Pre-service mathematics teachers' use of artificial intelligence: an extended technology acceptance model with self-efficacy (the case of ChatGPT)

Introduction This study examines pre-service mathematics teachers' use of ChatGPT in instructional processes within the framework of the Technology Acceptance Model (TAM), extended with pedagogical AI self-efficacy. The study investigates the relationships among perceived ease of use, perceived usefulness, attitudes toward use, actual use, and self-efficacy regarding the use of ChatGPT in mathematics teaching. Methods The study was conducted with 167 pre-service mathematics teachers. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results The findings revealed that perceived ease of use significantly predicted perceived usefulness (β = 0.648, p < 0.001) and directly influenced actual use (β = 0.311, p < 0.001). Perceived usefulness significantly predicted attitudes toward use (β = 0.638, p < 0.001), while attitudes toward use significantly affected actual use (β = 0.399, p < 0.001). In addition, pedagogical AI self-efficacy strongly predicted perceived ease of use (β = 0.647, p < 0.001) and indirectly contributed to technology acceptance. Discussion The findings confirm the explanatory power of TAM in the context of generative AI tools and highlight the critical role of self-efficacy in shaping pre-service teachers' acceptance of ChatGPT. The study provides important implications for the integration of AI tools into mathematics teacher education and supports the pedagogically grounded use of generative AI in teaching practices.