Policy guidelines and recommendations on AI use in teaching and learning: A meta-synthesis study - Aaron A. Funa; Renz Alvin E. Gabay (Social Sciences and Humanities Open)
As artificial intelligence becomes increasingly integral to educational systems, understanding policy guidelines and recommendations from various sources is crucial. This meta-synthesis examines AI policies and guidelines from peer-reviewed articles, reports, books, and websites from 2020 to 2024, with a focus on their implications for teaching and learning. Using a thematic analysis approach, the study categorizes findings into key themes and subthemes. Under the theme of policies and guidelines, notable subthemes include ethical AI use, AI literacy, and inclusivity and equity. In terms of implementation strategies, the synthesis identifies crucial areas such as student orientation and professional development, enhanced teaching tools and data-driven insights, improved student learning outcomes and engagement, and streamlined administrative processes. The study also determines practical constraints that challenge the successful integration of AI in education, including technical and integration challenges, training and support issues, ethical and fairness concerns, cost and accessibility, transparency and privacy issues, and misalignment with educational goals. Future research may explore the long-term impacts of AI integration policies and guidelines, refine practical implementation strategies, and foster collaboration among researchers, educators, and policymakers to tackle ongoing challenges and maximize AI's potential in education.