AI for Teaching and Learning in Higher Education: A 2020–2025 Systematic Review

• In Event: Teaching and Learning in a Time of Artificial Intelligence (AI)

Abstract

This study systematically reviews 53 empirical studies published between 2020 and 2025 to examine the availability, awareness, adoption, and efficacy of artificial intelligence (AI) in higher education. Guided by the Diffusion of Innovations (DOI) theory, it explores stakeholder attitudes, tool usage patterns, and educational outcomes. The findings highlight ChatGPT as the most studied tool, generally positive user attitudes, and varied adoption influenced by demographic and contextual factors. While AI supports cognitive and instructional gains, concerns persist about overreliance and reduced critical thinking. The review identifies research gaps in educational collaboration tools, underrepresented disciplines, and regional imbalances, offering evidence-based recommendations for AI integration, policy design, and equitable access in higher education.

Authors

• Xinting Wu, Florida State University

• Shouping Hu, Florida State University

• Joe O'shea, Florida State University

• Ziyue Meng, Florida State University