Leifi project of the JHS (Joachim Herz Foundation)
Prototype for learning physics with the support of artificial intelligence.
Goals/target group
The project aims to develop and test an adaptive, AI-based learning setting for physics lessons at secondary level 1. This involves preparing a topic from physics lessons using material from the free learning platform www.leifiphysik.de. The effectiveness of the prototype developed will be examined in a field study and compared with conventional teaching approaches. The project thus contributes to the identification of learning-promoting features for the design of adaptive, AI-based learning environments in the field of physics.
Contents
The digital transformation is permanently changing many parts of our society. In education, the digital transformation offers the opportunity to radically reshape teaching and learning processes. New technological approaches are opening up new opportunities for teaching and learning. It is the task of subject didactics to develop suitable digitally-supported teaching and learning scenarios and to test their learning effectiveness. In this way, empirically proven knowledge can be gained about the success factors and benefits of digitally supported teaching and learning scenarios.
In the context of individual learning in particular, technologies based on artificial intelligence (AI) represent a promising approach. These adaptive systems analyze the learning process in the background and offer learners appropriate assistance if required. In this way, the learning environment is individually adapted to the learner's needs and, at best, learning success is increased.
As part of the project described here, such an adaptive, AI-based learning setting (prototype) for physics is to be developed and tested in practice. For this purpose, a topic from secondary level 1 physics lessons will be developed. The content will be based on material from the free learning platform www.leifiphysik.de. The adaptive system developed will be examined for its learning effectiveness in a field study and compared with the learning effectiveness of other (conventional approaches). The project thus contributes to the identification of learning-promoting features for the design of adaptive, AI-based learning environments in the context of physics.