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Closing the Gender STEM Gap - A Large-Scale Randomized-Controlled Trial in Elementary Schools

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  • Kerstin Grosch
  • Simone Haeckl
  • Martin G. Kocher

Abstract

We examine individual-level determinants of interest in STEM and analyze whether a digital web application for elementary-school children can increase children’s interest in STEM with a specific focus on narrowing the gender gap. Coupling a randomized-controlled trial with experimental lab and survey data, we analyze the effect of the digital intervention and shed light on the mechanisms. We confirm the hypothesis that girls demonstrate a lower overall interest in STEM than boys. Moreover, girls are less competitive and exhibit less pronounced math confidence than boys at the baseline. Our treatment increases girls’ interest in STEM and decreases the gender gap via an increase in STEM confidence. Our findings suggest that an easy-to-implement digital intervention has the potential to foster gender equality for young children and can potentially contribute to a reduction of gender inequalities in the labor market such as occupational sorting and the gender wage gap later in life.

Suggested Citation

  • Kerstin Grosch & Simone Haeckl & Martin G. Kocher, 2022. "Closing the Gender STEM Gap - A Large-Scale Randomized-Controlled Trial in Elementary Schools," CESifo Working Paper Series 9907, CESifo.
    • Handle: RePEc:ces:ceswps:_9907
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    Cited by:

    1. Hermes, Henning & Huschens, Martin & Rothlauf, Franz & Schunk, Daniel, 2021. "Motivating low-achievers—Relative performance feedback in primary schools," Journal of Economic Behavior & Organization, Elsevier, vol. 187(C), pages 45-59.
    2. Grosch, Kerstin & Haeckl, Simone & Rau, Holger & Preuss, Paul, 2023. "A Guide to Conducting School Experiments: Expert Insights and Best Practices for Effective Implementation," UiS Working Papers in Economics and Finance 2023/2, University of Stavanger.

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    More about this item

    Keywords

    STEM; digital intervention; gender equality; field experiment;
    All these keywords.

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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