Fen Bilimleri Öğretmen Adaylarının YZ-TPAB Yeterlikleri ve Eğitimde Yapay Zekaya İlişkin Algılarının İncelenmesi

The primary purpose of this study is to investigate preservice science teachers’ competencies related to AI-TPACK and their perceptions regarding the use of artificial intelligence in education. By examining these constructs, the study aims to provide insights into how preservice teachers integrate AI into their pedagogical and content knowledge and how their perceptions influence this process. This study adopted a quantitative survey research design. Specifically, two standardized instruments, the AI-TPACK and Perceptions of Artificial Intelligence in Education (PAI) scales, were administered simultaneously to preservice science teachers. The participants of this study consisted of 122 undergraduate students enrolled in the science education program at the faculty of education of a public university. The findings indicate that preservice science teachers’ overall performance on the AI-TPACK scale reflected moderate competency in integrating AI into pedagogical practices. The highest mean scores highlighted willingness to integrate AI technologies into self directed learning, self-efficacy in enhancing conceptual understanding, and competence in using AI-based simulations. The findings revealed that preservice science teachers’ overall results on the PAI indicated generally positive perceptions toward AI integration in education. Preservice science teachers particularly valued AI’s contribution to efficiency, rapid assessment, and ease of access to information while noting potential drawbacks such as reduced student engagement and dependency. The analysis revealed a statistically significant positive correlation between preservice teachers’ AI-TPACK competencies and their perceptions of AI. Results also indicated that male preservice teachers scored significantly higher in several AI-TPACK subscales. At the same time, prior AI training enhanced technological knowledge but did not necessarily improve pedagogical or content-related competencies. Overall, the findings highlight the need for targeted training opportunities emphasizing hands-on, pedagogically integrated use of AI to foster more comprehensive AI-TPACK competencies.