Personalizing STEM-learning with AI: adaptive platforms

Abstract

The modern system of STEM education is undergoing significant changes because technological progress is at the heart of this transformation. The digitalisation of the educational process offers educators and students advanced digital technologies.

The study aims to identify the features of personalisation of STEM learning using artificial intelligence, particularly adaptive platforms.

Methods. The study used the description method to describe adaptive educational platforms; the analysis method to determine teachers' attitudes towards using artificial intelligence; and the case method to determine further prospects for using artificial intelligence in education.

Results. In the course of the study, the author highlighted the changes that are taking place in the modern educational process and defined the role of the teacher in this context. The study describes such adaptive educational platforms as Siemens NX Virtual Lab, Labster, Immersive Google VR, Oculus, Pico, zSpace, Querium, PTC Creo Simulate. It is emphasised that using these platforms can adapt the learning process and provide feedback between students and teachers. Teachers' attitudes to using artificial intelligence in the educational process were analysed. The results showed that most teachers have a positive attitude towards using artificial intelligence in the learning process. The author also highlighted the positive and negative aspects of personalised learning and the prospects for using artificial intelligence in education.

The conclusions emphasize that AI technologies are already helping students to use them when choosing educational courses and programmes that will fully meet their interests. As for teachers, artificial intelligence tells them how best to present material to achieve the most favorable results. Prospects for future research are related to improving and expanding the capabilities of adaptive learning systems with artificial intelligence in STEM education.