What Students’ Use of AI Reveals about Academic Advising and Judgement

Abstract

Generative artificial intelligence (AI) is now widely discussed in higher education in relation to learning, assessment design, and academic integrity. Much of this discussion, however, treats students’ AI use as a set of discrete academic practices, rather than as part of broader decision-making that spans learning and everyday life. This piece argues that students’ academic and non-academic uses of AI increasingly shape one another, influencing how they approach uncertainty, manage emotional pressure, and make judgements when learning feels high stakes.

Drawing on academic advising and personal tutoring conversations, it shows that students are not using AI solely to generate outputs, but to talk ideas through, test interpretations, and steady their thinking when confidence and academic identity are in play. These practices closely resemble the relational and cognitive work advisers already support and make visible how AI is now being used to sustain the emotional work of learning that underpins sound judgement.

A practice-based framework is presented describing four overlapping modes of student AI use - instrumental, dialogic, metacognitive, and affective-regulatory - each aligned with established advising functions. Rather than positioning AI as a threat to academic integrity or professional judgement, the paper argues for advising as guidance: supporting students to recognise how AI shapes their thinking, to develop appropriate boundaries, and to make learning decisions with confidence and responsibility.