why they leave: the impact of stereotype threat on the ... 2012.pdf · 430 m. a. beasley, m. j....

Soc Psychol Educ (2012) 15:427–448DOI 10.1007/s11218-012-9185-3

Why they leave: the impact of stereotype threaton the attrition of women and minorities from science,math and engineering majors

Maya A. Beasley · Mary J. Fischer

Received: 26 May 2011 / Accepted: 20 March 2012 / Published online: 23 June 2012© Springer Science+Business Media B.V. 2012

Abstract This paper examines the effects of group performance anxiety on the attri-tion of women and minorities from science, math, and engineering majors. While pastresearch has relied primarily on the academic deficits and lower socioeconomic statusof women and minorities to explain their absence from these fields, we focus on theimpact of stereotype threat—the anxiety caused by the expectation of being judgedbased on a negative group stereotype. Using data from the National LongitudinalSurvey of Freshmen, our findings indicate that minorities experience stereotype threatmore strongly than whites, although women do not suffer from stereotype threat morethan men. Our findings also reveal that stereotype threat has a significant positiveeffect on the likelihood of women, minorities, and surprisingly, white men leavingscience, technology, engineering and math majors.

Keywords Minorities · Women · Higher education · Science · Majors ·Stem fields · Stereotype threat

1 Introduction

In January 2005, during a speech to the National Bureau of Economic Research,Lawrence Summers, then President of Harvard University, observed that innate dif-ferences between men and women may be to blame for the lack of women in scientificand mathematical careers. Specifically, Summers asserted that “In the special case ofscience and engineering, there are issues of intrinsic aptitude, and particularly of the

M. A. Beasley (B) · M. J. FischerUniversity of Connecticut, Storrs, CT, USAe-mail: [email protected]

M. J. Fischere-mail: [email protected]

123

428 M. A. Beasley, M. J. Fischer

variability of aptitude, and that those considerations are reinforced by what are, infact, lesser factors involving socialization and continuing discrimination” (Summers,2005). His assertion was not unlike those made in the controversial 1994 book TheBell Curve, which purported that the lower test scores and grades of African-Amer-icans and Hispanics were due to inferior cognitive function (Herrnstein and Murray1994). While each of these events spurred a storm of debates and ill-will within theacademy, they also identified an increasing problem in the United States: a criticalunderrepresentation of women and minorities in the sciences.

The dearth of science, technology, math and engineering (STEM)1 professionalsis in part, a consequence of the low rate of minority and female majors in these aca-demic disciplines. As Elliott et al. (1996) observe, “You can’t play if you don’t stay,and leaving science or premed for education or history usually means leaving scienceor premed forever” (p. 706). It is virtually impossible to pursue a graduate degree orcareer in STEM without first majoring in a STEM field. Although a significant num-ber of underrepresented minorities and women may express interest in STEM fieldsprior to or at the start of college, the number who ultimately major in these fieldsis considerably smaller. Out of a sample of four Ivy League institutions, only 34 and55 % of African-Americans and Hispanics who initially expressed a interest in sciencepersisted as science majors relative to 70 and 61 % of Asian and White students respec-tively (Elliott et al. 1996). National estimates follow a similar pattern. In 2004 the ratioof the proportion of entering White freshman who intended to major in STEM relativeto White STEM graduates was 0.76 while the respective figures for African-Americansand Hispanics2 were each only 0.57 (National Science Foundation 2007).

To explain the scarcity of minority and female STEM majors, previous researchhas often focused on the academic deficits of minority students (Elliott et al. 1996;Stangor and Sechrist 1998) and the inaptitude of women to perform in quantitative orscientific disciplines (Holden 1998; Beckham et al. 1988). Educational statistics doindicate that a considerable amount of the racial disparity in initial STEM interest canbe attributed to inequalities in primary and secondary education. African-American,Latino and White students have notably different educational opportunities. Specifi-cally, Whites fare better than Blacks and Latinos in teacher quality, curriculum, classsize, and school size, all of which are correlated with academic performance (Darling-Hammond 2004). However, while academic preparation does account for part of theloss of Black and Hispanic STEM majors, as research can attest considerable var-iation in the degree of preparation and socioeconomic background at each level ofperformance remains (Aronson et al. 1998; Steele 1997; Steele and Aronson 1995).Such findings are compounded by the erroneousness of claims that the deficit of Afri-can-Americans in STEM is based on differences in aptitude. As Stangor and Sechrist(1998) point out, “Since many students choose their final majors after their first yearin school, it seems unlikely that aptitude is playing a large part in determining them.”Moreover, the high rate of STEM graduates within historically Black colleges and

1 For the purposes of this article, STEM fields do not include social sciences or psychology—fields inwhich both minorities and women are better represented.2 Hispanics of Puerto Rican or Chicano descent.

