Evidence of a Cognitive Shift in AI Education: How Students Are Rethinking Human Intelligence?
For AI educators and curriculum designers, this reveals a cognitive shift in student perceptions of intelligence, impacting learner autonomy and epistemic agency.
A longitudinal study of 471 students from 2020-2026 found that initial hype and trust in AI shifted toward a preference for human intelligence (HI), with HI preference reaching 65% in technical courses and 90% in design-oriented courses by 2026, suggesting a reappraisal of HI as AI becomes routine.
Perceptions of intelligence shape how learners evaluate and rely on artificial intelligence (AI) systems. Despite rapid advances in AI capabilities, the impact of sustained exposure to these tools on students' valuation of human intelligence (HI) relative to AI remains underexplored. This paper presents a longitudinal analysis of classroom poll responses collected between 2020 and 2026 in AI-focused undergraduate and MSc courses in computer science. Data from 471 students across technical courses (such as Machine Learning and Deep Graph Learning) and design-oriented courses (such as Design Thinking for AI) reveal four recurring phases: hype, distrust, trust, and dependency. While early responses in 2020 slightly favored AI, a consistent shift toward HI emerged from 2024 onward across all MSc cohorts. By 2026, preference for HI reached 65 percent in a technical course (a 12 percentage-point increase from 2025) and 90 percent in a design-oriented course (a 36 percentage-point increase). These findings suggest a gradual reappraisal of human intelligence as AI becomes a routine tool, with implications for learner autonomy and epistemic agency. We conclude by reflecting on this cognitive shift from favoring artificial intelligence toward prioritizing human intelligence.