IDEAS home Printed from https://ideas.repec.org/a/eee/ecoedu/v47y2015icp34-48.html
   My bibliography  Save this article

Does computer-assisted learning improve learning outcomes? Evidence from a randomized experiment in migrant schools in Beijing

Author

Listed:
  • Lai, Fang
  • Luo, Renfu
  • Zhang, Linxiu
  • Huang, Xinzhe
  • Rozelle, Scott

Abstract

The education of the disadvantaged population has been a long-standing challenge to education systems in both developed and developing countries. Although computer-assisted learning (CAL) has been considered one alternative to improve learning outcomes in a cost-effective way, the empirical evidence of its impacts on improving learning outcomes is mixed. This paper uses a randomized field experiment to explore the effects of CAL on student academic and non-academic outcomes for students in migrant schools in Beijing. Our results show that a remedial CAL program held out of regular school hours improved the student standardized math scores by 0.15 standard deviations and most of the program effect took place within 2 months after the start of the program. Students with less-educated parents benefited more from the program. Moreover, CAL also significantly increased the students’ interest in learning.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:ecoedu:v:47:y:2015:i:c:p:34-48
    DOI: 10.1016/j.econedurev.2015.03.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S027277571500045X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.econedurev.2015.03.005?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Abhijit V. Banerjee & Shawn Cole & Esther Duflo & Leigh Linden, 2007. "Remedying Education: Evidence from Two Randomized Experiments in India," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(3), pages 1235-1264.
    2. Thomas Fuchs & Ludger Wossmann, 2004. "Computers and student learning: bivariate and multivariate evidence on the availability and use of computers at home and at school," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 47(3-4), pages 359-386.
    3. Austan Goolsbee & Jonathan Guryan, 2006. "The Impact of Internet Subsidies in Public Schools," The Review of Economics and Statistics, MIT Press, vol. 88(2), pages 336-347, May.
    4. Jishnu Das & Stefan Dercon & James Habyarimana & Pramila Krishnan & Karthik Muralidharan & Venkatesh Sundararaman, 2013. "School Inputs, Household Substitution, and Test Scores," American Economic Journal: Applied Economics, American Economic Association, vol. 5(2), pages 29-57, April.
    5. Glewwe, Paul & Kremer, Michael & Moulin, Sylvie & Zitzewitz, Eric, 2004. "Retrospective vs. prospective analyses of school inputs: the case of flip charts in Kenya," Journal of Development Economics, Elsevier, vol. 74(1), pages 251-268, June.
    6. Glewwe, Paul & Kremer, Michael, 2006. "Schools, Teachers, and Education Outcomes in Developing Countries," Handbook of the Economics of Education, in: Erik Hanushek & F. Welch (ed.), Handbook of the Economics of Education, edition 1, volume 2, chapter 16, pages 945-1017, Elsevier.
    7. Joshua Angrist & Victor Lavy, 2002. "New Evidence on Classroom Computers and Pupil Learning," Economic Journal, Royal Economic Society, vol. 112(482), pages 735-765, October.
    8. 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.
    9. 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.
    10. Hanushek, Eric A, 1995. "Interpreting Recent Research on Schooling in Developing Countries," The World Bank Research Observer, World Bank, vol. 10(2), pages 227-246, August.
    11. repec:mpr:mprres:5414 is not listed on IDEAS
    12. David Newhouse & Kathleen Beegle, 2006. "The Effect of School Type on Academic Achievement: Evidence from Indonesia," Journal of Human Resources, University of Wisconsin Press, vol. 41(3).
    13. Hanushek, Eric A, 1986. "The Economics of Schooling: Production and Efficiency in Public Schools," Journal of Economic Literature, American Economic Association, vol. 24(3), pages 1141-1177, September.
    14. Mark Dynarski & Roberto Agodini & Sheila Heaviside & Timothy Novak & Nancy Carey & Larissa Campuzano & Barbara Means & Robert Murphy & William Penuel & Hal Javitz & Deborah Emery & Willow Sussex, "undated". "Effectiveness of Reading and Mathematics Software Products: Findings from the First Student Cohort," Mathematica Policy Research Reports 2fa5b23b827f497091fc730f0, Mathematica Policy Research.
    15. Karthik Muralidharan & Venkatesh Sundararaman, 2011. "Teacher Performance Pay: Experimental Evidence from India," Journal of Political Economy, University of Chicago Press, vol. 119(1), pages 39-77.
