Research on the AIGC-assisted Instructional Model of Intergrating Computational Thinking in STEM Education

Computational thinking (CT) is crucial in the smart era and cultivating students' CT has attracted attention all around the world. Science, Technology, Engineering, and Math-ematics (STEM) education, focusing on the cultivation of higher-order thinking, aids CT development, with group work being the essential part of integrating CT in STEM education. The advent of artificial intelligence in generative content (AIGC) offers new opportunities for improving CT, especially in self-learning and group work. Thus, this study aims to construct an AIGC-assisted instructional design model of integrating CT in STEM education to enhance students' CT learning while providing them with a good experience of group work. Based on that, we developed a course and conducted a two-week quasi-experiment in a senior high school in the South area of China. Data analysis showed that the students were very satisfied with the instructional design model and their CT was significantly improved with the assistance of AIGC in STEM contexts. This study provides some evidence for AIGC-assisted STEM education that supports the development of CT skills and and to provide a reference for AIGC to support teachers in conducting STEM courses.