Factors Affecting Student Learning Outcomes in the Context of an Art and Science Program Integrated with Artificial Intelligence

As artificial intelligence (AI) has been rapidly adopted in educational fields, significant efforts have been made to foster the integration of AI into K-12 educational contexts. In this study, we aimed to design and implement a science, technology, engineering, arts, and mathematics (STEAM) educational program that incorporates AI under the theme of space exploration and to examine the relationships among the factors affecting student learning outcomes. Two hundred and twenty-seven seventh graders participated in the AI-STEAM program under the theme of space exploration. Students were invited to respond to an instrument examining self-efficacy, task value, learning engagement, and several learning outcome variables. Path analysis was conducted to verify the appropriateness of the set path and to investigate the relationship between variables. The results indicate that students’ self-efficacy in learning AI had a significant direct impact on their learning engagement and an indirect impact on learning satisfaction and career aspiration to AI fields. Additionally, students’ perception of task value and learning engagement directly affected their learning satisfaction and career aspiration to AI fields. Interestingly, students’ conceptual understanding of AI was not directly or indirectly predicted by any factors. The results provide pedagogical implications for teaching practitioners in designing and implementing AI-integrated lessons in curriculums.