Potenciál a limity integrácie AI v matematickej príprave budúcich učiteľov primárneho vzdelávania

The study focuses on profiling pre-service teacher students in the context of artificial intelligence (AI) use and openness to digital forms of learning. The aim was to compare groups of students according to their level of AI experience and to identify barriers and potential for didactic intervention in undergraduate teacher education. The research sample consisted of 112 students enrolled in a study programme focused on primary education teaching. Three indices were analysed: openness to AI integration (AI_OPEN), AI use proficiency (AI_SKILL), and attitudes toward podcasts as a learning tool (POD_LEARN). Differences between groups based on the frequency of AI use were tested using the Kruskal–Wallis test; comparisons between users and non-users were conducted with the Mann–Whitney U test; and the relationship between AI experience and the use of AI in mathematics was verified using a chi-square (χ²) test. The results showed significant and practically relevant differences in AI_OPEN and AI_SKILL in favour of regular users, with differences being more pronounced in skills than in openness. In contrast, attitudes toward podcasts did not differ significantly across groups, suggesting that willingness to engage in audio-based learning is relatively independent of AI experience. AI experience was also reflected in subject-specific use – the proportion of students using AI for mathematics increased with the frequency of AI use. The findings support the need for targeted support especially for occasional and less experienced students through AI onboarding, the development of practical skills, and modelling safe scenarios for AI use in mathematics.