123

Why they leave: the impact of stereotype threat 429

universities (HBCU’s) indicates that there is both an interest and the ability to com-pete within these fields among students of color. In 2004, for example, 19 % of HBCUgraduates were in STEM fields relative to 17 and 30 % of Whites and Asians at allinstitutions (National Science Foundation 2007).3

Differences in academic performance by gender, although limited primarily toSTEM fields, have had similar explanations. Some, like Summers, have suggestedthat it is a genetic difference in ability (Benbow and Stanley 1980; Robinson et al.1996; Geary 1996; Benbow et al. 2000). For example, arguments that spatial abil-ities vary by gender (Hedges and Nowell 1995; Fennema and Sherman 1977) arenot uncommon. However, research has also provided evidence that the differencelies not in the aptitude of boys and girls, but in the different ways in which boys andgirls believe intelligence and academic performance are related (Georgiou et al. 2007).Others have proposed that the disparity in male-female performance is largely a matterof socialization and subsequent interest levels, particularly in primary and secondaryschool classrooms (Campbell and Beaudry 1998; Updegraff and Eccles 1996; Eccleset al. 1990). Yet as is the case for minorities, the fact that some women (of all races) do,at least initially, intend to major in STEM fields, suggests that differences in aptitude,socialization, and interest alone cannot explain the movement of young women fromSTEM disciplines to social sciences and humanities while in college.

2 Stereotype threat and undergraduate attrition from STEM fields

Given the limited research that directly addresses the high rates of minority and femaledrop-outs from STEM disciplines at the college level, we must consider additional the-ories. In this study, we examine the role of stereotype threat in the attrition of womenand minorities from STEM majors. Defined as the social-psychological threat arisingfrom a situation or activity for which a negative stereotype about the actor’s groupapplies (Steele 1997; Steele and Aronson 1995), stereotype threat has been used toexplain the underperformance of minorities and women in a variety of domains. Spe-cifically, it is the anxiety individuals from stigmatized groups have that their behaviormight confirm—to others or even to themselves—the negative stereotypes imposedupon their group (Spencer et al. 1999). Stereotype threat is a complex phenome-non that has multiple explanations (Steele et al. 2002b). On one hand, it underminesachievement by interfering with performance on mental tasks by, among other things,increasing blood pressure (Blascovich et al. 2001) and reducing working memorycapacity (Schmader and Johns 2003). Stereotype threat also drives students to defendtheir self-esteem by disengaging from the domain in question (Aronson et al. 1998).That is, expected or actual threats to identity in a given area prompt individuals tomake the domain less central to self-concept (Major et al. 1998).

In 1995, Steele and Aronson performed a series of clinical studies which havebeen replicated with similar results myriad times on women and racial/ethnic minor-ities (Schmader et al. 2001, 2004; Major et al. 1998; Quinn and Spencer 2001).

3 While only 21 % of African-Americans received their college degrees from HBCUs, 30 % of African-Americans who received a degree in STEM graduated from an HBCU. Black.

123


In the first study, (Steele and Aronson 1995), African-American and White studentswere asked to take an identical exam and were broken into two groups. One groupwas told the exam was based on cognitive ability whereas in the other, the examwas presented without reference to aptitude. African-Americans performed worsethan their White counterparts when the test was described as a measure of ability,but performed equally to Whites when the test was presented as reflective of some-thing else. In the second study, groups were divided into a race-prime category—in which students were required to list their race prior to taking the test—and anon-prime group in which students were asked to list their race at the close of theexam. African-Americans in the race-prime group fared worse than any other group,while African-Americans in the non race-prime group performed equally to Whites(Steele and Aronson 1995). The results of these types of experiments indicate that sim-ple awareness of a stereotype is sufficient to reduce women and minority’s intellectualperformance.

