IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp18055.html
   My bibliography  Save this paper

Generative AI in Higher Education: Evidence from an Elite College

Author

Listed:
  • Contractor, Zara

    (Middlebury College)

  • Reyes, Germán

    (Middlebury College)

Abstract

Generative AI is transforming higher education, yet systematic evidence on student adoption remains limited. Using novel survey data from a selective U.S. college, we document over 80 percent of students using AI academically within two years of ChatGPT's release. Adoption varies across disciplines, demographics, and achievement levels, highlighting AI's potential to reshape educational inequalities. Students predominantly use AI for augmenting learning (e.g., explanations, feedback), but also to automate tasks (e.g., essay generation). Positive perceptions of AI's educational benefits strongly predict adoption. Institutional policies can influence usage patterns but risk creating unintended disparate impacts across student groups due to uneven compliance.

Suggested Citation

  • Contractor, Zara & Reyes, Germán, 2025. "Generative AI in Higher Education: Evidence from an Elite College," IZA Discussion Papers 18055, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp18055
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp18055.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bresnahan, Timothy F. & Trajtenberg, M., 1995. "General purpose technologies 'Engines of growth'?," Journal of Econometrics, Elsevier, vol. 65(1), pages 83-108, January.
    2. Esther Duflo & Michael Kremer & Jonathan Robinson, 2011. "Nudging Farmers to Use Fertilizer: Theory and Experimental Evidence from Kenya," American Economic Review, American Economic Association, vol. 101(6), pages 2350-2390, October.
    3. Lori Beaman & Ariel BenYishay & Jeremy Magruder & Ahmed Mushfiq Mobarak, 2021. "Can Network Theory-Based Targeting Increase Technology Adoption?," American Economic Review, American Economic Association, vol. 111(6), pages 1918-1943, June.
    4. Benjamin Bushong & Tristan Gagnon-Bartsch, 2024. "Failures in Forecasting: An Experiment on Interpersonal Projection Bias," Management Science, INFORMS, vol. 70(12), pages 8735-8752, December.
    5. Philippe Jehiel, 2018. "Investment Strategy and Selection Bias: An Equilibrium Perspective on Overoptimism," American Economic Review, American Economic Association, vol. 108(6), pages 1582-1597, June.
    6. Daron Acemoglu, 2025. "Nobel Lecture: Institutions, Technology, and Prosperity," American Economic Review, American Economic Association, vol. 115(6), pages 1709-1748, June.
    7. Philip Oreopoulos & Daniel Lang & Joshua Angrist, 2009. "Incentives and Services for College Achievement: Evidence from a Randomized Trial," American Economic Journal: Applied Economics, American Economic Association, vol. 1(1), pages 136-163, January.
    8. repec:osf:osfxxx:h6a7c_v1 is not listed on IDEAS
    9. Andrew D. Foster & Mark R. Rosenzweig, 2010. "Microeconomics of Technology Adoption," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 395-424, September.
    10. Edward Felten & Manav Raj & Robert Seamans, 2021. "Occupational, industry, and geographic exposure to artificial intelligence: A novel dataset and its potential uses," Strategic Management Journal, Wiley Blackwell, vol. 42(12), pages 2195-2217, December.
    11. Otis, Nicholas G. & Cranney, Katelyn & Delecourt, Solene & Koning, Rembrand, 2024. "Global Evidence on Gender Gaps and Generative AI," OSF Preprints h6a7c, Center for Open Science.
    12. Erik Brynjolfsson & Danielle Li & Lindsey Raymond, 2025. "Generative AI at Work," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 140(2), pages 889-942.
    13. Kathryn Bonney & Cory Breaux & Cathy Buffington & Emin Dinlersoz & Lucia S. Foster & Nathan Goldschlag & John C. Haltiwanger & Zachary Kroff & Keith Savage, 2024. "Tracking Firm Use of AI in Real Time: A Snapshot from the Business Trends and Outlook Survey," NBER Working Papers 32319, National Bureau of Economic Research, Inc.
    14. Robert W. Fairlie & Florian Hoffmann & Philip Oreopoulos, 2014. "A Community College Instructor Like Me: Race and Ethnicity Interactions in the Classroom," American Economic Review, American Economic Association, vol. 104(8), pages 2567-2591, August.
    15. Hall, Bronwyn H. & Khan, Beethika, 2003. "Adoption of New Technology," Department of Economics, Working Paper Series qt3wg4p528, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    16. Alexander Bick & Adam Blandin & David Deming, 2023. "The Rapid Adoption of Generative AI," On the Economy 98843, Federal Reserve Bank of St. Louis.
    17. Ed Felten & Manav Raj & Robert Seamans, 2023. "How will Language Modelers like ChatGPT Affect Occupations and Industries?," Papers 2303.01157, arXiv.org, revised Mar 2023.
    18. Grant Goehring & Filippo Mezzanotti & S. Abraham (Avri) Ravid, 2024. "Technology Adoption and Career Concerns: Evidence from the Adoption of Digital Technology in Motion Pictures," NBER Working Papers 32844, National Bureau of Economic Research, Inc.
