IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/26967.html
   My bibliography  Save this paper

Does EdTech Substitute for Traditional Learning? Experimental Estimates of the Educational Production Function

Author

Listed:
  • Eric Bettinger
  • Robert W. Fairlie
  • Anastasia Kapuza
  • Elena Kardanova
  • Prashant Loyalka
  • Andrey Zakharov

Abstract

Experimental studies rarely consider the shape and nature of the education production function, which is useful for deriving optimal levels of input substitution in increasingly resource constrained environments. Because of the rapid expansion of EdTech as a substitute for traditional learning around the world and against the backdrop of full-scale temporary substitution due to the coronavirus pandemic, we explore the educational production function by using a large randomized controlled trial that varies dosage of computer-assisted learning (CAL) as a substitute for traditional learning. Results show production is concave in CAL. Moving from zero to a low level of CAL, the marginal rate of technical substitution (MRTS) of CAL for traditional learning is greater than one. Moving from a lower to a higher level of CAL, production remains on the same or a lower isoquant and the MRTS is equal to or less than one. The estimates are consistent with the general form of a Cobb-Douglas production function and imply that a blended approach of CAL and traditional learning is optimal. The findings have direct implications for the rapidly expanding use of educational technology worldwide and its continued substitution for traditional learning.

Suggested Citation

  • Eric Bettinger & Robert W. Fairlie & Anastasia Kapuza & Elena Kardanova & Prashant Loyalka & Andrey Zakharov, 2020. "Does EdTech Substitute for Traditional Learning? Experimental Estimates of the Educational Production Function," NBER Working Papers 26967, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:26967
    Note: CH DEV ED LS PE PR
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w26967.pdf
    Download Restriction: Access to the full text is generally limited to series subscribers, however if the top level domain of the client browser is in a developing country or transition economy free access is provided. More information about subscriptions and free access is available at http://www.nber.org/wwphelp.html. Free access is also available to older working papers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hull, Marie C. & Duch, Katherine, 2017. "One-To-One Technology and Student Outcomes," IZA Discussion Papers 10886, Institute of Labor Economics (IZA).
    2. Auriol, Emmanuelle & Warlters, Michael, 2012. "The marginal cost of public funds and tax reform in Africa," Journal of Development Economics, Elsevier, vol. 97(1), pages 58-72.
    3. Julian Cristia & Pablo Ibarrarán & Santiago Cueto & Ana Santiago & Eugenio Severín, 2017. "Technology and Child Development: Evidence from the One Laptop per Child Program," American Economic Journal: Applied Economics, American Economic Association, vol. 9(3), pages 295-320, July.
    4. Abhijit V. Banerjee & Shawn Cole & Esther Duflo & Leigh Linden, 2007. "Remedying Education: Evidence from Two Randomized Experiments in India," The Quarterly Journal of Economics, Oxford University Press, vol. 122(3), pages 1235-1264.
    5. Fang Lai & Linxiu Zhang & Xiao Hu & Qinghe Qu & Yaojiang Shi & Yajie Qiao & Matthew Boswell & Scott Rozelle, 2013. "Computer assisted learning as extracurricular tutor? Evidence from a randomised experiment in rural boarding schools in Shaanxi," Journal of Development Effectiveness, Taylor & Francis Journals, vol. 5(2), pages 208-231, June.
    6. Di Mo & Linxiu Zhang & Renfu Luo & Qinghe Qu & Weiming Huang & Jiafu Wang & Yajie Qiao & Matthew Boswell & Scott Rozelle, 2014. "Integrating computer-assisted learning into a regular curriculum: evidence from a randomised experiment in rural schools in Shaanxi," Journal of Development Effectiveness, Taylor & Francis Journals, vol. 6(3), pages 300-323, September.
    7. repec:mpr:mprres:5414 is not listed on IDEAS
