Access Timing as Scaffolding: A Reinforcement Learning Approach to GenAI in Education
A recent study explores the timing of access to generative AI (GenAI) in educational settings. The research indicates that strategically timed access can enhance learning outcomes and metacognitive engagement compared to unrestricted or completely restricted access. This approach offers a new pedagogical framework for integrating GenAI into education effectively.
- ▪The study involved 105 participants and utilized a reinforcement learning agent to determine optimal access timing for GenAI.
- ▪Results showed that timed access improved post-test performance and reduced task errors compared to unrestricted access.
- ▪No significant differences were found in self-reported metacognitive awareness across different access conditions.
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| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.15850 |
| Publication time | Mon, 18 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-18T04:04:54.418Z |
| Last seen | 2026-05-18T04:04:54.418Z |
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Computer Science > Computers and Society arXiv:2605.15850 (cs) [Submitted on 15 May 2026] Title:Access Timing as Scaffolding: A Reinforcement Learning Approach to GenAI in Education Authors:Janne Rotter, Pau Benazet i Montobbio, Davinia Hernández-Leo View a PDF of the paper titled Access Timing as Scaffolding: A Reinforcement Learning Approach to GenAI in Education, by Janne Rotter and 2 other authors View PDF HTML (experimental) Abstract:In recent years, generative AI (GenAI) in educational settings has become ubiquitous in students' daily lives, despite its potential to induce over-reliance, metacognitive disengagement, and diminished learning when used unrestrictedly.
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