שימוש בבינה מלאכותית באקדמיה הישראלית

The current study examined the relationships between motivations for using artificial intelligence tools, self-efficacy, and academic motivation among 131undergraduate students at higher education institutions in Israel. The study was conducted to understand how the increasing use of artificial intelligence tools in Israeli academia affects key psychological and educational processes. Structured questionnaires were used to measure motivation to learn (AMS), general self-efficacy (GSE), and use of artificial intelligence tools (QAIUM). The main findings showed significant positive relationships between self-efficacy for using artificial intelligence tools (r = .25), intrinsic motivation for using these tools (r = .28), and extrinsic motivation for using them (r = .32). Interestingly, extrinsic motivation was more dominant (M = 4.73) than intrinsic motivation (M = 4.39), indicating a pragmatic use of these tools. Significant gender differences were found, with men reporting higher intrinsic motivation and use of AI tools. Surprisingly, no relationships were found between age or year of study and the study variables. Regression analyses revealed that extrinsic motivation and self-efficacy are the main factors predicting use of AI tools. The study highlights the importance of fostering self-efficacy and developing intrinsic motivation for optimal implementation of AI tools in the Israeli higher education system.This study examined the relationships between motivations for using artificial intelligence tools, self-efficacy, and learning motivation among 131 undergraduate students in Israeli higher education institutions. The research aimed to understand how the increasing use of AI tools in Israeli academia affects key psychological and educational processes. Validated questionnaires were used to measure learning motivation (AMS), general self-efficacy (GSE), and AI tool usage (QAIUM). Main findings revealed significant positive correlations between self-efficacy and AI tool usage (r = .25), between intrinsic motivation and AI usage (r = .28), and between extrinsic motivation and AI usage (r = .32). Notably, extrinsic motivation was more dominant (M = 4.73) than intrinsic motivation (M = 4.39), indicating pragmatic use of these tools. Significant gender differences were found, with males reporting higher intrinsic.