    8. Lisa Barrow & Lisa Markman & Cecilia Elena Rouse, 2009. "Technology's Edge: The Educational Benefits of Computer-Aided Instruction," American Economic Journal: Economic Policy, American Economic Association, vol. 1(1), pages 52-74, February.
    9. John List & Sally Sadoff & Mathis Wagner, 2011. "So you want to run an experiment, now what? Some simple rules of thumb for optimal experimental design," Experimental Economics, Springer;Economic Science Association, vol. 14(4), pages 439-457, November.
    10. Rouse, Cecilia Elena & Krueger, Alan B., 2004. "Putting computerized instruction to the test: a randomized evaluation of a "scientifically based" reading program," Economics of Education Review, Elsevier, vol. 23(4), pages 323-338, August.
    11. Karthik Muralidharan & Abhijeet Singh & Alejandro J. Ganimian, 2019. "Disrupting Education? Experimental Evidence on Technology-Aided Instruction in India," American Economic Review, American Economic Association, vol. 109(4), pages 1426-1460, April.
    12. Caroline M. Hoxby, 2000. "The Effects of Class Size on Student Achievement: New Evidence from Population Variation," The Quarterly Journal of Economics, Oxford University Press, vol. 115(4), pages 1239-1285.
    13. Fairlie Robert W., 2016. "Do Boys and Girls Use Computers Differently, and Does It Contribute to Why Boys do Worse in School Than Girls?," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 16(1), pages 59-96, January.
    14. Lai, Fang & Luo, Renfu & Zhang, Linxiu & Huang, Xinzhe & Rozelle, Scott, 2015. "Does computer-assisted learning improve learning outcomes? Evidence from a randomized experiment in migrant schools in Beijing," Economics of Education Review, Elsevier, vol. 47(C), pages 34-48.
    15. Oliver Falck & Constantin Mang & Ludger Woessmann, 2018. "Virtually No Effect? Different Uses of Classroom Computers and their Effect on Student Achievement," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(1), pages 1-38, February.
    16. Mo, Di & Huang, Weiming & Shi, Yaojiang & Zhang, Linxiu & Boswell, Matthew & Rozelle, Scott, 2015. "Computer technology in education: Evidence from a pooled study of computer assisted learning programs among rural students in China," China Economic Review, Elsevier, vol. 36(C), pages 131-145.
    17. Robert W. Fairlie & Jonathan Robinson, 2013. "Experimental Evidence on the Effects of Home Computers on Academic Achievement among Schoolchildren," American Economic Journal: Applied Economics, American Economic Association, vol. 5(3), pages 211-240, July.
    18. Diether W. Beuermann & Julian Cristia & Santiago Cueto & Ofer Malamud & Yyannu Cruz-Aguayo, 2015. "One Laptop per Child at Home: Short-Term Impacts from a Randomized Experiment in Peru," American Economic Journal: Applied Economics, American Economic Association, vol. 7(2), pages 53-80, April.
    19. repec:mpr:mprres:6181 is not listed on IDEAS
    20. Mo, Di & Swinnen, Johan & Zhang, Linxiu & Yi, Hongmei & Qu, Qinghe & Boswell, Matthew & Rozelle, Scott, 2013. "Can One-to-One Computing Narrow the Digital Divide and the Educational Gap in China? The Case of Beijing Migrant Schools," World Development, Elsevier, vol. 46(C), pages 14-29.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ferman, Bruno & Lima, Lycia & Riva, Flávio, 2021. "Artificial Intelligence, Teacher Tasks and Individualized Pedagogy," SocArXiv qw249, Center for Open Science.
    2. Noam Angrist & Peter Bergman & Moitshepi Matsheng, 2020. "School’s Out: Experimental Evidence on Limiting Learning Loss Using “Low-Tech” in a Pandemic," NBER Working Papers 28205, National Bureau of Economic Research, Inc.
    3. Bin Tang & Te-Tien Ting & Chyi-In Wu & Yue Ma & Di Mo & Wei-Ting Hung & Scott Rozelle, 2020. "The Impact of Online Computer Assisted Learning at Home for Disadvantaged Children in Taiwan: Evidence from a Randomized Experiment," Sustainability, MDPI, Open Access Journal, vol. 12(23), pages 1-16, December.
    4. Ferman, Bruno & Lima, Lycia & Riva, Flavio, 2020. "Experimental Evidence on Artificial Intelligence in the Classroom," MPRA Paper 103934, University Library of Munich, Germany.

