Experimental Evidence on the Learning Impact of Generative AI

Zara Contractor () and Germán Reyes
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Zara Contractor: Middlebury College

No 18792, IZA Discussion Papers from IZA Network @ LISER

Abstract: We study how generative AI affects student learning in a randomized experiment. In proctored, in-person sessions, undergraduates learn about an unfamiliar topic and write an analytical essay with or without access to off-the-shelf generative AI, then complete unaided assessments immediately and one week later. We measure learning with knowledge tests (factual and conceptual understanding) and open-ended essays (higher-order skills). AI access raises immediate test scores by 0.27 standard deviations. These gains persist one week later. Essay quality, by contrast, changes little while students have AI access but improves in style and relevance one week later, when students write unaided. These delayed gains are larger among augmentation users—who use AI to explain concepts rather than generate text—whereas automation users' short-run quality gains vanish once AI is removed. We find evidence for two mechanisms behind the learning gains: students shift time away from drafting text and toward reading and searching for information, and they report greater learning enjoyment.

Keywords: generative AI; human capital; learning; higher education; randomized experiment (search for similar items in EconPapers)
JEL-codes: C93 D83 I21 I23 J24 O33 (search for similar items in EconPapers)
Date: 2026-07
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