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The Role of Attributions in Stereotype Threat Effects: Female Achievements in STEM Domains

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The Role of Attributions in Stereotype Threat Effects: Female Achievements in STEM Domains DePaul University Via Sapientiae College of Science and Health Theses and Dissertations College of Science and Health Summer 8-17-2012 The Role of Attributions in Stereotype Threat Effects: Female Achievements in STEM Domains Caitlyn Yantis DePaul University, [email protected] Follow this and additional works at: https://via.library.depaul.edu/csh_etd Part of the Psychology Commons Recommended Citation Yantis, Caitlyn, "The Role of Attributions in Stereotype Threat Effects: Female Achievements in STEM Domains" (2012). College of Science and Health Theses and Dissertations. 14. https://via.library.depaul.edu/csh_etd/14 This Thesis is brought to you for free and open access by the College of Science and Health at Via Sapientiae. It has been accepted for inclusion in College of Science and Health Theses and Dissertations by an authorized administrator of Via Sapientiae. For more information, please contact [email protected]. THE ROLE OF ATTRIBUTIONS IN STEREOTYPE THREAT EFFECTS: FEMALE ACHIEVEMENT IN STEM DOMAINS A Thesis Presented in Partial Fulfillment of the Requirements for the Degree of Master of Science BY CAITLYN ANNE YANTIS JULY, 2012 Department of Psychology College of Science and Health DePaul University Chicago, Illinois ii THESIS COMMITTEE Christine Reyna, Ph.D. Chairperson Ralph Erber, Ph.D. iii VITA The author was born in Baltimore, Maryland on August 30, 1988. She graduated from Loch Raven High School in 2006 and received her Bachelor of Science degree from the University of Mary Washington in 2010. TABLE OF CONTENTS Thesis Committee . ii Vita . iii List of Tables . iv List of Figures . v CHAPTER I. INTRODUCTION . 1 Stereotype Threat. 3 Stereotype Threat Contingencies . 4 Causal Explanations for Stereotype Threat Effects . 6 Attributions . 7 Attributions and Performance . 8 Attributions and Persistence . 9 Attributions and Self-Efficacy . 10 Attributions and Stereotypes . 10 Attributional Model of Stereotypes . 12 Rationale . 14 Statement of Hypotheses . 17 CHAPTER II. METHOD . 21 Procedure . 21 Domain Identification . 21 Attribution Manipulation . 22 Self-Efficacy . 23 Task Performance . 23 Exit Survey . 25 CHAPTER III. RESULTS . 27 Performance . 28 Persistence . 31 Self Efficacy . 34 Domain Identification . 36 Additional Analyses . 38 CHAPTER IV. DISCUSSION . 45 CHAPTER V. SUMMARY. 53 References . 53 Appendix A. Hypotheses . 61 Appendix B. Domain Identification Measure. 63 Appendix C. Attribution Manipulation. 65 Appendix D. Manipulation Check. 70 Appendix E. Demographics Questionnaire. 72 Appendix F. State Self-Esteem Scale . 74 Appendix G. Logical Reasoning Test . 76 Appendix H. Exit Survey . 84 iv List of Tables Table 1. Means and standard deviations of number of correct, attempted problems by group . 29 Table 2. Frequencies of number of correct, attempted problems by group . 30 Table 3. Means, standard deviations, and frequencies for number of problems attempted during persistence . 33 Table 4. Means and standard deviations for self efficacy pre- and post-test . 35 Table 5. Means and standard deviations for domain identification pre- and post-test . 37 Table 6. Correlations between attribution endorsement and achievement outcomes . 42 Table 7. Correlations between attribution endorsement and achievement outcomes (all participants included) . 44 v List of Figures Figure 1. Performance ratios by condition . 30 Figure 2. Performance ratios by condition (after square root transformation) . 31 Figure 3. Desire to persist by condition . 33 Figure 4. Pre- and post-test self efficacy by condition . 36 Figure 5. Pre- and post-test domain identification by condition . 37 Figure 6. Participants’ personal attributions for logical reasoning by condition . 40 Figure 7. Post-test attributions (all participants included) . 44 1 CHAPTER I INTRODUCTION The underrepresentation of women in science, technology, engineering, and mathematics (STEM) is a familiar problem, but the reasoning behind this gender gap is the subject of ongoing study. Although the gender gap in STEM subjects among students has been closing (Buchmann & DiPrete, 2006; Hyde, Lindberg, Linn, Ellis, & Williams, 2008), discrepancies remain on high-stakes exams such as the Scholastic Aptitude Test, Graduate Record Exam, and Advanced Placement tests. On these tests, males out- perform females consistently in science and mathematics (Halpern et al., 2007; Lubinski & Benbow, 2008). It is under the pressure and anxiety of such major diagnostic evaluations that male and female students begin to separate, with women falling behind. These gender differences on critical exams are mirrored in the continuing gender gap in college major selection. Although women are more likely than men to earn a college degree (Buchmann & DiPrete, 2006), there has been little change in female participation in STEM areas, where males typically dominate (Legewie & DiPrete, 2011). Specifically, men are significantly more likely to select engineering, computer science, and mathematics as a college major than are women (Peter & Horn, 2005). Gender differences in college major selection also translate to fewer women in STEM careers. For example, women only make up 5.9% of mechanical engineers and 29.5% of environmental scientists (US Department of Labor, 2010). This pattern holds in academia as well, where 92% of engineering professors and 87% of computer science professors are male (National Science Foundation, 2004). What are the driving forces behind this ongoing gender disparity? 