Investigation of Artificial Intelligence Self-Efficacy of Prospective Elementary Mathematics Teachers in Terms of Some Variables
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https://doi.org/10.5281/zenodo.14279357Keywords:
Artificial intelligence, Self-efficacy, Prospective mathematics teachersAbstract
The aim of this study is to examine the self-efficacy perceptions of prospective elementary mathematics teachers towards the use of artificial intelligence according to gender, grade, receiving training on artificial intelligence and using an artificial intelligence program before. The research was designed in descriptive survey model. The study group of the research consists of 82 prospective teachers studying in the undergraduate and graduate programs of elementary mathematics teaching in the 2024-2025 academic year. The data were collected with the Artificial Intelligence Self-Efficacy Scale (AIES) developed by Wang and Chuang (2023) and adapted into Turkish by Uyan and Gültekin (2024). In the study, frequency, percentage, arithmetic mean, standard deviation, t-test for independent groups and Anova test were used to determine the self-efficacy perceptions of prospective elementary mathematics teachers towards the use of artificial intelligence and the differences of these perceptions according to variables. As a result of the analyses, it was determined that pre-service elementary mathematics teachers' perceptions of efficacy towards the use of artificial intelligence were generally at a moderate level. On the other hand, it was determined that pre-service teachers' AI self-efficacy perception levels did not show a significant difference for gender and class variables, but showed a significant difference according to the status of receiving training on artificial intelligence and using artificial intelligence before.
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