Relationships among AI Competency, AI Anxiety, and Inquiry-Based Teaching among Science Teachers

Abstract

As Artificial Intelligence (AI) becomes increasingly integrated into science education, questions of teacher preparedness and emotional response come to the fore. This quantitative study explored three key dimensions: (a) the levels of AI competency and anxiety among secondary science teachers, (b) differences in these levels based on school location and teaching experience, and (c) how these factors relate to the use of structured, guided, and open inquiry-based teaching practices. A total of 136 teachers from a Malaysian state participated in the study by completing validated Likert-scale surveys. Results showed that teachers generally reported moderate levels of AI competency (M = 3.65, SD = 0.69) and AI-related anxiety (M = 3.24, SD = 0.64). Among the inquiry approaches, guided inquiry was most used, followed by structured and open formats. A multivariate analysis of variance (MANOVA) revealed that teaching experience had a significant influence on combined competency and anxiety levels, with teachers in the 6–10 years’ experience range reporting the highest competency. School location did not impact competency but did have a small, statistically significant effect on anxiety, with higher levels reported among rural teachers. Correlation analyses further indicated small but positive relationships between AI competency and all three inquiry styles, whereas anxiety showed no significant association with inquiry use. These findings point to AI competency rather than anxiety as the key driver of inquiry-based teaching involving AI. The study highlights the need for targeted professional development that builds classroom-ready AI skills, enhances assessment literacy, and addresses contextual challenges in rural settings.