The negative effects of stereotype threat are not limited, however, to explicit situ-ational reminders. They may instead be implicitly activated in domains in which thestereotypes are well known. For example, women who participated in an exam withmen performed worse than those who participated with only women (Inzlicht andBen-Zeev 2000). In essence, susceptibility to stereotype threat requires only that indi-viduals are aware of negative stereotypes about their group and that they recognize thepotential that they will be judged by those stereotypes (Steele et al. 2002a,b; Wheelerand Petty 2001). Most germane to the study at hand, this threat is particularly pertinentto those who closely identify with a given domain, as its strongest influence is on thevanguard of these groups. That is, stereotype threat has the greatest impact on thoseindividuals with the skills and self-confidence to have identified with a field in whicha negative stereotype about their group is particularly salient (Steele 1997).

In this article we examine whether the reputation of math, science, and engineeringas hostile environments for minorities and women and the subsequent expectationof racism and sexism in these fields may provoke these students to ultimately with-draw from STEM majors. Although psychologists have conducted numerous studiesto identify the effects of stereotype threat in isolated instances such as taking the SATor other exams (See for example Steele 1997; Steele and Aronson 1995), the cumula-tive effects of this threat in a long-term, situation outside of a laboratory have not beencomprehensively examined. Steele et al. (2002a,b) suggests that aside from its effectson performance, stereotype threat also decreases the degree of engagement individu-als have with a given domain. In an attempt to defend their self-esteem, individualsmay temporarily “disengage” from a specific situation (e.g. an exam), detaching theiregos from their performance in that domain. In these cases, individuals remain iden-tified with the domain, but selectively choose not to identify with a specific situation(Major et al. 1998). Continuous disengagement resulting from repeated experiencesof racial antagonism may, however, influence persons to “disidentify” entirely with adomain by continuously distancing themselves from their performance in that area.That is, repeated instances which trigger disengagement may eventually cause peopleto permanently opt out of that domain (Major et al. 1998; Nussbaum and Steele 2007).

Although psychological studies have repeatedly tested and demonstrated the effectof short-term disengagement (Major et al. 1998; Crocker and Major 1989; Major and

123


Schmader 1998; Nussbaum and Steele 2007), we know very little about long-termdisidentification. Hence, a key question is whether stereotype threat impacts disiden-tification and ultimately attrition from STEM fields. Fischer and Massey’s (2007) find-ings, that felt performance burden (based on externalized stereotypes) and decreasingwork effort (based on internalized stereotypes) over time are negatively related toacademic performance, is the starting point of the present research. Rather than exam-ining the indirect relationships between internalized and externalized stereotypes toperformance, however, we explore their direct effects on leaving STEM majors. Giventhe high rates of attrition of women and minorities from STEM disciplines and theirabsence from STEM graduate programs, it is imperative to determine whether andhow stereotype threat plays a role.

Our primary hypothesis is that (H1) the experience of stereotype threat forAfrican-Americans, Hispanics, and women4 is positively related to their attrition fromscience, math, and engineering majors. One aspect of stereotype threat which is espe-cially salient to this study is that it can be activated implicitly in domains in whichstereotypes are prevalent. For example, Chavous et al. (2004) found that Black studentsshowed notably greater levels of stereotype expectations in traditionally male-dom-inated majors than they did in majors with greater female or minority presences.Likewise, low levels of female or minority representation heightens expectations ofstereotypic evaluations in group work situations (Cohen and Swim 1995). Thus, theeffect of stereotype threat is likely to be heightened in learning situations in whichstereotypes are well-known and students (of any race or gender) are prone to makemistakes. In the following sections we provide further theoretical arguments for therelationships between stereotype threat and race and gender.

3 The role of stereotype threat in the attrition of minorities from STEM majors

African-Americans are perhaps the most marginalized racial group on college cam-puses and are especially susceptible to negative stereotypes. In a study of undergrad-uates at an Ivy League university, Torres and Charles (2004) found that White stu-dents consistently held racial stereotypes of African-Americans as unqualified for theUniversity, able to attend only because of affirmative action quotas or athletic ability. Inturn, over 75 % of African-American participants believed that most Whites assumedthey were the recipients of preferential treatment and incapable of being accepted ontheir own academic merits. Given the high rate of Black attrition from STEM majorsand the commonly-held negative stereotypes against African-Americans in academia,we believe (H2) stereotype threat will have a significant positive relationship to Blackattrition from STEM majors.

