Evidence of a Cognitive Shift in AI Education: How Students Are Rethinking Human Intelligence?
Islem Rekik

TL;DR
This longitudinal study reveals a significant shift in students' perceptions, increasingly valuing human intelligence over AI in educational settings from 2024 onward, indicating a reappraisal of AI's role.
Contribution
The paper provides empirical evidence of a cognitive shift in AI education, highlighting changing student attitudes towards human intelligence versus AI over six years.
Findings
Preference for human intelligence increased to 65% in technical courses by 2026.
Preference for human intelligence increased to 90% in design courses by 2026.
Students' perception shifted from AI hype to valuing human intelligence as AI tools became routine.
Abstract
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…
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