Teachers' AI use and student learning outcomes in higher education: The roles of learning engagement and teacher AI...

As generative artificial intelligence (AI) becomes increasingly integrated into higher education, teachers are playing a central role in transforming AI technologies into educational value. However, empirical evidence regarding whether and how teachers' AI use improves student learning outcomes remains limited. Drawing on self-determination theory, this study examines the influence of teachers' AI use on student learning outcomes, focusing on the mediating role of learning engagement and the moderating role of teacher AI literacy.

A dual-study design combining experimental and survey methods was employed. Study 1 adopted a pretest-posttest experimental design involving 482 university students and 12 teachers. Teachers in the experimental group systematically integrated AI tools into instructional activities, whereas teachers in the control group adopted conventional teaching approaches. To strengthen causal inference, learning engagement and learning outcomes were measured at different time points. Study 2 employed a multi-wave teacher-student matched survey design based on 97 teachers and 816 students from Chinese higher education institutions. Teacher AI literacy was reported by teachers, whereas students evaluated teachers' AI use, learning engagement, and learning outcomes. Mediation, moderation, and moderated mediation analyses were conducted using Bootstrap procedures.

The results consistently showed that teachers' AI use positively predicts student learning outcomes. Learning engagement significantly mediates the relationship between teachers' AI use and learning outcomes, indicating that teachers' AI use enhances learning outcomes by increasing students' cognitive, behavioral, and emotional engagement in learning. Furthermore, teacher AI literacy positively moderates the relationship between teachers' AI use and learning engagement. Specifically, the positive effect of teachers' AI use on learning engagement is stronger when teachers possess higher levels of AI literacy. In addition, teacher AI literacy strengthens the indirect effect of teachers' AI use on student learning outcomes through learning engagement.

This study contributes to the educational AI literature in three ways. First, it extends self-determination theory to AI-assisted teaching contexts and provides a theoretical explanation of how AI is transformed into learning value. Second, it identifies learning engagement as a key mechanism linking teachers' AI use and student learning outcomes, thereby advancing understanding of learning processes in AI-supported education. Third, by integrating experimental and survey evidence and incorporating teacher AI literacy as a boundary condition, this study offers a more comprehensive explanation of when and how teachers' AI use contributes to student learning success. The findings provide practical implications for AI-enabled teaching reform, teacher professional development, and higher education digital transformation.