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Does AI Help or Hurt Learning?

Author

Listed:
  • Franco, Catalina

    (Center for Applied Research (SNF) at NHH – Norwegian School of Economics)

  • Irmert, Natalie

    (Department of Economics, Lund University)

  • Isaksson, Siri

    (Burgundy School of Business Groupe ESC Dijon Bourgogne - CEREN)

Abstract

AI is transforming how students learn, raising concerns about whether it expands educational opportunities or widens existing gaps. We examine this question in a preregistered lab experiment (N=572) in which students study a novel topic under one of three conditions: browsing only (control), AI-assisted, or AI-guided, and then complete an exam without AI access. We find no overall effect of AI access on learning outcomes. However, this average zero effect masks substantial heterogeneity. High GPA women appear to benefit the most from AI-guided access, while the effects on men and low-GPA students are weaker and in some cases negative. We also find that students with AI access attempt fewer practice questions during the study phase. This suggests that studying with AI crowds out other learning activities, but does not lead to an overall change in exam performance. Finally, exploratory analyses of prompt data provide suggestive evidence on why some students benefit more than others. More delegative AI use (measured by copy-pasting practice questions into the chatbot) is associated with attempting more questions but performing worse on the final exam. High-GPA women rely on this strategy the least and perform the best. Overall, AI appears to crowd out some traditional study effort without reducing learning on average, but because its benefits are concentrated among already advantaged students, it may reinforce existing educational inequalities

Suggested Citation

  • Franco, Catalina & Irmert, Natalie & Isaksson, Siri, 2026. "Does AI Help or Hurt Learning?," Working Papers 2026:2, Lund University, Department of Economics.
    • Handle: RePEc:hhs:lunewp:2026_002
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    References listed on IDEAS

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    1. Zachary A Pardos & Shreya Bhandari, 2024. "ChatGPT-generated help produces learning gains equivalent to human tutor-authored help on mathematics skills," PLOS ONE, Public Library of Science, vol. 19(5), pages 1-18, May.
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      JEL classification:

      • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
      • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
      • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
      • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
      • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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