Jundan Wang
2025.5.12International Journal of Web-Based Learning and Teaching Technologies
tlooto Summary
The results show that AI teaching mainly improves teaching quality indirectly through enhancing student motivation and improving teacher expertise, rather than directly, differs from the traditional view that AI teaching directly enhances teaching quality.
Abstract
This study analyzed the impact of AI teaching on teaching quality, and revealed the mediating effect of student motivation and teacher expertise in the relationship of AI teaching and teaching quality.Based on the AI-TPACK theory, this study explored the impact of AI teaching on teaching quality and its mediating mechanism using questionnaires and AMOS structural equation modeling. The results show that AI teaching mainly improves teaching quality indirectly through enhancing student motivation and improving teacher expertise, rather than directly. This finding differs from the traditional view that AI teaching directly enhances teaching quality and emphasizes the important roles of students and teachers in AI teaching environments. The study provides some insights for educational policy makers and school administrators, pointing out that when implementing AI teaching strategies, emphasis should be placed on stimulating student learning motivation and teacher expertise growth in order to promote the optimization of teaching quality.
Citation format
WANG, Jundan. The impact of AI teaching on teaching quality. International Journal of Web-Based Learning and Teaching Technologies, 2025.