Exploring the Impact of Artificial Intelligence (AI) on Learning and Teaching Practices in Higher Education

Research Context

AI is becoming a critical driver of innovation across service industries, including education. In the UK and beyond, universities are prioritizing AI integration into learning and teaching experiences to enhance academic outcomes and institutional efficiency.

AI applications in education—such as intelligent tutoring systems, adaptive learning technologies, and personalized support—are showing promise in improving both student and teacher engagement. Despite growing evidence of AI’s potential, there remains a significant gap in research examining its impact on the teaching and learning experience.

This project aims to address this gap by exploring the perspectives of students and faculty on AI adoption and its implications for professional practice and pedagogical innovation.

Research Objectives

This PhD project will:

1. Investigate the behavioral dynamics of AI adoption in HE, focusing on both teaching and learning practices.
2. Evaluate the effectiveness of AI-based innovations on teaching delivery and student outcomes.
3. Provide actionable recommendations for universities integrating AI into their pedagogical frameworks.

Methodology

The research employs a two-stage sequential design:

• Stage One: Quantitative data will be gathered through post-project surveys on AI initiatives, featuring feedback from tutors, module leaders, and students. These surveys will assess the teaching and learning experience, including both closed and open-ended responses.
• Stage Two: Qualitative insights will be collected via semi-structured interviews informed by the findings from stage one. These interviews will delve into emerging themes, contradictions, and anomalies, providing a deeper understanding of AI’s role in HE.

Expected outcomes

The research will produce insights in two key areas:

1. Expanding theoretical and practical knowledge on AI applications in HE, focusing on behavioral and pedagogical impacts.
2. Offering actionable implications for HE institutions, including strategies to overcome teaching delivery challenges through AI technologies.

Application deadlines

• Applications for the October 2025 intake close on 1st July 2025
• Applications for the January 2026 intake close on 1st October 2025.