# Faster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They Build

arXiv: https://arxiv.org/abs/2605.21629 · HTML: https://mlsanity.com/paper/2605.21629/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 30 references that are in the map.
- First posted on arXiv 20 May 2026.

## Builds on (most cited first, 2 of 2)

- [Sparks of Artificial General Intelligence: Early experiments with GPT-4](https://mlsanity.com/paper/2303.12712/) (2023)
- [AI Assistance Reduces Persistence and Hurts Independent Performance](https://mlsanity.com/paper/2604.04721/) (2026)

## Built on by (most cited first, 1 of 1)

- [Designing Against Deskilling: Metacognitive Feedback Reduces Cognitive Offloading to LLM Assistants](https://mlsanity.com/paper/2609.20143/) (2026)

## Abstract (arXiv)

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 investigating time-on-task, complemented by ALEKS PPL placement-assessment data for examining proctoring and learning outcomes, with a quasi-experimental design exploiting variation in tasks that are more susceptible to AI (text-based word problems) and less susceptible to AI (interactive graph-based problems). 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. Among college students, the post-ChatGPT divergence vanishes entirely under proctoring, ruling out broad efficiency gains as the likely explanation. 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 cognitive surrender, with direct implications for educational research, assessment governance, and AI policy.