Content area
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.
Details
Educational Practices;
Literature Reviews;
Educational Research;
Learning Motivation;
Junior High School Teachers;
Expertise;
Literacy;
Cooperative Learning;
Concept Teaching;
Artificial Intelligence;
Student Motivation;
Educational Environment;
Course Content;
Learner Engagement;
Educational Strategies;
Algorithms;
Educational Quality;
Competence;
Intelligent Tutoring Systems;
Influence of Technology;
Distance Education;
Mathematics Education;
Educational Facilities Improvement;
Individual Needs
Education policy;
Collaboration;
Student teacher relationship;
Student participation;
Policy making;
Teachers;
Motivation;
Distance learning;
Technology;
Knowledge;
Personalized learning;
Impact analysis;
Optimization;
Algorithms;
Learning;
Education;
Digital literacy;
Pedagogy;
Experts;
Structural equation modeling;
Teaching methods;
Strategies;
Artificial intelligence;
Learning outcomes;
Students;
Administrators