Challenges and Countermeasures in Post-Pandemic Teacher Performance Management: Insights from Public Universities in Hong Kong, China
DOI:
https://doi.org/10.71222/rayy4027Keywords:
teacher performance management, post-pandemic era, blended teaching, resource allocation, incentive mechanismsAbstract
This study focuses on the impact of the blended teaching model on higher education management in the post-pandemic era. Taking eight public universities in Hong Kong, China as cases, it deeply explores the challenges and optimization paths faced by teacher performance management through qualitative research methods. The research adopted a multi-case design and conducted semi-structured interviews with 32 interdisciplinary teachers and 8 administrative managers. Combined with the thematic analysis method, three core issues were identified: The deficiency of the incentive mechanism was manifested as 70% of the respondents pointed out that the rigid senior-salary system was difficult to reflect the value of teaching innovation, and the interdisciplinary achievements had insufficient weight in the promotion evaluation; The imbalance in resource allocation was manifested in 80% of the participants confirming that there was a severe disciplinary bias (for example, business monopolized 70% of the digital teaching budget, and the internship opportunities in science and engineering were eight times that of humanities), resulting in a satisfaction rate of humanities teachers as low as 2.3/5. The insufficiency of professional development support is prominently reflected in the fact that 77.5% of teachers lack training in blended teaching skills (such as asynchronous interaction and LMS data analysis), and 55% believe that mental health support is absent. Based on the emergent theory, the transformational leadership theory and the framework of the TPACK model, a systematic countermeasure is studied and proposed: reconstructing dynamic performance indicators and adopting the Analytic Hierarchy Process (AHP) to integrate dimensions such as the flexibility of online teaching and the application of technology; Establish a performance-oriented resource allocation mechanism and promote fairness through interdisciplinary special funds; Build a teacher learning community to provide customized technical training and psychological support; Innovate diverse incentives such as linking salary with teaching innovation achievements and establishing social impact awards. These measures have been initially verified for effectiveness through practices such as the development of AI courses at the University of Hong Kong, China and the resource pooling at the Hong Kong University of Science and Technology, and can provide a paradigm reference for global higher education institutions to build a resilient performance management system. Future research needs to expand cross-cultural comparisons and long-term tracking to deepen the applicability of the theory.
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