligenz im Lehr-Lernprozess von MINT-Fächern: Vom adaptiven Lernmaterial zur Implementation in die Lehrkräftebildung.

In the course of increasing heterogeneity, individualized and personalized learning and adaptive instruction materials play an increasing role in classroom education. Technological developments allow new approaches to personalization by using non-invasive sensors that diagnose cognitive preferences, predispositions, as well as resources of learners during the learning process and predict learning success in real time using AI algorithms and provide assistance in this regard. The paper describes an adaptive system for STEM education, planned and partially developed that provides individualized learning materials using visual attention data and AI algorithms. In addition to tracking the learning process, the paper also describes how the system can be used to train prospective and in-service teachers to use and assess such systems. [ABSTRACT FROM AUTHOR]