Examining Prior Experience and Initial Gender Stereotypes Among First-Year Computer Science Students (Poster 43)

• In Event: AERA Poster Session Saturday 8:00 a.m.
  In Poster Session: Learning and Motivation in STEM

Abstract

Poor gender representation in computer science remains a problem that is partially due to stereotypes about women’s ability, brilliance, and interest in computer science. However, early experience in computer science may ameliorate these stereotypes, as it has with other outcomes. The present study examined if prior experience in computer science was associated with fewer stereotypes about women, and if these relationships differed by gender. A multigroup structural equation modeling approach with responses from 574 undergraduate students in a first-semester computer science course revealed that prior experience was associated with fewer ability and brilliance stereotypes, but only among men. These results suggest that early experience in computer science may help create a better environment for women at the college level.

Authors

• Nathaniel Woznicki, New York University

• Sophie Arnold, New York University

• Aashna Poddar, New York University

• Bethany Lassetter, New York University

• Natalie Hutchins, University of Virginia

• Kenneth Joseph, University at Buffalo - SUNY

• Chris Proctor, University at Buffalo - SUNY

• Andrei Cimpian, New York University