Developing AI Education Competency Framework: A Systematic Literature Review

Artificial Intelligence (AI) is rapidly transforming education, yet many institutions lack a comprehensive framework to integrate AI effectively. This paper develops an AI Education Competency Framework to guide the integration of AI in educational settings through a systematic literature review. Methodologically, a rigorous systematic literature review (SLR) was conducted following PRISMA guidelines, ensuring methodological rigor and empirical grounding. Key databases (e.g., Google Scholar, IEEE Xplore, SpringerLink) were searched for studies on AI frameworks in education, yielding 21 relevant sources. The analysis resulted in a novel framework which is built on four pillars—Foundation, Integration, Innovation, and AI Citizenship, encompassing fundamental AI knowledge, curricular and administrative integration, AI-driven innovation in pedagogy, and ethical AI use. The proposed framework informed by findings from these studies, addressing gaps such as the lack of unified approaches that combine technical, pedagogical, and ethical dimensions. The framework provides a holistic strategy for AI integration in education, including for open and distance education contexts, bridging theoretical and practical aspects. In discussion, we highlight the framework’s contributions in filling identified gaps, its potential implementation challenges, and recommendations for educators and policymakers. The study concludes that the AI Education Competency Framework offers significant contributions by aligning AI advancements with educational competencies, ensuring stakeholders are prepared to navigate AI’s complexities responsibly and effectively.