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Isolating the “Tech” from EdTech: Experimental Evidence on Computer Assisted Learning in China

Author

Listed:
  • Yue Ma
  • Robert W. Fairlie
  • Prashant Loyalka
  • Scott Rozelle

Abstract

EdTech which includes online education, computer assisted learning (CAL), and remote instruction was expanding rapidly even before the current full-scale substitution for in-person learning at all levels of education around the world because of the coronavirus pandemic. Studies of CAL interventions have consistently found large positive effects, bolstering arguments for the widespread use of EdTech. However CAL programs, often held after school, provide not only computer-based instruction, but often additional non-technology based inputs such as more time on learning and instructional support by facilitators. In this paper, we develop a theoretical model to carefully explore the possible channels by which CAL programs might affect academic outcomes among schoolchildren. We isolate and test the technology-based effects of CAL and additional parameters from the theoretical model, by designing a novel multi-treatment field experiment with more than four thousand schoolchildren in rural China. Although we find evidence of positive overall CAL program effects on academic outcomes, when we isolate the technology-based effect of CAL (over and above traditional pencil-and-paper learning) we generally find small to null effects. Our empirical results suggest that, at times, the “Tech” in EdTech may have relatively small effects on academic outcomes, which has important implications for the continued, rapid expansion of technologies such as CAL throughout the world.

Suggested Citation

  • 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.
  • Handle: RePEc:nbr:nberwo:26953
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. 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.
    3. Tianli Feng & Xiyuan Jia & Lucy Pappas & Xiaojun Zheng & Teresa Shao & Letao Sun & Charlie Weisberg & Madeline Lu Li & Scott Rozelle & Yue Ma, 2022. "Academic Performance and the Link with Depressive Symptoms among Rural Han and Minority Chinese Adolescents," IJERPH, MDPI, vol. 19(10), pages 1-20, May.

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    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I25 - Health, Education, and Welfare - - Education - - - Education and Economic Development

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