Gender Gaps in Overestimation of Math Performance View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2015-06

AUTHORS

Shane W. Bench, Heather C. Lench, Jeffrey Liew, Kathi Miner, Sarah A. Flores

ABSTRACT

In the United States, men are more likely to pursue math-intense STEM courses and careers than women. This investigation explored whether positivity bias in the degree to which people overestimate their past performance contributes to this gender gap. To find out, two studies were conducted with undergraduate college students in the Southern United States. In Study 1, participants (n = 122) completed a math test and estimated the percent they had solved. They then were given feedback and completed a second math test and estimation. Men overestimated their performance more than women, judging they had done better on the test than they actually had. This gender difference was not present after feedback. Further, women, but not men, who reported a more positive previous experience with math were more likely to overestimate their performance. In Study 2, participants (n = 184) completed a math test and estimated the percent they had solved. They also reported their interest in pursuing math courses and careers. Again, men overestimated their performance more than women. This greater overestimation of performance in men accounted for their greater intent to pursue math fields compared to women. The findings suggest that gender gaps in STEM fields are not necessarily the result of women underestimating their abilities, but rather may be due to men overestimating their abilities. More... »

PAGES

536-546

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11199-015-0486-9

DOI

http://dx.doi.org/10.1007/s11199-015-0486-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1004667624


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

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Turtle is a human-readable linked data format.

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RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11199-015-0486-9'


 

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