IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp15964.html
   My bibliography  Save this paper

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

Author

Listed:
  • Gu, Xin

    (Georgia Institute of Technology)

  • Li, Haizheng

    (Georgia Institute of Technology)

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
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp15964.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    Full references (including those not matched with items on IDEAS)

    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. Lin, Zhongjian & Hu, Yingyao, 2024. "Binary choice with misclassification and social interactions, with an application to peer effects in attitude," Journal of Econometrics, Elsevier, vol. 238(1).
    2. Alexandra de Gendre & Krzysztof Karbownik & Nicolás Salamanca & Yves Zenou, 2024. "Integrating Minorities in the Classroom: The Role of Students, Parents, and Teachers," NBER Working Papers 32429, National Bureau of Economic Research, Inc.
    3. Arun Advani & Bansi Malde, 2018. "Credibly Identifying Social Effects: Accounting For Network Formation And Measurement Error," Journal of Economic Surveys, Wiley Blackwell, vol. 32(4), pages 1016-1044, September.
    4. Engelhardt, Bryan & Johnson, Marianne & Meder, Martin E., 2021. "Learning in the time of Covid-19: Some preliminary findings," International Review of Economics Education, Elsevier, vol. 37(C).
    5. Ushchev, Philip & Zenou, Yves, 2020. "Social norms in networks," Journal of Economic Theory, Elsevier, vol. 185(C).
    6. Guo, Yuhe & Li, Shaoping & Chen, Siwei & Tang, Yalin & Liu, Chengfang, 2022. "Health benefits of having more female classmates: Quasi-experimental evidence from China," Economics of Education Review, Elsevier, vol. 91(C).
    7. de Gendre, Alexandra & Salamanca, Nicolás, 2020. "On the Mechanisms of Ability Peer Effects," IZA Discussion Papers 13938, Institute of Labor Economics (IZA).
    8. Yingyao Hu & Zhongjian Lin, 2018. "Misclassification and the hidden silent rivalry," CeMMAP working papers CWP12/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. M Paula Cacault & Christian Hildebrand & Jérémy Laurent-Lucchetti & Michele Pellizzari, 2021. "Distance Learning in Higher Education: Evidence from a Randomized Experiment [A Randomized Assessment of Online Learning]," Journal of the European Economic Association, European Economic Association, vol. 19(4), pages 2322-2372.
    10. Liza Charroin, 2018. "Homophily, peer effects and dishonesty," Post-Print halshs-01993618, HAL.
    11. Zhou, Wenyu, 2019. "A network social interaction model with heterogeneous links," Economics Letters, Elsevier, vol. 180(C), pages 50-53.
    12. Yang, Chao & Lee, Lung-fei & Qu, Xi, 2018. "Tobit models with social interactions: Complete vs incomplete information," Regional Science and Urban Economics, Elsevier, vol. 73(C), pages 30-50.
    13. Topa, Giorgio & Zenou, Yves, 2015. "Neighborhood and Network Effects," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 561-624, Elsevier.
    14. Konstanting Lucks & Melanie Lührmann & Joachim K. Winter, 2017. "Peer effects in risky choices among adolescents," IFS Working Papers W17/16, Institute for Fiscal Studies.
    15. 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.
    16. Goux, Dominique & Gurgand, Marc & Maurin, Eric, 2014. "Adjusting Your Dreams? The Effect of School and Peers on Dropout Behaviour," IZA Discussion Papers 7948, Institute of Labor Economics (IZA).
    17. Busso, Matias & Frisancho, Veronica, 2021. "Good peers have asymmetric gendered effects on female educational outcomes: Experimental evidence from Mexico," Journal of Economic Behavior & Organization, Elsevier, vol. 189(C), pages 727-747.
    18. Ezra Einy & Ori Haimanko & David Lagziel, 2022. "Strong robustness to incomplete information and the uniqueness of a correlated equilibrium," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 73(1), pages 91-119, February.
    19. Bryan S. Graham, 2018. "Identifying and Estimating Neighborhood Effects," Journal of Economic Literature, American Economic Association, vol. 56(2), pages 450-500, June.
    20. Magdalena Bennett & Peter Bergman, 2021. "Better Together? Social Networks in Truancy and the Targeting of Treatment," Journal of Labor Economics, University of Chicago Press, vol. 39(1), pages 1-36.

    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

    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:iza:izadps:dp15964. 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: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.html .

    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.