Teaching in the Age of Generative AI: A Qualitative Analysis of Faculty Identity, Emotion, and Assessment Concerns

Abstract

The rise of generative AI, particularly large language models like ChatGPT, has profoundly impacted higher education. While debates have centered on academic integrity, curriculum design, and the future of work, less attention has been paid to the affective dimensions of this shift—specifically, how university educators are emotionally experiencing and responding to these transformations. Drawing on affect theory, cognitive dissonance, identity theory, and assessment theory, this study explores the affective experiences of university teachers in response to AI’s integration into teaching and learning. Thematic analysis was conducted using Braun and Clarke’s method, and NVivo 14 was used to support the coding process for 20 faculty members’ in-depth interviews. Three core themes emerged that encapsulate faculty members’ affective experiences with AI integration in higher education. These interconnected themes are as follows: (1) Erosion of Pedagogical Identity, (2) Emotional Disruption and Cognitive Dissonance, and (3) Assessment Anxiety and Distrust. The thematic analysis reflected the profound psychological and emotional challenges educators face asthey navigate the rapid adoption of AI technologies in their teaching practices. Findings suggest that institutional response to AI must engage with the emotional labor and subjectivities of teachers, not just the technological infrastructure of learning. Ignoring the human side of AI adoption risks burnout and resistance. Recommendations made to achieve sustainable solutions include providing psychological support for identity shifts, fostering collaborative policy-making with faculty input, and balancing AI adaptability with trust-building in assessment.

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