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Do Boys and Girls Use Computers Differently, and Does It Contribute to Why Boys doWorse in School than Girls?

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  • Fairlie, Robert

Abstract

Boys are doing worse in school than are girls, which has been dubbed "the Boy Crisis." An analysis of the latest data on educational outcomes among boys and girls reveals extensive disparities in grades, reading and writing test scores, and other measurable educational outcomes, and these disparities exist across family resources and race. Focusing on disadvantaged schoolchildren, I then examine whether time investments made by boys and girls related to computer use contribute to the gender gap in academic achievement. Data from several sources indicate that boys are less likely to use computers for schoolwork and are more likely to use computers for playing games, but are less likely to use computers for social networking and email than are girls. Using data from a large field experiment randomly providing free personal computers to schoolchildren for home use, I also test whether these differential patterns of computer use displace homework time and ultimately translate into worse educational outcomes among boys. No evidence is found indicating that personal computers crowd out homework time and effort for disadvantaged boys relative to girls. Home computers also do not have negative effects on educational outcomes such as grades, test scores, courses completed, and tardies for disadvantaged boys relative to girls.

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  • Fairlie, Robert, 2015. "Do Boys and Girls Use Computers Differently, and Does It Contribute to Why Boys doWorse in School than Girls?," Santa Cruz Department of Economics, Working Paper Series qt4n54q8xh, Department of Economics, UC Santa Cruz.
    • Handle: RePEc:cdl:ucscec:qt4n54q8xh
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    Cited by:

    1. 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.
    2. Chatterjee Somdeep, 2017. "Getting Girls to Schools! – Assessing the Impacts of a Targeted Program on Enrollment and Academic Performance," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 17(1), pages 1-6, February.
    3. M. Niaz Asadullah & Anindita Bhattacharjee, 2022. "Digital Divide or Digital Provide? Technology, Time Use, and Learning Loss during COVID-19," Journal of Development Studies, Taylor & Francis Journals, vol. 58(10), pages 1934-1957, October.
    4. 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.
    5. 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).
    6. Algan, Yann & Fortin, Nicole M., 2016. "Computer Gaming and Test Scores: Cross-Country Gender Differences among Teenagers," IZA Discussion Papers 10433, Institute of Labor Economics (IZA).
    7. 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).

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    More about this item

    Keywords

    Education; Social and Behavioral Sciences; technology; computers; ICT; education; gender; field experiment;
    All these keywords.

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination

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