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arXiv · 2505.24126

How Students (Really) Use ChatGPT: Uncovering Experiences Among Undergraduate Students

Tawfiq Ammari·Meilun Chen·S M Mehedi Zaman·Kiran Garimella
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Abstract

We examine how undergraduate students integrate ChatGPT into everyday self-directed learning, analyzing 10,536 naturalistic messages donated by 36 students over a year. A sequential mixed-methods pipeline pairs iterative qualitative coding with zero-shot language-model annotation validated against human labels (kappa = 0.75-0.91). It yields a five-category taxonomy: Information Seeking, Content Generation, Language Use, Student-ChatGPT Interaction, and ChatGPT Response Behavior. Time-lagged linear regression and Cox proportional-hazards models link these categories to sustained engagement. Three findings stand out. First, structured tasks (theory application, code writing, job-application content, multiple-choice questions) predict continued use; ChatGPT becomes incorporated into academic rhythms when gratifications are reliably fulfilled. Second, system-issued "apologies" are the strongest positive predictor of increased engagement, outweighing every task-completion predictor. We name this mechanism "repair gratification": the reward of a breakdown acknowledged and repaired rather than a task simply completed. Third, interactional strain--prompt revision, frustration, follow-up clarification--predicts disengagement. When managing the system falls on the user without system accountability, students abandon the tool. We interpret these results through Self-Directed Learning, Uses and Gratifications Theory, and Expectancy Violations Theory, mapping predictors onto positive/negative violations and confirmations. We close with design recommendations for graduated repair patterns, mode-aware interaction, and verification affordances, and outline a participatory AI-literacy agenda for higher education.

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Tawfiq Ammari, Meilun Chen, S M Mehedi Zaman, Kiran Garimella. 2025-05-30. How Students (Really) Use ChatGPT: Uncovering Experiences Among Undergraduate Students. https://arxiv.org/abs/2505.24126

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