    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. 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.
    2. Sabrin Beg & Waqas Halim & Adrienne M. Lucas & Umar Saif, 2022. "Engaging Teachers with Technology Increased Achievement, Bypassing Teachers Did Not," American Economic Journal: Economic Policy, American Economic Association, vol. 14(2), pages 61-90, May.
    3. Yu Bai & Linxiu Zhang & Chengfang Liu & Yaojiang Shi & Di Mo & Scott Rozelle, 2018. "Effect of Parental Migration on the Academic Performance of Left Behind Children in North Western China," Journal of Development Studies, Taylor & Francis Journals, vol. 54(7), pages 1154-1170, July.
    4. 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).
    5. Ferman, Bruno & Finamor, Lucas & Lima, Lycia, 2019. "Are Public Schools Ready to Integrate Math Classes with Khan Academy?," MPRA Paper 94736, University Library of Munich, Germany.
    6. 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.
    7. Aymo Brunetti & Konstantin Buechel & Martina Jakob & Ben Jann & Christoph Kuehnhanss & Daniel Steffen, 2020. "Teacher Content Knowledge in Developing Countries: Evidence from a Math Assessment in El Salvador," Diskussionsschriften dp2005, Universitaet Bern, Departement Volkswirtschaft.
    8. Joël Cariolle & David A Carroll, 2022. "The Use of Digital for Public Service Provision in Sub-Saharan Africa," Working Papers hal-03004535, HAL.
    9. Ian K. McDonough & Constant I. Tra, 2017. "The impact of computer-based tutorials on high school math proficiency," Empirical Economics, Springer, vol. 52(3), pages 1041-1063, May.
    10. Narain Das & Kenneth Khawandiza Sunguh & Binesh Sarwar & Arslan Ahmed & Shah Hassan, 2019. "Technology-Embedded Educational Policy: Mediation Effects of the Use of Virtual Learning Influence on Learner Satisfaction," Journal of Education and Training, Macrothink Institute, vol. 6(1), pages 41-54, February.
    11. Yaojiang Shi & Yu Bai & Yanni Shen & Kaleigh Kenny & Scott Rozelle, 2016. "Effects of Parental Migration on Mental Health of Left-behind Children: Evidence from Northwestern China," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 24(3), pages 105-122, May.
    12. Cardim, Joana & Molina-Millán, Teresa & Vicente, Pedro C., 2023. "Can technology improve the classroom experience in primary education? An African experiment on a worldwide program," Journal of Development Economics, Elsevier, vol. 164(C).
    13. Fulya Ersoy, 2021. "Returns to effort: experimental evidence from an online language platform," Experimental Economics, Springer;Economic Science Association, vol. 24(3), pages 1047-1073, September.
    14. Eric Bettinger & Robert Fairlie & Anastasia Kapuza & Elena Kardanova & Prashant Loyalka & Andrey Zakharov, 2023. "Diminishing Marginal Returns to Computer‐Assisted Learning," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 42(2), pages 552-570, March.
    15. Gourley, Patrick, 2021. "Back to basics: How reading the text and taking notes improves learning," International Review of Economics Education, Elsevier, vol. 37(C).
    16. Blimpo,Moussa Pouguinimpo & Gajigo,Ousman & Owusu,Solomon & Tomita,Ryoko & Xu,Yanbin, 2020. "Technology in the Classroom and Learning in Secondary Schools," Policy Research Working Paper Series 9288, The World Bank.
    17. 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, vol. 12(23), pages 1-16, December.
    18. Konstantin Büchel & Martina Jakob & Christoph Kühnhanss & Daniel Steffen & Aymo Brunetti, 2020. "The Relative Effectiveness of Teachers and Learning Software: Evidence from a Field Experiment in El Salvador," University of Bern Social Sciences Working Papers 36, University of Bern, Department of Social Sciences.
    19. Gómez-Fernández, Nerea & Mediavilla, Mauro, 2021. "Exploring the relationship between Information and Communication Technologies (ICT) and academic performance: A multilevel analysis for Spain," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).
    20. Konstantin Buechel & Martina Jakob & Daniel Steffen & Christoph Kuehnhanss & Aymo Brunetti, 2020. "The Relative Effectiveness of Teachers and Learning Software: Evidence from a Field Experiment in El Salvador," Diskussionsschriften dp2006, Universitaet Bern, Departement Volkswirtschaft.
    21. Mohammad Khasawneh & Ahmad Bani Yaseen, 2017. "Critical success factors for e-learning satisfaction, Jordanian Universities’ experience," Journal of Business & Management (COES&RJ-JBM), , vol. 5(1), pages 56-69, January.

