AI Systematic Review
Today, I would like to share a recent AI SoTL article by Figueroa de la Fuente and Farhadian (2025) entitled, “Systematic review of the impact of AI in higher education. Journal of Teaching and Learning” which provides a comprehensive systematic literature review (SLR) of AI. The study spans 243 studies published between 2017 and 2025. Using the PRISMA framework and advanced text-mining tools, the authors mapped trends, challenges, and opportunities emerging. Their analysis positions AI as a transformative but unevenly adopted force in global higher ed, balancing efficiency, personalization, and ethical complexity.
The study connects AI’s integration to the broader goals of flexible, student-centered, and lifelong learning. Drawing on frameworks from UNESCO (2023) and OECD (2025), the authors highlight the imperative for human-centered, equitable, and transparent AI governance. The review synthesized peer-reviewed and credible non-peer-reviewed literature. Data were analyzed through both quantitative modeling and qualitative interpretation, yielding insights into dominant research patterns. AI tools were used transparently to refine text clarity but not to conduct analysis, ensuring methodological integrity.
Findings
Five primary themes emerged from the literature:
Ethical Governance and Academic Integrity – The most recurrent theme, focusing on fairness, transparency, algorithmic bias, and plagiarism. Many studies called for institutional AI ethics policies but found limited actionable frameworks (Fowler, 2023).
Institutional Practices and Policy Development – Universities are integrating AI into administration and pedagogy but face challenges related to regulation, infrastructure, and staff readiness (Ahmed et al., 2025).
Learning Outcomes – AI can improve personalization and engagement but evidence of long-term cognitive or motivational gains remains inconclusive (Bond et al., 2024).
Faculty Teaching and PD – Faculty adoption is hindered by autonomy concerns, limited AI literacy, and lack of institutional support (Gibson, 2024).
Emerging Focus on AI Tools – AI tools are reshaping writing support, raising questions about authorship, originality, and human-AI collaboration (Cavazos et al., 2024).
Quantitative trend analysis revealed an exponential growth in AI scholarship, especially after 2023. The most urgent priorities identified include:
AI Governance and Ethical Regulation
Personalized Learning and Student Success
Faculty AI Literacy and Training
Student Mental Health and Digital Well-being
Institutional Decision-Making and Policy Integration
The authors argue that AI adoption in higher education is not a purely technological endeavor it is a political, ethical, and cultural transformation. The review calls for participatory governance involving students, faculty, and communities to ensure equitable outcomes. Without this shift, institutions risk technocratic policy making and widening digital divides. The authors advocate for longitudinal, theory-driven, and context-sensitive research to evaluate AI’s real impact across diverse learning environments.
Reference
Figueroa de la Fuente, M., & Farhadian, G. (2025). Systematic review of the impact of AI in higher education. Journal of Teaching and Learning, 19(4), 72–96.