Nilanjana Dasgupta University of Massachusetts, Amherst

1. STEMing the tide:Female experts and peers enhance young women's interest in science, technology, engineering, and mathematics Nilanjana Dasgupta University of Massachusetts, Amherst

2. Setting the stage • Many people believe that if middle-school and high-school girls show no interest in science or math, there's little anyone can do about it. • Interest is not fixed but dynamic. Related to confidence. If students feel confident, it feeds interest. If they lack confidence, it kills interest. Gender disparity in STEM has more to do with confidence than ability. • Gender gap in math test performance has shrunk and, in some cases completely disappeared (Dutton et al., 2002; Hyde et al., 2008; Hyde & Mertz, 2009). • Yet, female students lag behind male peers in confidence in STEM, attitudes, motivation to pursue STEM (Hargreaves et al., 2008; Hyde,et al., 1990; Schmader, et al., 2004; Mendez, et al., 2006). • What accounts for discrepancy between performance vs. self-concept in STEM? What factors increase confidence and motivation to pursue classes, majors, and careers in STEM?

3. Student sex (moderator) Identification with STEM experts (moderator) STEM attitudes Future career intentions about STEM Gender composition of STEM environment STEM identification Self-efficacy, behaviors show interest Professors Other experts Peers Stereotype inoculation model Stout, Dasgupta, Hunsinger, & McManus (2011). STEMing the tide: Using ingroup experts to inoculate women’s self-concept in science, technology, engineering, and mathematics (STEM). Journal of Personality and Social Psychology, 100, 255-270

4. Does contact with female (vs. male) math professors enhance women’s confidence in math, attitudes, performance, engagement in class?

5. Study 1 • Recruited female and male undergrads from an introductory calculus class (N = 96). All students were beginners in college. This course was a prerequisite for all STEM majors • Multiple sections. Recruited students from some sections taught by female professors and others taught by male professors. All sections used same syllabus, same exams, blind grading. • Tracked students from beginning of semester (Time 1) to end (Time 2). At both Time 1 & Time 2 we measured: • Attitudes toward math (implicit and explicit) • Identification with math (implicit and explicit) • How well they expected to do in class (confidence) • How much they identified with their math professor • Classroom dynamics • Final grade

6. Results • Women developed more positive implicit attitudes toward math if they happened to be in sections taught by female vs. male professors. Men liked math equally regardless of professor’s gender • Women implicitly identified with math more if they were in sections taught by female vs. male professors. Men identified with math equally regardless of professor’s gender. • Women developed more confidence in their math performance if they took the class with female vs. male professors. Men were equally confident regardless of professor’s gender. • Interestingly, women got higher grades in math than men regardless of professor gender. Yet their confidence fluctuated significantly depending on their professor’s gender.

7. Results (cont’d) • Women identified more with female vs. male professors. The more they identified with her, the more confident they felt about their own ability. • Male students identified equally with male and female professors. Identification with professors had no effect on their self-confidence. • Early in the semester, women participated in class equally regardless of professor. But by the end, they were more active in sections taught by female professors and more likely to seek help from her than him.

8. If contact with same-sex experts has a positive effect on female students, will contact with same-sex peers produce the same benefit?

9. Study 2: Effect of peers What gender composition of peers in academic settings is most beneficial for female students? Do women do better in learning environments with gender parity (50% female peers) or female majorities (75% females)? • Created 3 types of engineering peer groups that varied in gender. Assigned female engineering students (N = 96) to one of these groups • Female majority (3 women, 1 man) • Female parity (2 women, 2 men) • Female minority (1 woman, 3 men) • Variables measured: • Feelings about upcoming group activity: Feeling challenged vs. threatened • Students’ behavior in group: Interest, confidence, generate solutions? • How accurate was her knowledge of engineering concepts? • Post-group: Motivation to pursue engineering career

10. Results Women did best when assigned to groups withmostly female peers (female majority groups) compared to other two groups • Most challenged; least threatened • Participated more actively in the problem-solving task • Students who demonstrated knowledge of engineering during group task subsequently expressed more interest in pursuing engineering careers • Women did worst when assigned to groups with mostly male peers (female minority groups) compared to other two groups • Least challenged; most threatened • Least likely to participate in problem-solving task • Even women who demonstrated knowledge of engineering during group task did not uniformly express interest in pursuing engineering careers Groups with gender parity fell in the middle; less beneficial than groups with female majorities—at least for beginning students in engineering.

11. Translating results into concrete interventions for schools, colleges, and universities • Have more female instructors teach foundational courses in STEM • Introduce students to female scientists and innovators in other ways through special projects, internships, etc. • Personalize female scientists, mathematicians, and engineers by telling students how they got interested in their fields 4. For beginning students in STEM, create study groups of mostly female students to encourage students to develop mastery through group work with similar others 5. Finally, consider the timing of interventions: Most important in early transitional years; e.g., middle school, transition to high school, college, grad school.

12. Collaborators and Funding Graduate students Jane Stout Matthew Hunsinger Melissa McManus Math Department Colleagues Professors George Avrunin & Arline Norkin Undergraduate Research Assistants Elizabeth Baker, Joseph Bove, Dante Ciliberti, Tori Dennis, Gavin Desmond, Diana Fiore, Jessica Gorman, Alexandra Hamill, Thomas Holubiak, Sarah Krieger, Jody Pangburn, David Satin, Priya Senecal, Nicole Stewart, Patricia Torgerson, Gwendolyn Vincent, Octavia Willard, Michael Chapin, William Shattuck, Ryan Piers, Ada Aimua, Patrick Lowry, Andrew Boissonault, Julie Stiver, Matt Leonard, Ruta Kulkarni, Alicia McDermott, Anna Vacha, Sergio Sian, Gary Saldago National Science Foundation CAREER award (BCS 0547967)

13. Thanks!