Enhancing Pre-service Teachers’ Scientific Inquiry Questioning through Generative AI-Supported Scaffolding

This study examined pre-service science teachers’ scientific inquiry questioning ability and the types of inquiry questions generated before and after participating in learning activities using an AI-supported scaffolding strategy. A one-group pretest-posttest design was employed. The research instruments consisted of (1) learning activities using an AI-supported scaffolding strategy, (2) a situational assessment of scientific inquiry questioning ability, and (3) criteria for evaluating scientific inquiry questions. The findings revealed that students’ scientific inquiry questioning ability improved from a moderate level before the intervention to a high level after the intervention, with the difference being statistically significant at the .05 level. In addition, the predominant type of students’ questions shifted from reasoning questions before the intervention to predictive or forecasting questions after the intervention. Students also reported that AI-generated feedback, together with instructor guidance, helped them identify weaknesses and refine their scientific inquiry questions. These findings suggest that AI-supported scaffolding can serve as a practical approach for supporting pre-service science teachers and science educators in designing learning activities that promote scientific inquiry in 21st-century classrooms.