AI-supported instructional design and preservice teachers’ perceived metacreativity: a mixed-methods study

This study examined the role of an artificial intelligence (AI)-supported instructional program in relation to preservice teachers’ attitudes toward AI, perceived metacreativity skills, and academic achievement in an undergraduate Philosophy of Education course. A convergent parallel mixed-methods design was employed. Quantitative data were collected using pretest-posttest measures from an experimental group ( n = 22) and a control group ( n = 28), while qualitative data were obtained through reflective journals and written responses to open-ended questions. In the experimental group, positive attitudes toward AI increased significantly from pretest to posttest. Significant increases were also observed in four perceived metacreativity subdimensions: Comprehending the Main Problem and Sub-Problems, Reconstructing Connections, Finding Solutions, and the Affective Dimension. No significant pretest-posttest changes in attitudes toward AI or perceived metacreative skills were found in the control group. After controlling for pretest scores, the groups did not differ significantly in attitudes toward AI, whereas significant differences favoring the experimental group were found in Reconstructing, Evaluation, Finding and Affective subdimensions. Academic achievement increased significantly in both groups, suggesting that general course learning may also have contributed to the gains; however, the adjusted posttest scores favored the experimental group. The qualitative findings highlighted Creativity and Perspective Change, with participants reporting greater perceived creativity and new perspectives, although some reported limited change. The results suggest that AI-supported activities in teacher education should encourage preservice teachers to compare alternatives, revise AI-generated content, justify their decisions, and evaluate their final products. The results should be interpreted cautiously because the study involved a relatively small sample from a single public university in Türkiye. The practical recommendations should also be adapted to local institutional contexts and student populations.