2 One explanation for this continuing gender gap is a cultural environment in which gender stereotypes are particularly pervasive and influence not only perceptions of male and female ability in STEM areas, but also students’ performance in these domains. The stereotype that “math is male”, for example, has recently been shown to be acquired as early as second grade (Cvencek, Meltzoff, & Greenwald, 2011). Not only did young students associate math with male, but female elementary students had a much weaker identification with math than did males even at this early age. Studies such as this one indicate that the gender stereotypes related to STEM domains are understood very early and may then contribute to performance on high-stakes exams as well as interest in STEM fields later in life, where STEM gender stereotypes persist (Nosek & Smyth, 2011; Nosek et al., 2009). The internalization of such gender stereotypes can have severe consequences that lead to disengagement from the domain. In order to preserve self- esteem, it is common for individuals to selectively place less value on domains for which their group is stereotyped (Crocker & Major, 1989; Nieva & Gutek, 1981). Therefore, the pervasiveness gender STEM stereotypes can lead to disengagement from an early age, resulting in the gender disparities observed throughout secondary education and in the work force. In general, stereotypes can be debilitating in terms of performance and are influential in the gender STEM problem. Specifically, the phenomenon of stereotype threat can be strong enough to inhibit performance in several different domains, including important diagnostic tests such as the SAT and GRE that students pursuing these fields must take. 3 Stereotype Threat Stereotype threat is defined as “the concrete, real-time threat of being judged and treated poorly in settings where a negative stereotype about one’s group applies (Steele, Spencer, & Aronson, 2002, p. 389).” Feeling threatened by a salient stereotype about one’s group can hinder performance in different domains compared to when no stereotype threat is present. Stereotype threat effects have been observed with various social groups and with many different skills. For example, athletic performance of White participants was impaired compared to Blacks when a sports task was defined as diagnostic of natural ability (Stone, Lynch, Sjomeling, & Darley, 1999). In this case, White participants were threatened by the negative stereotype that Whites as a group are less skillful in athletics than are Blacks, which subsequently interfered with their ability to perform well. Useful skills for the workplace are also affected by stereotype threat. Men’s ability to decode nonverbal cues showed impaired performance when they were told this was a test of social sensitivity, on which women generally score higher (Koenig & Eagly, 2005). The stereotype that women are more sensitive and understanding served as a threat to the male participants, showing that stereotype threat can occur even with typically non-marginalized groups. Similarly, women’s ability to negotiate successfully was impaired when gender was made salient, indicating that females had an existing stereotype of men as superior negotiators (Kray, Galinsky, & Thompson, 2001). Perhaps the most often studied form of stereotype threat is in intellectual or academic domains. This research began with experiments showing that the possibility of confirming a negative racial stereotype about intellectual ability impaired Black students’ 4 performance on difficult verbal reasoning and math tests (Aronson, Quinn, & Spencer, 1998; Steele, 1997; Steele & Aronson, 1995). This effect was observed even when individual skills and level of preparation were accounted for, indicating that although the two racial groups were equally qualified, the negative stereotype present at the time of the test was enough to impair performance. This effect has been replicated with different tasks as well as with different target groups. White males who were highly identified with and proficient in math experienced impaired performance on a math test when comparisons were made with Asians, who are stereotyped as exceling in mathematics (Aronson, Lustina, Good, Keough, Steele, & Brown, 1998; Smith & White, 2002). Furthermore, when a difficult math test was described as producing gender differences, women performed much worse than men even though the two groups were equally qualified (Spencer, Steele, & Quinn,.
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