Hispanics are also stereotyped as being undeserving recipients of affirmative actionin college admissions and do have a low rate of STEM graduates. In 2004, for exam-ple, only 14 % of baccalaureates awarded to Hispanics were in STEM fields (NationalScience Foundation 2007). While the low rate of Hispanic STEM graduates is well-known, the majority of studies concerning their college experiences focus only ontroubles related to socioeconomic status and cultural differences (Sy and Brittian 2008;

4 White and non-White women.

123


Alberta et al. 2005). Although we take the differences between minority groups seri-ously, Hispanics’ marginalized status on college campuses may well mean they expe-rience stereotype threat in STEM fields in much the same ways as African-Americans.Indeed, Smedley et al. (1993) found that Hispanic students on predominantly Whitecollege campuses experience significant psychological stresses and social tensionswith White peers and faculty. Hispanic students also expressed high rates of perceivedracial antagonism. Such racial tensions are directly related to Hispanic students’ adjust-ment to college (Hurtado et al. 1996). Moreover, Hispanic adolescents who experiencehigh levels of psychosocial stress, such as those caused by racial antagonism, are morelikely to have anxiety, receive lower grades, and perceive themselves as less compe-tent academically (Alva and de Los Reyes 1999). Thus like African-Americans, (H3)we expect Hispanics who experience stereotype threat to have a greater likelihood ofattrition from STEM majors.

Asian Americans present perhaps the most difficult minority group about which tomake predictions. On the one hand, they are a marginalized group. On the other hand,however, Asians are considered a “model minority”. This stereotype first appeared inthe mid 1960s, in large part to discredit the demands of African-Americans for eco-nomic justice (Wong et al. 1998). A 1966 US News and World Report article entitled“Success Story of One Minority Group in the U.S.” observed, “At a time when it isbeing proposed that hundreds of billions be spent to uplift Negros and other minori-ties, the nation’s 300,000 Chinese Americans are moving ahead on their own—withno help from anyone else” (U.S. News and World Report, 1966 p. 73). According tothe current model minority stereotype, Asian-Americans perform well in school andwork, are diligent and self-sufficient, and are effectively a model for other groups,particularly other minorities, to follow (Zia 2001). Previous research on universitystudents found that not only did non-Asian students believe this stereotype, but thepreponderance of Asian-American students accepted it as well. In particular, Asianand non-Asian students perceived Asian-Americans to be better prepared, more moti-vated, and have a greater likelihood of career success than Whites (Wong et al. 1998).Given the positive stereotype about Asian-Americans’ aptitudes in STEM fields, (H4)we expect that stereotype threat does not affect their attrition from such majors.

4 The role of stereotype threat in the attrition of women from STEM majors

The stereotype that girls and women are bad at math and science is also well-knownthroughout the U.S. (Park et al. 2001) and has been implicated in the long-term careerinterests of women (Eccles and Wigfield 2002). Although women who major in thesedisciplines may not buy into the stereotype, they are quite familiar with it. Rine-hart and Watson (1998), for example, found that women in engineering were morelikely than men to sense discriminatory behavior by their professors. Likewise, Steeleet al. (2002a,b) found that undergraduate women in male-dominated disciplines hadstronger perceptions of discrimination towards themselves and other women than didwomen in other disciplines, yet they were no less identified with male-dominated fieldsof study. Based on psychological studies, it is evident that these concerns impact theperformance of women in STEM disciplines. Prior clinical research on stereotype

123


threat has firmly established that the activation of this stereotype increases anxietyand causes women to perform worse on tests in these fields than they otherwise would(Spencer et al. 1999; Steele 1997; Shih et al. 1999). Based on the impact of stereotypethreat in isolated situations and its proclivity to activate in settings in which groupmembers are underrepresented, (H5) we anticipate women who experience stereotypethreat to have a greater likelihood of attrition from STEM majors.

5 Race-gender interactions

Aside from the persistent trend among women and minorities respectively to avoidcollege majors in science, math, and engineering, regardless of skill (Stangor andSechrist 1998; Schmader et al. 2004), female minorities are conspicuously scarceamong STEM graduates. Whether this is simply an additive effect of gender and race,or whether race and gender have distinct interactions is unclear. The paradox betweenthe greater proportion of female college attendance among minorities and the absenceof women of all races with STEM degrees requires a more complex examination of therole of stereotype threat in STEM attrition for men and women of color. In 2004 alone,67 and 62 % of Black and Hispanic college graduates respectively were female yetonly 53 and 42 % of Black and Hispanic STEM grads were female (National ScienceFoundation 2007). We must therefore question not only how stereotype threat affectsfemale and minority participation in STEM majors, but how the interaction betweenrace and gender creates different effects for women and men of color.

