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Does the Closeness of Peers Matter? An Investigation Using Online Training Platform Data and Survey Data

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  • Gu, Xin

    (Georgia Institute of Technology)

  • Li, Haizheng

    (Georgia Tech)

Abstract

We study peer effects in online training participation using unique data from a large-scale online teacher training program. The platform data allow us to observe the accurate duration of attendance for every individual-lecture pair. We classify peer groups as close peers, local peers, and global peers based on their relationships. By controlling for unobserved heterogeneity, we find positive effects of close and local peer appearance on trainees' joining a lecture and on their length of stay in the lecture. However, global peers generate a negative but economically insignificant impact. Peer effects differ by group and increase with the relationship closeness. Using the survey data, we investigate the mechanisms of peer influences and find that social interactions facilitate online peer effects. Peer pressure and reputation concerns also help explain our findings. Our results shed new light on how peer effects can be utilized to improve the effectiveness of online learning.

Suggested Citation

  • Gu, Xin & Li, Haizheng, 2023. "Does the Closeness of Peers Matter? An Investigation Using Online Training Platform Data and Survey Data," IZA Discussion Papers 15964, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp15964
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    References listed on IDEAS

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    1. Lawrence E. Blume & William A. Brock & Steven N. Durlauf & Rajshri Jayaraman, 2015. "Linear Social Interactions Models," Journal of Political Economy, University of Chicago Press, vol. 123(2), pages 444-496.
    2. David Card & Laura Giuliano, 2013. "Peer Effects and Multiple Equilibria in the Risky Behavior of Friends," The Review of Economics and Statistics, MIT Press, vol. 95(4), pages 1130-1149, October.
    3. William T. Alpert & Kenneth A. Couch & Oskar R. Harmon, 2016. "A Randomized Assessment of Online Learning," American Economic Review, American Economic Association, vol. 106(5), pages 378-382, May.
    4. Yann Bramoull? & Rachel Kranton & Martin D'Amours, 2014. "Strategic Interaction and Networks," American Economic Review, American Economic Association, vol. 104(3), pages 898-930, March.
    5. Byron W. Brown & Carl E. Liedholm, 2002. "Can Web Courses Replace the Classroom in Principles of Microeconomics?," American Economic Review, American Economic Association, vol. 92(2), pages 444-448, May.
    6. Eric Bettinger & Jing Liu & Susanna Loeb, 2016. "Connections Matter: How Interactive Peers Affect Students in Online College Courses," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 35(4), pages 932-954, September.
    7. Scott E. Carrell & Bruce I. Sacerdote & James E. West, 2013. "From Natural Variation to Optimal Policy? The Importance of Endogenous Peer Group Formation," Econometrica, Econometric Society, vol. 81(3), pages 855-882, May.
    8. Timothy M. Diette & Ruth Uwaifo Oyelere, 2014. "Gender and Race Heterogeneity: The Impact of Students with Limited English on Native Students' Performance," American Economic Review, American Economic Association, vol. 104(5), pages 412-417, May.
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    More about this item

    Keywords

    peer effects; online training;

    JEL classification:

    • 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
    • M53 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Training

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