AI COMPETENCY MODEL OF TEACHERS FOR HIGHER EDUCATION INSTITUTIONS IN GUANGXI ZHUANG AUTONOMOUS REGION

Abstract

The integration of artificial intelligence (AI) into higher education has significantly transformed teaching practices and learning environments. As universities increasingly adopt AI technologies, the development of teachers’ AI competency has become a critical factor influencing educational effectiveness. This study provides a comprehensive literature review to synthesize existing research on AI competency in education and to propose a theoretical model tailored to higher education institutions in Guangxi Zhuang Autonomous Region. This review examines four key themes: theoretical foundations of AI competency, applications of AI in higher education, pedagogical frameworks including AI-TPACK and GenAI-TPACK, and institutional support for AI adoption. Through critical analysis and comparison of existing studies, this paper identifies AI competency as a multidimensional construct integrating technological literacy, pedagogical integration, ethical awareness, and reflective capacity. Unlike previous studies that primarily describe AI adoption or digital competence, this study contributes by synthesizing multiple theoretical perspectives into a unified conceptual framework. Based on this synthesis, a proposed AI competency model is developed, illustrating the relationships among institutional support, AI competency, TPACK, and teaching performance. The findings provide both theoretical contributions and practical implications for teacher professional development and intelligent education policy in higher education.