Abstract:How much have students' ordinary learning processes shifted in response to generative AI, and how does that affect their durable learning outcomes? Self-report surveys show little change, while small-scale behavioral studies report widespread AI use without the scale or duration to measure learning consequences. We address both questions using a ten-year panel of $3.2$ million ALEKS learning interactions for the time-on-task analysis, complemented by ALEKS PPL placement-assessment data for the proctoring and retention analyses, with a quasi-experimental design exploiting within-curriculum variation in AI susceptibility: text-based word problems transcribable into AI prompts serve as the treated group; graph-based problems requiring interactive platform manipulation as the comparison. Learning time on AI-susceptible problems declines $2.8\%$ per quarter among college students after ChatGPT's release, cumulating to $26.9\%$ over eleven quarters; high-schoolers show $31.3\%$, middle-schoolers $9.0\%$, and Grade 5 students no detectable change. The divergence vanishes entirely under proctoring for college students, making general efficiency gains unlikely. Logistic fixed-effects models on randomly assigned proctored retention items yield a $25\%$ cumulative decline in odds of correct response; the same estimator on non-proctored assessment produces a large opposite-signed increase -- inconsistent with any platform, cohort, or curriculum explanation. These results are among the first large-scale behavioral and outcome evidence that generative AI has altered how students study and the knowledge they build -- the population-level indicator of \emph{cognitive surrender}, with direct implications for educational research, assessment governance, and AI policy.
| Subjects: | Computers and Society (cs.CY); Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC) |
| Cite as: | arXiv:2605.21629 [cs.CY] |
| (or arXiv:2605.21629v1 [cs.CY] for this version) | |
| https://doi.org/10.48550/arXiv.2605.21629 arXiv-issued DOI via DataCite (pending registration) |
From: Sina Rismanchian [view email]
[v1]
Wed, 20 May 2026 18:40:53 UTC (400 KB)
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