IDEAS home Printed from https://ideas.repec.org/p/idd/wpaper/4.html

When Science Feels like Math: Quantitative Content in Science Assessments and the Gender Achievement Gap

Author

Listed:
  • Jain, Divyanshu

    (Plaksha University)

  • Jain, Tarun

    (Indian Institute of Management Ahmedabad)

Abstract

This paper shows how math-intensive evaluation drives science gender gaps. Using question-level data from a large standardized exam in grades 3 to 10 in India, we find boys outperform girls in mathematics in each grade. In science, girls outperform boys in early grades when few questions are math-intensive, but underperform in later grades as math intensity increases. A substantial portion of the gender gap is explained by question type: girls perform comparably to boys on non-quantitative science questions, but underperform on quantitative ones across all grades. Conditional on previous year performance, girls face a larger penalty from increasing math intensity in science exams. These findings show that gender differences in science are primarily driven by quantitative content in science assessments, helping explain why gender gaps are concentrated in math-intensive science fields. Strengthening foundational mathematics skills and confidence for girls could reduce gender gaps in science, with implications for gender-based sorting in higher education and careers.

Suggested Citation

Handle: RePEc:idd:wpaper:4
DOI: 10.5281/zenodo.21907670
as

Download full text from publisher

File URL: https://zenodo.org/records/21907671/files/IDEA-wp0004.pdf?download=1
Download Restriction: no

File URL: https://libkey.io/10.5281/zenodo.21907670?utm_source=ideas
LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
---><---

More about this item

Keywords

;
;
;
;

JEL classification:

  • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
  • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
  • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination

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:idd:wpaper:4. 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.

We have no bibliographic references for this item. You can help adding them by using 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: Ethan Ligon (email available below). General contact details of provider: https://edirc.repec.org/data/ideaaea.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.