Toward a Digital-Enabled Evaluation Model for Graduate Education Quality: A Study of Chinese Universities - Yue Liao; Jing Quan; Shiyan Chen; Can Zeng (International Journal of Humanities, Education, and Social Sciences, 2026)
In the context of high-quality development in higher education, evaluating graduate education quality has become increasingly important for assessing the cultivation of high-level talent. This study aimed to construct a graduate education quality evaluation system grounded in comprehensive competency development, encompassing five key dimensions: digital awareness, digital technology knowledge and skills, digital application, digital social responsibility, and professional development. The study employed the Analytic Hierarchy Process to determine indicator weights, Data Envelopment Analysis to measure institutional efficiency across China, panel regression to identify factors influencing educational value-added, and K-means clustering to reveal patterns of resource allocation. The findings indicate that digital technology knowledge and skills, together with digital application, carry the highest weights in the evaluation system. The results further show substantial variation in efficiency across institution types and regions, while also demonstrating that high investment does not necessarily translate into high educational value-added, thereby underscoring the importance of resource utilization efficiency and appropriate training models. The study concludes that a more differentiated evaluation mechanism and optimized resource allocation are necessary to enhance graduate education quality. These findings provide a scientific basis for improving graduate education evaluation and offer practical implications for policy and institutional quality enhancement.