Black women, for example, outpace their male counterparts at all levels of degreeconferrals (Cohen and Nee 2000). However, Black men still represent nearly one-half of African-Americans receiving degrees in STEM (National Science Foundation2007).5 One possible explanation is that Black women face a double threat; that is,being a member of multiple marginalized groups has an additive effect (Brown 2000).Black women do indeed carry negative stereotypes on two fronts. Accordingly, wemight expect Black women to be more vulnerable to stereotype threat than Blackmen. However the lower rate of Black male degree conferral indicates that Black menmay well suffer from stereotype threat as well. In 2004, the ratio of the proportionof Black female freshman intending to major in STEM relative to the proportion ofBlack women graduating with STEM degrees was 0.61. That same year, the figurefor Black men was 0.60 (National Science Foundation 2007). Cohen and Nee (2000)stipulate that the absence of Black men at predominantly White colleges and univer-sities may exacerbate their negative experiences on these campuses. Black men maybe particularly susceptible to stereotype threat due to their minimal campus presenceand overrepresentation in college athletics (Lederman 1992). Given the absence ofBlack men on predominantly White campuses, and the additional liability of multiplemarginalized identities of Black women, (H6) we anticipate stereotype threat willhave a positive association with Black men and women’s attrition from STEM majors.Whether stereotype threat has a stronger association with attrition among Black menor Black women, however, is unclear.

5 According to 2004 figures.

123


The interaction of gender and race among Hispanics is also complex. Like Afri-can-Americans, a large majority of Hispanic graduates are women, but few of thosegraduates receive science, math or engineering degrees. While Hispanic males repre-sent only 38 % of Hispanic college graduates, they comprise 58 % of all HispanicSTEM graduates (National Science Foundation 2007). Yet, although the propor-tion of Hispanic and African-American male graduates may be similar, there isa markedly larger proportion of Hispanic males in STEM than Black men. As58 % of the Hispanic population receiving science, math and engineering degrees,they have a larger presence in those fields than their Black male counterparts andtherefore may not suffer to the same degree as Black men or Hispanic womenin STEM attrition. In contrast, the double burden of multiple marginalized identi-ties faced by Latinas makes their susceptibility to stereotype threat greater withinSTEM majors. Thus, (H7) we expect stereotype threat to have a stronger associationwith attrition from STEM for Hispanic women than it does for their male counter-parts.

Asian-American women, present yet another puzzle. While the model minor-ity stereotype is not limited to Asian-American men, Asian-American womendo face negative stereotypes about gender within and outside of Asian-Americanpopulations. Media portrayals of Asian and Asian-American women depict themas delicate, shy and exotic (Espiritu 1997; Kang 1993), characteristics antitheti-cal to scholarship or careers. Moreover, while the general stereotype of Asian-Americans is closely associated with STEM, the general stereotype of women isnot.

The question is which identity—Asian-American, female, or Asian female—is most salient? Past research (Shih et al. 1999) established that performance isdependent on which stereotype is triggered. For individuals with multiple iden-tities relevant to a given task, the more/most salient identity exerts a strongerinfluence. In a recent series of experiments on stereotype awareness (Sinclairet al. 2006) Asian-American women believed they were evaluated less favorablyin math when their gender was salient, but more favorably when their ethnicitywas salient. Likewise, Shih et al. (1999) found that Asian-American women per-formed better on a quantitative test when their ethnicity was activated but worsewhen their gender was activated relative to a control group without a prompt.Yet in a similar set of studies, Cheryan and Bodenhausen (2000) found just theopposite: that Asian-American women’s performance on a math test was signifi-cantly lower when ethnicity was primed but not significantly changed when gen-der was primed. Their research showed that the relationship between their iden-tity as Asian and their performance was not direct, however, but mediated by adecrease in the ability to concentrate. Thus, Asian American women did not losemotivation due to the ethnic prime, but they did lose concentration which ulti-mately decreased their performance. Our research, however, focuses on long-termmotivation, not short-term performance. Hence (H8), we expect stereotype threatto have no significant association with attrition from STEM for Asian men. How-ever, (H9) because Asian women experience negative gender stereotypes, we predictstereotype threat will have a negative association with attrition from STEM for Asianwomen.