    19. Erik Brynjolfsson & Lorin M. Hitt, 2000. "Beyond Computation: Information Technology, Organizational Transformation and Business Performance," Journal of Economic Perspectives, American Economic Association, vol. 14(4), pages 23-48, Fall.
    20. Rema Hanna & Sendhil Mullainathan & Joshua Schwartzstein, 2014. "Learning Through Noticing: Theory and Evidence from a Field Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(3), pages 1311-1353.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zara Contractor & Germ'an Reyes, 2025. "Generative AI in Higher Education: Evidence from an Elite College," Papers 2508.00717, arXiv.org.
    2. Zara Contractor & Germán Reyes, 2025. "Generative AI in Higher Education: Evidence from an Elite College," CEDLAS, Working Papers 0359, CEDLAS, Universidad Nacional de La Plata.
    3. de Janvry, Alain & Rao, Manaswini & Sadoulet, Elisabeth, 2025. "Seeding the seeds: Role of social structure in agricultural technology diffusion," Journal of Economic Behavior & Organization, Elsevier, vol. 236(C).
    4. David Atkin & Azam Chaudhry & Shamyla Chaudry & Amit K. Khandelwal & Eric Verhoogen, 2017. "Organizational Barriers to Technology Adoption: Evidence from Soccer-Ball Producers in Pakistan," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(3), pages 1101-1164.
    5. David Alfaro‐Serrano & Tanay Balantrapu & Ritam Chaurey & Ana Goicoechea & Eric Verhoogen, 2021. "Interventions to promote technology adoption in firms: A systematic review," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(4), December.
    6. Peeyush Agarwal & Harsh Agarwal & Akshat Rana, 2025. "What Work is AI Actually Doing? Uncovering the Drivers of Generative AI Adoption," Papers 2510.23669, arXiv.org, revised Oct 2025.
    7. Chen, Shuo & Lan, Xiaohuan, 2020. "Tractor vs. animal: Rural reforms and technology adoption in China," Journal of Development Economics, Elsevier, vol. 147(C).
    8. Jutao Zeng & Jie Lyu, 2023. "Simultaneous Decisions to Undertake Off-Farm Work and Straw Return: The Role of Cognitive Ability," Land, MDPI, vol. 12(8), pages 1-21, August.
    9. Ram Fishman & Stephen C. Smith & Vida Bobic & Munshi Sulaiman, 2022. "Can Agricultural Extension and Input Support Be Discontinued? Evidence from a Randomized Phaseout in Uganda," The Review of Economics and Statistics, MIT Press, vol. 104(6), pages 1273-1288, November.
    10. Niu, Chiyu & Ragasa, Catherine, 2018. "Selective attention and information loss in the lab-to-farm knowledge chain: The case of Malawian agricultural extension programs," Agricultural Systems, Elsevier, vol. 165(C), pages 147-163.
    11. Gashaw Tadesse Abate & Tanguy Bernard & Alan de Brauw & Nicholas Minot, 2018. "The impact of the use of new technologies on farmers’ wheat yield in Ethiopia: evidence from a randomized control trial," Agricultural Economics, International Association of Agricultural Economists, vol. 49(4), pages 409-421, July.
    12. Paola Mallia, 2022. "You reap what (you think) you sow? Evidence on farmers’behavioral adjustments in the case of correct crop varietal identification," Working Papers hal-03597332, HAL.
    13. Aggarwal, Shilpa & Francis, Eilin & Robinson, Jonathan, 2018. "Grain today, gain tomorrow: Evidence from a storage experiment with savings clubs in Kenya," Journal of Development Economics, Elsevier, vol. 134(C), pages 1-15.
    14. Dalton, Patricio & Pamuk, H. & Ramrattan, R. & van Soest, Daan & Uras, Burak, 2019. "Transparency and Financial Inclusion : Experimental Evidence from Mobile Money (revision of CentER DP 2018-042)," Other publications TiSEM 98cf0741-8e78-4bba-a270-4, Tilburg University, School of Economics and Management.
    15. Emerick, Kyle & Kelley, Erin & De Janvry, Alain & Sadoulet, Elisabeth, 2019. "Endogenous Information Sharing and the Gains from Using Network Information to Maximize Technology Adoption," CEPR Discussion Papers 13507, C.E.P.R. Discussion Papers.
    16. Bashir, Sadaf & Sadowski, B. M., 2014. "General purpose technologies: A survey, a critique and future research directions," 25th European Regional ITS Conference, Brussels 2014 101443, International Telecommunications Society (ITS).
    17. Arslan, Cansın & Wollni, Meike & Oduol, Judith & Hughes, Karl, 2022. "Who communicates the information matters for technology adoption," World Development, Elsevier, vol. 158(C).
    18. Réka Juhász & Mara P. Squicciarini & Nico Voigtländer, 2020. "Technology Adoption and Productivity Growth: Evidence from Industrialization in France," NBER Working Papers 27503, National Bureau of Economic Research, Inc.
    19. Kevin He & Ran Shorrer & Mengjia Xia, 2025. "Human Misperception of Generative-AI Alignment:A Laboratory Experiment," PIER Working Paper Archive 25-019, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    20. Emerick, Kyle & Chakravorty, Ujjayant & Dar, Manzoor, 2019. "Inefficient water pricing and incentives for conservation," CEPR Discussion Papers 13572, C.E.P.R. Discussion Papers.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:iza:izadps:dp18055. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.