A Structural Causal Analysis of Teaching Quality in Higher Education Institutions in Shanxi, China

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👤 Haojing Linghu
🏢 Ph.D. in Educational Administration, Faculty of Business Administration, Southeast Asia University, Bangkok 10160, Thailand
👤 Xizhe Zhang
🏢 Lecturer, Ph. D., Faculty of Business Administration, Southeast Asia University, Bangkok 10160, Thailand

The purpose of this study was to construct and verify the causal model of teaching quality in Shanxi universities, and to systematically analyze the direct and indirect impacts of teacher training and development, teacher evaluation system, policy reform, university management policy, teacher development and student learning effectiveness on teaching quality. The study used questionnaires, in-depth interviews and field observations to collect data, covering teachers, students and administrators of three public undergraduate universities in Shanxi Province.
Through structural equation model analysis, the study reveals the complex relationship and action path between various variables and finds that teacher training and development plans and education management policies indirectly affect teaching quality through teacher evaluation system and university management policy, while teacher development and student learning effectiveness show a significant direct impact. The results of this study not only enrich the theoretical system in the field of teaching quality in colleges and universities but also provide empirical basis and practical suggestions for the optimization of education management policies, the support of teachers' professional development and the improvement of students' learning experience in Shanxi universities. At the same time, the study emphasizes the key role of policy implementation, fairness of resource allocation and teacher incentive mechanism in promoting the improvement of teaching quality, which has important theoretical value and practical significance.

Linghu, H., & Zhang, X. (2026). A Structural Causal Analysis of Teaching Quality in Higher Education Institutions in Shanxi, China. Artificial Intelligence in Learning, 2(3). Retrieved from https://ail.mbicore.com/index.php/ail/article/view/61

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