    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. Yue Ma & Robert W. Fairlie & Prashant Loyalka & Scott Rozelle, 2020. "Isolating the “Tech” from EdTech: Experimental Evidence on Computer Assisted Learning in China," NBER Working Papers 26953, National Bureau of Economic Research, Inc.
    2. Karthik Muralidharan & Abhijeet Singh & Alejandro J. Ganimian, 2019. "Disrupting Education? Experimental Evidence on Technology-Aided Instruction in India," American Economic Review, American Economic Association, vol. 109(4), pages 1426-1460, April.
    3. Rosa Sanchis-Guarner & José Montalbán & Felix Weinhardt, 2021. "Home Broadband and Human Capital Formation," CESifo Working Paper Series 8846, CESifo.
    4. NAKAMURO Makiko & ITO Hirotake, 2020. "The Effect of Computer Assisted Learning on Children's Cognitive and Noncognitive Skills: Evidence from a Randomized Experiment in Cambodia," Discussion papers 20074, Research Institute of Economy, Trade and Industry (RIETI).
    5. Nerea Gómez-Fernández & Mauro Mediavilla, 2018. "Do information and communication technologies (ICT) improve educational outcomes? Evidence for Spain in PISA 2015," Working Papers 2018/20, Institut d'Economia de Barcelona (IEB).
    6. Naik, Gopal & Chitre, Chetan & Bhalla, Manaswini & Rajan, Jothsna, 2020. "Impact of use of technology on student learning outcomes: Evidence from a large-scale experiment in India," World Development, Elsevier, vol. 127(C).
    7. Bulman, George & Fairlie, Robert W., 2015. "Technology and Education: Computers, Software, and the Internet," IZA Discussion Papers 9432, Institute of Labor Economics (IZA).
    8. Bin Tang & Te-Tien Ting & Chyi-In Wu & Yue Ma & Di Mo & Wei-Ting Hung & Scott Rozelle, 2020. "The Impact of Online Computer Assisted Learning at Home for Disadvantaged Children in Taiwan: Evidence from a Randomized Experiment," Sustainability, MDPI, Open Access Journal, vol. 12(23), pages 1-16, December.
    9. Bulman, George & Fairlie, Robert W, 2016. "Technology and Education: Computers, Software, and the Internet," Santa Cruz Department of Economics, Working Paper Series qt0rb5x6bf, Department of Economics, UC Santa Cruz.
    10. Bulman, George & Fairlie, Robert W, 2015. "Technology and Education: Computers, Software, and the Internet," Santa Cruz Department of Economics, Working Paper Series qt5265z87t, Department of Economics, UC Santa Cruz.
    11. Sabrin A. Beg & Adrienne M. Lucas & Waqas Halim & Umar Saif, 2019. "Engaging Teachers with Technology Increased Achievement, Bypassing Teachers Did Not," NBER Working Papers 25704, National Bureau of Economic Research, Inc.
    12. Bet, German & Cristia, Julián P. & Ibarrarán, Pablo, 2014. "The Effects of Shared School Technology Access on Students Digital Skills in Peru," IZA Discussion Papers 7954, Institute of Labor Economics (IZA).
    13. Patterson, Richard W. & Patterson, Robert M., 2017. "Computers and productivity: Evidence from laptop use in the college classroom," Economics of Education Review, Elsevier, vol. 57(C), pages 66-79.
    14. Malamud, Ofer & Cueto, Santiago & Cristia, Julian & Beuermann, Diether W., 2019. "Do children benefit from internet access? Experimental evidence from Peru," Journal of Development Economics, Elsevier, vol. 138(C), pages 41-56.
    15. Derksen, Laura & Leclerc, Catherine Michaud & Souza, Pedro CL, 2019. "Searching for Answers : The Impact of Student Access to Wikipedia," The Warwick Economics Research Paper Series (TWERPS) 1236, University of Warwick, Department of Economics.
    16. Comi, Simona Lorena & Argentin, Gianluca & Gui, Marco & Origo, Federica & Pagani, Laura, 2017. "Is it the way they use it? Teachers, ICT and student achievement," Economics of Education Review, Elsevier, vol. 56(C), pages 24-39.
    17. Di Mo & Linxiu Zhang & Renfu Luo & Qinghe Qu & Weiming Huang & Jiafu Wang & Yajie Qiao & Matthew Boswell & Scott Rozelle, 2014. "Integrating computer-assisted learning into a regular curriculum: evidence from a randomised experiment in rural schools in Shaanxi," Journal of Development Effectiveness, Taylor & Francis Journals, vol. 6(3), pages 300-323, September.
    18. Yi Lu & Hong Song, 2020. "The effect of educational technology on college students’ labor market performance," Journal of Population Economics, Springer;European Society for Population Economics, vol. 33(3), pages 1101-1126, July.
    19. Derksen, Laura & Leclerc, Catherine Michaud & Souza, Pedro CL, 2019. "Searching for Answers: The Impact of Student Access to Wikipedia," CAGE Online Working Paper Series 450, Competitive Advantage in the Global Economy (CAGE).
    20. Peter Bergman, 2020. "Nudging Technology Use: Descriptive and Experimental Evidence from School Information Systems," Education Finance and Policy, MIT Press, vol. 15(4), pages 623-647, Fall.

    More about this item

    JEL classification:

    • F63 - International Economics - - Economic Impacts of Globalization - - - Economic Development
    • I25 - Health, Education, and Welfare - - Education - - - Education and Economic Development

    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:nbr:nberwo:26967. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    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: (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.