Reframing faculty development for digital transformation and generative AI in higher education

As educational digitalization continues to deepen and generative artificial intelligence rapidly enters higher education teaching contexts, faculty professional development is undergoing a profound transformation from tool use to pedagogical redesign and from individual adaptation to organizational change. However, current faculty development practices still tend to substitute standardized training for differentiated support, making it difficult to address the diverse needs of teachers at different career stages in digital competence, curricular innovation, disciplinary integration, and academic leadership. To enhance the transparency of the framework-building process, this study was informed by explicit review questions, database-based literature retrieval, and thematic synthesis. Building on scholarship on teacher digital competence, teacher professional development theory, and the practice of digital transformation in higher education, with Heilongjiang University of Chinese Medicine serving as the institutional context for framework formulation, this paper offers a systematic account of the stage-specific developmental tasks of university faculty in the digital era and advances a multi-level, developmental framework. The framework is organizationally supported by coordination across three institutional levels-university, school, and department-structured around four developmental stages: entry and adaptation, stable development, deep integration, and academic leadership, and implemented through five pathways: blended professional learning, cross-boundary linkage, community-based mutual learning, diagnostic mentoring, and evidence-informed practice. The study contends that faculty development should move beyond a narrow focus on digital tool training and instead emphasize the systematic development of capacities related to pedagogical improvement, disciplinary reconfiguration, digital ethics, and organizational leadership. This framework helps enhance the stage-specific relevance, practical explanatory power, and organizational operability of faculty development, while also providing a theoretical reference for designing faculty development systems in digitally transformed universities.