When Attention Fails but Grades Do Not: Attentional Vulnerability, AI Compensation, and Resilience in College Students with ADHD

Attention-Deficit/Hyperactivity Disorder (ADHD) presents substantial challenges in higher education, including elevated mind wandering, difficulties sustaining attention during academic reading, and diminished self-regulatory capacity. Yet, many students with ADHD achieve academic outcomes comparable to their neurotypical (NT) peers, suggesting that protective and compensatory mechanisms may help decouple attentional vulnerability from distal academic achievement. This study examined whether artificial intelligence (AI) tools may function as compensatory support for college students with ADHD and whether resilience is differentially associated with academic success in this population. A sample of 195 engineering students (ADHD = 84, NT = 111) completed self-report measures of trait mind wandering, boredom proneness, self-efficacy, resilience, return-to-focus ability, AI usage and motivation, alongside Raven’s Progressive Matrices, an academic reading task with attention probes and comprehension questions, and end-of-semester course grades. Students with ADHD reported significantly greater AI usage than NT students (d = 0.32), despite no significant group differences in cognitive ability or course grades. Hierarchical regression showed that once attentional traits were included, diagnostic group membership no longer accounted for AI usage, indicating that attentional vulnerability, particularly elevated mind wandering, rather than diagnosis per se, may better explain AI usage. Self-efficacy was positively associated with AI usage among students with ADHD but not among NT students, though this group difference was not statistically significant; the pattern is therefore reported as tentative rather than as an established compensatory mechanism. Resilience was lower among students with ADHD than among NT students but was not associated with course grade in either group, and neither resilience nor AI usage was independently associated with course grade once cognitive ability and attentional traits were accounted for. These findings suggest that AI use may reflect compensatory academic adaptation to attentional vulnerability in ADHD. More broadly, the results highlight how attentional vulnerability, self-efficacy, AI-based compensatory strategies, and resilience jointly shape academic outcomes in ADHD and raise questions about how equitable, AI-supported learning environments might be designed in higher education. Because the design is cross-sectional, the present data do not establish that AI use improves academic achievement.