Empowering university teachers in higher education: A generative AI-responsive competency framework

The integration of generative artificial intelligence (GenAI) into higher education necessitates a reconceptualization of teacher competencies, moving beyond technical proficiency to encompass pedagogical strategies for fostering critical, ethical, and developmentally appropriate student-AI collaboration. Existing competency frameworks, however, exhibit notable limitations in equipping university teachers with actionable guidance for designing GenAI-mediated learning experiences that cultivate their students’ higher-order thinking and subject knowledge. In response, this paper develops and proposes a GenAI-responsive competency framework for university teachers to supplement existing frameworks and address areas that are not sufficiently covered or elaborated. Developed through a systematic analysis of digital and AI-related competency frameworks, the proposed model is grounded in constructivist learning theory, sociological perspectives, and student-centered pedagogy. Its theoretical and practical robustness was further refined through iterative expert review and consultation. The resulting framework comprises four core dimensions: GenAI Literacy, Curriculum/Learning Design, Teaching and Learning, and Assessment. Each dimension is articulated through a dual perspective: teachers’ own proficiency and their capacity to foster students’ critical engagement with GenAI. Competency progression is structured across three developmental levels: Basic, Intermediate, and Advanced, representing a continuum from technical awareness to guided application, and ultimately to critical and creative integration. The proposed framework supports teachers’ ongoing professional growth and enhances their ability to facilitate student autonomy, ethical reasoning, and collaborative engagement with GenAI. It provides a structured yet flexible tool for self-assessment, instructional design, and targeted professional development in higher education, thereby advancing the discourse on effective and responsible human-AI collaboration.