AI in Higher Education: A Comprehensive Review

Published Date : 10/09/2025 

Artificial Intelligence (AI) is revolutionizing higher education by personalizing instruction and enhancing student engagement. This systematic review explores the role of teaching methods in maximizing AI's impact. 

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. The 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.

In summary, the integration of AI in higher education is not just about adopting new technologies but also about aligning these technologies with effective teaching methods. The PMAISE model provides a roadmap for educators to navigate this complex landscape and ensure that AI truly enhances the learning experience for all students. 

Frequently Asked Questions (FAQS): 

Q: What is the PMAISE model?

A: The PMAISE model stands for Pedagogical Mediation of AI for Student Engagement. It maps the alignment between AI technologies, pedagogical strategies, and the affective, behavioral, and cognitive dimensions of engagement.

Q: How does AI enhance student engagement?

A: AI tools such as chatbots, adaptive systems, and predictive analytics enhance student engagement by personalizing instruction and providing timely feedback, especially when integrated with interactive pedagogies like flipped classrooms and project-based learning.

Q: What are the key concerns related to AI in education?

A: Key concerns include ethics, data privacy, and structural barriers to equitable AI adoption. These issues need to be addressed to ensure that AI is used responsibly and benefits all students.

Q: What is the role of teaching methods in AI integration?

A: Teaching methods play a crucial role in maximizing the impact of AI. Interactive and student-centered approaches, such as flipped classrooms and project-based learning, can amplify the benefits of AI tools and enhance student engagement.

Q: What is the main finding of the systematic review?

A: The main finding is that AI tools are most effective in enhancing student engagement when they are embedded within interactive pedagogies. The PMAISE model provides a framework for aligning AI technologies with pedagogical strategies to achieve this goal. 

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