    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. 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.
    2. Bulman, George & Fairlie, Robert W., 2015. "Technology and Education: Computers, Software, and the Internet," IZA Discussion Papers 9432, Institute of Labor Economics (IZA).
    3. Ama Baafra Abeberese, 2011. "Improving Reading Skills by Encouraging Children to Read: A Randomized Evaluation of the Sa Aklat Sisikat Reading Program in the Philippines," Working Papers id:4312, eSocialSciences.
    4. Ama Baafra Abeberese & Todd J. Kumler & Leigh L. Linden, 2014. "Improving Reading Skills by Encouraging Children to Read in School:: A Randomized Evaluation of the Sa Aklat Sisikat Reading Program in the Philippines," Journal of Human Resources, University of Wisconsin Press, vol. 49(3), pages 611-633.
    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. 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.
    7. Marchionni, Mariana & Pinto, Florencia & Vazquez, Emmanuel, 2013. "Determinantes de la desigualdad en el desempeño educativo en la Argentina [Determinants of the inequality in PISA test scores in Argentina]," MPRA Paper 56421, University Library of Munich, Germany.
    8. Miguel Urquiola, 2015. "Progress and challenges in achieving an evidence-based education policy in Latin America and the Caribbean," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 24(1), pages 1-30, December.
    9. Gómez-Fernández, Nerea & Mediavilla, Mauro, 2021. "Exploring the relationship between Information and Communication Technologies (ICT) and academic performance: A multilevel analysis for Spain," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).
    10. Marchionni, Mariana & Vazquez, Emmanuel & Pinto, Florencia, 2012. "Desigualdad educativa en la Argentina. Análisis en base a los datos PISA 2009 [Education Inequality in Argentina. An analysis based on PISA 2009 data]," MPRA Paper 56420, University Library of Munich, Germany.
    11. 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.
    12. Stephen Machin & Sandra McNally & Olmo Silva, 2007. "New Technology in Schools: Is There a Payoff?," Economic Journal, Royal Economic Society, vol. 117(522), pages 1145-1167, July.
    13. 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).
    14. 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.
    15. 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.
    16. Carrillo, Paul E. & Onofa, Mercedes & Ponce, Juan, 2010. "Information Technology and Student Achievement: Evidence from a Randomized Experiment in Ecuador," IDB Publications (Working Papers) 3094, Inter-American Development Bank.
    17. 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.
    18. Catherine Rodríguez Orgales & Fabio Sánchez Torres & Juliana Márquez Zúñiga, 2011. "Impacto del Programa Computadores para Educar" en la deserción estudiantil, el logro escolar y el ingreso a la educación superior"," Documentos CEDE 8744, Universidad de los Andes, Facultad de Economía, CEDE.
    19. Eric Bettinger & Robert Fairlie & Anastasia Kapuza & Elena Kardanova & Prashant Loyalka & Andrey Zakharov, 2023. "Diminishing Marginal Returns to Computer‐Assisted Learning," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 42(2), pages 552-570, March.
    20. Aaron K. Chatterji, 2017. "Innovation and American K-12 Education," NBER Chapters, in: Innovation Policy and the Economy, Volume 18, pages 27-51, National Bureau of Economic Research, Inc.

    More about this item

    Keywords

    Education; Development; Computer-assisted learning; Random assignment; Test scores; China; Migration;
    All these keywords.

    JEL classification:

    • I20 - Health, Education, and Welfare - - Education - - - General
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

    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:eee:ecoedu:v:47:y:2015:i:c:p:34-48. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/econedurev .

    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.