ArticleFrontiers in psychology2026
Research on the optimization of the training system of university faculty development centers in the context of GenAI: a comparative analysis based on Chinese and Kazakhstani universities.
Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: This mixed-methods field study examined generative artificial intelligence (GenAI) pedagogical readiness among university faculty in five participating universities in China and Kazakhstan, with particular attention to cross-sample differences and the effects of faculty development training. Methods: Baseline survey data were collected from 568 faculty members, including 340 from China and 228 from Kazakhstan. Readiness was assessed across seven dimensions: basic GenAI understanding, prompt design, AI-supported instructional design, AI-supported assessment, critical judgement, educational ethics, and disciplinary transfer. A quasi-experimental subsample of 160 faculty members compared structured GenAI prompt-task training with conventional GenAI-focused faculty development. Prompt logs were additionally coded to identify post-training faculty development needs. Results: At baseline, the Kazakhstani sample reported higher readiness across all seven dimensions, with the largest differences in disciplinary transfer, prompt design, and basic understanding. Measurement-invariance analysis supported cross-sample comparison of observed mean patterns. In hierarchical regression, the Kazakhstan coefficient decreased from Discussion: The findings indicate that GenAI pedagogical readiness is shaped by faculty course tasks, institutional support, resource access, and training design. Structured prompt-task training may therefore provide a useful approach to strengthening course-level faculty readiness for pedagogical uses of GenAI.
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