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Amidst the rapid evolution of intelligent technology clusters—including large language models, virtual reality, and educational big data—this paper proposes the imperative to enhance AI literacy among college teachers as a cornerstone of digital competence development. We propose a three-tiered competency framework, named ‘Tool Application → Behavior Transformation → Innovative Design’, to transition educators from technical operators to intelligent instructional designers. Current challenges include outdated perceptions of AI, uneven technical proficiency, inadequate training resources, and limited pedagogical integration. To address these, we construct a multidimensional AI literacy framework spanning five domains: 1) cognitive understanding of AI fundamentals, 2) pedagogical integration through instructional design, 3) discipline-specific applications via industry collaboration, 4) ethical governance, and 5) educational innovation. Implementation strategies emphasize blended training models, tiered skill development, hands-on tool practice, case-based learning, and ethical education. A dual-perspective evaluation system (teacher-student feedback loops) assesses training efficacy and instructional outcomes. The study establishes an innovative dual-core driven platform architecture comprising the Teacher Development Cloud Platform and the Subject-Specific Tool Box, aiming to enhance teaching capabilities and discipline-specific application competencies. The research provides actionable pathways for advancing educators’ AI competencies, supporting digital transformation in higher education, and fostering sustainable ‘AI + Education’ ecosystems. Findings underscore the critical role of structured competency development in bridging technological potential with pedagogical innovation.
Yu et al. (Tue,) studied this question.