SYSTEMATIC REVIEW article
Front. Educ.
Sec. Digital Education
Volume 10 - 2025 | doi: 10.3389/feduc.2025.1648661
Artificial Intelligence in Higher Education (AIHE): A systematic review of their impact on student engagement and the mediating role of teaching methods
Provisionally accepted
- 1Department of Student Affairs, Jiaying University, Meizhou, China
- 2Faculty of Social Sciences and Liberal Arts, UCSI University, Cheras, Malaysia
- 3Shanxi Province Optoelectronic Information Science and Technology Laboratory, Yuncheng University, Yuncheng, China
- 4Institute of Computer Science and Digital Innovation, UCSI University, Cheras, Malaysia
- 5Department of Foreign Languages, Jiaying University, Meizhou, China
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Artificial Intelligence (AI) is increasingly integrated into higher education to personalize instruction and support student engagement. However, the mediating role of teaching methods in this process remains underexplored. This systematic review analyzed 73 peer-reviewed articles published between 2015 and early 2025, retrieved from Scopus and Web of Science, following PRISMA guidelines. Studies were screened based on predefined inclusion criteria and coded using a structured framework that examined AI types, engagement outcomes, and instructional strategies. Findings reveal that AI tools-such as chatbots, adaptive systems, and predictive analytics-enhance engagement most effectively when embedded within interactive pedagogies like flipped classrooms, project-based learning, and scaffolded feedback loops. To conceptualize this relationship, we introduce the PMAISE model (Pedagogical Mediation of AI for Student Engagement), which maps the alignment between AI technologies, pedagogical strategies, and the affective, behavioral, and cognitive dimensions of engagement. Concrete examples from recent studies demonstrate how teaching methods amplify or inhibit the effects of AI tools. The review also critically examines emerging concerns related to ethics, data privacy, and structural barriers to equitable AI adoption. This study offers a conceptual and practical framework for integrating AI into higher education in a context-sensitive, evidence-based, and pedagogically meaningful manner, highlighting the crucial role of thoughtful pedagogical mediation in maximizing AI's educational benefits.
Keywords: Artificial intelligence (AI), higher education, student engagement, teaching methods, Pedagogical mediation, Education quality
Received: 20 Jun 2025; Accepted: 10 Sep 2025.
Copyright: © 2025 Long, Wang and Lu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Shuai Wang, Shanxi Province Optoelectronic Information Science and Technology Laboratory, Yuncheng University, Yuncheng, China
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