Stereotypes associating men more strongly with science compared to women have harmful implications for women’s science, technology, engineering, and math (STEM) outcomes. Exposure to successful female STEM role models can buffer women from the effect of these stereotypes and lead to better performance and greater interest in STEM fields. Moreover, role model identification is especially important for improving women’s STEM outcomes. The current study posits that encouraging women to reflect on the ways in which they identify with a role model will improve women’s STEM identification, STEM sense of belonging, weaken explicit STEM stereotypes, and will strengthen implicit associations between women and science over the course of a semester, which will then lead to increased desire to pursue STEM opportunities and improved STEM GPA. Seventy-two incoming freshmen women interested in majoring in STEM completed the study. Participants read two role model biographies at different time points during the semester, and at both time points were asked to either write about the ways in which they identified with the role model, asked to write facts about the role model, or asked to write facts about a woman whose hobbies they read about (i.e., control condition). Results revealed that encouraging women to identify with a role model weakened explicit stereotypes and strengthened implicit women-science associations compared to merely exposing women to a role model. Furthermore, encouraging women to identify with a role model and merely exposing women to a role model tended to increase STEM sense of belonging compared to not exposing women to a role model. These findings suggest that encouraging women to identify with a role model is important for improving women’s STEM attitudes. / acase@tulane.edu
| Identifer | oai:union.ndltd.org:TULANE/oai:http://digitallibrary.tulane.edu/:tulane_27945 |
| Contributors | Gilbert, Patricia (Author), O'Brien, Laurie (Thesis advisor) |
| Publisher | Tulane University |
| Source Sets | Tulane University |
| Language | English |
| Detected Language | English |
| Format | 98 |
| Rights | Copyright is in accordance with U.S. Copyright law |
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