Feeling AI: Circulating emotions, institutional climates, and moral boundaries in student use of AI

Abstract

This study investigates how students emotionally and morally engage with artificial intelligence (AI) in higher education (HE). Through a sociotechnical lens of AI and drawing on a Sara Ahmed’s frame of affective economies, we report on a national survey (n = 8021) with qualitative focus groups (n = 79) to explore the emotional textures of student experiences. Quantitative findings reveal strong co-occurrences of optimism with excitement, reflecting students’ positive anticipatory engagement with AI. However, these emotions often unfolded alongside scepticism and worry, highlighting a pervasive ambivalence. Qualitative narratives show how emotions like relief, guilt, gratitude, and vigilance circulate around AI, particularly in relation to assessment, learning, and creativity and voice. The analysis illuminates how emotions emerge from and reflect institutional affective climates that mobilise pride, shame, and moral anxiety to enforce academic norms. In this context, AI becomes an affective actor entangled with individualised ideals of effort and authenticity, and embedded in relational negotiations around trust, surveillance, and belonging. Students are negotiating complex affective and moral decisions when engaging with AI in their studies. We argue for a shift toward critical affective literacy in HE to foster spaces for emotional and ethical dialogue that enable pedagogical trust and support students as reflective, morally engaged learners.

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