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Integrating Computer Assisted Learning into a Regular Curriculum: Evidence from a Randomized Experiment in Rural Schools in Shaanxi

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  • Mo, Di
  • Zhang, Linxiu
  • Luo, Renfu
  • Qu, Qinghe
  • Huang, Weiming
  • Wang, Jiafu
  • Qiao, Yajie
  • Boswell, Matthew
  • Rozelle, Scott

Abstract

Recent attention has been placed on whether computer assisted learning (CAL) can effectively improve learning outcomes. However, the empirical evidence of its impact is mixed. Previous studies suggest that the lack of an impact in developed countries may be attributable to substitution of effort/time away from productive, in-school activities. However, there is little empirical evidence on how effective an in-school program may be in developing countries. In order to explore the impact of an in-school CAL program, we conducted a clustered randomized experiment involving over 4000 third and fifth grade students in 72 rural schools in China. Our results indicate that the in-school CAL program has significantly improved the overall math scores by 0.16 standard deviations. Both the third graders and the fifth graders benefited from the program.

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  • Mo, Di & Zhang, Linxiu & Luo, Renfu & Qu, Qinghe & Huang, Weiming & Wang, Jiafu & Qiao, Yajie & Boswell, Matthew & Rozelle, Scott, 2015. "Integrating Computer Assisted Learning into a Regular Curriculum: Evidence from a Randomized Experiment in Rural Schools in Shaanxi," 2015 Conference, August 9-14, 2015, Milan, Italy 212473, International Association of Agricultural Economists.
  • Handle: RePEc:ags:iaae15:212473
    DOI: 10.22004/ag.econ.212473
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    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. 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.
    3. Facundo Albornoz & María Victoria Anauati & Melina Furman & Mariana Luzuriaga & María Eugenia Podestá & Inés Taylor, 2020. "Training to Teach Science: Experimental Evidence from Argentina," The World Bank Economic Review, World Bank, vol. 34(2), pages 393-417.
    4. 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).
    5. 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.
    6. Fang Lai & Linxiu Zhang & Qinghe Qu & Xiao Hu & Yaojiang Shi & Matthew Boswell & Scott Rozelle, 2015. "Teaching the Language of Wider Communication, Minority Students, and Overall Educational Performance: Evidence from a Randomized Experiment in Qinghai Province, China," Economic Development and Cultural Change, University of Chicago Press, vol. 63(4), pages 753-776.
    7. 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).
    8. Yue Ma & Robert W. Fairlie & Prashant Loyalka & Scott Rozelle, 2020. "Isolating the "Tech" from EdTech: Experimental Evidence on Computer Assisted Learning in China," CESifo Working Paper Series 8186, CESifo.
    9. 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.
    10. Marcel Fafchamps & Di Mo, 2018. "Peer effects in computer assisted learning: evidence from a randomized experiment," Experimental Economics, Springer;Economic Science Association, vol. 21(2), pages 355-382, June.
    11. Hojun Lee & Youngsik Kim, 2023. "Exploring the Effects of Computer and Smart Device-Assisted Learning on Students’ Achievements: Empirical Evidence from Korea," Sustainability, MDPI, vol. 15(17), pages 1-16, September.
    12. 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.
    13. Cueto, Santiago & Beuermann, Diether & Cristia, Julian P. & Malamud, Ofer & Pardo, Francisco, 2024. "Laptops in the Long-Run: Evidence from the One Laptop per Child Program in Rural Peru," IDB Publications (Working Papers) 13786, Inter-American Development Bank.
    14. 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).

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