Student Perspectives on Teacher Interpersonal Behaviours in AI-Mediated Higher Education: A Q Methodology Study

Abstract

Research on artificial intelligence (AI) in higher education largely emphasises technical performance and outcomes, leaving student views of teacher interpersonal behaviours in AI-mediated classrooms insufficiently understood. In response, this study applied Q methodology, supported by content and sentiment analyses, to examine student perspectives. A total of 30 university students Q-sorted 40 statements, covering empathy, immediacy, clarity, autonomy support, engagement and personalization. Subsequently, principal component analysis with varimax rotation yielded four factors: (F0) Selective-Connection Seekers, (F1) Autonomous Collaborators, (F2) Gamification-Driven Minimalists and (F3) Clarity and Empathy Advocates. Additionally, open-ended reflections clustered into seven themes, with Clarity and Instructional Precision and Empathy and Emotional Support most frequent. At the same time, sentiment analysis showed predominantly positive-neutral tones, with some resistance to over-personalization. Overall, the findings indicated that authentic interaction, transparent criteria and profile-aligned differentiation (including targeted gamification) are pivotal for sustaining meaningful teacher-student relationships. Accordingly, several actionable suggestions were provided based on the findings.