123


6 Methods and measures

The data for this study comes from the National Longitudinal Survey of Freshmen(NLSF), a probability sample of nearly 4000 students who matriculated into 28selective colleges and universities as first time freshmen in the Fall of 1999.6 Thebaseline sample included 998 Whites, 959 Asians, 916 Latinos, and 1,051 AfricanAmericans. The survey was designed to gather extensive information about respon-dents prior to their entering college and to measure their initial attitudes, motiva-tions, and perceptions. A detailed description of the sampling methodology, includ-ing the 28 institutions and their characteristics, is contained in Massey et al. (2006).This initial interview was followed-up with subsequent surveys conducted by tele-phone in the spring of each academic year. In this paper, we focus on the intendedmajor of students from wave 1 as they entered college, their background character-istics gathered during this initial survey, their early college experiences recorded inwaves 2 and 3, and their subsequent retention or departure from STEM measured inwaves 2–4.

7 Examining the attrition of STEM and non-STEM majors

Our measure of initial intention to major in a STEM major comes from the wave1 NLSF interview. Students who stated that they intended to major in engineering,science, math, or computing majors were coded ‘1’ on this measure, while all otherresponses were coded ‘0’. As such, the main dependent variable in our analyses iswhether these students who initially intended to major in STEM ended up staying in aSTEM major. Our measure of attrition from STEM is coded 1 if the student reporteda non-STEM major in the latest year they were observed in the sample, thereby pre-ferencing the major named in the senior year if the student was still in the sample atthat point. If the student was unobserved in wave 5, we moved to wave 4 to constructattrition from STEM. For those missing from waves 4 and 5, we looked instead towave 3.7 Table 1 shows the percent of students leaving STEM majors by race/eth-nicity and gender. As can be seen, Asian men have the lowest attrition from STEMat 14 %, followed by Hispanic men at 32 % and White men at 34 %. Black men andwomen are the most likely to leave STEM majors at 47 and 41 % respectively. Thispaper will examine what factors account for STEM attrition and whether these factorsdiffer by race/ethnicity and gender.

8 Stereotype threat and performance anxiety measures

Our primary measure of stereotype threat is what we call group based performanceanxiety, which is derived from a series of questions from the third wave about race

6 The NLSF has been used in a variety of notable psychological and sociological studies in recent yearsincluding Massey et al. (2006); Charles et al. (2009); Ehrmann (2007); Rivas-Drake and Mooney (2008). Asof 2011, it was the most recent longitudinal, non-experimental dataset focused on college students available.7 Students who eventually dropped out of school were not included in this sample.

123


and/or gender self-consciousness and the extent to which students feel that their indi-vidual performance reflects upon their group. Items include student’s agreement onthree statements: “if I excel academically it reflects positively on my group”, “if I dopoorly academically it reflects negatively on my group”, and “if I don’t do well peoplewill look down on others like me”. The alpha value for this scale is 0.73.

We also control for what we call general performance anxiety: the extent to whichstudents feel pressure or anxiety unrelated to their group identity to perform academ-ically. Because stereotype threat is sometimes confused with a more general anxiety,it is particularly important to include this as a separate variable. This measure is basedon two questions: the extent to which a student agrees that if his/her instructor knowss/he is having difficulty with class they will think less of the student and the extent towhich the student believes fellow students will think less of him/her if they know s/heis having difficulty with class. The alpha value for this scale is 0.76.

9 Methodology

Our analysis takes place in three stages. First, we examine the characteristics ofstudents who declare a STEM major as they are entering college compared to thosewho are undeclared or who declared a non-STEM major using a logistic regression.This model helps us to understand whether there are significant differences betweenstudents who had a STEM major in mind at college entrance compared to those whodid not. Next we conduct an analysis of variance on the mean group anxiety expe-rienced by respected race-gender groups to determine whether there are significantdifferences based on these identities. The final stage of the analysis uses a series oflogistic regressions to examine the factors related to leaving STEM majors amongthose who entered college as declared STEM majors. We are particularly interestedin whether group based performance anxiety played a role in attrition.

10 Results

We begin this section by examining the racial and gender composition of students thatentered with the intent to major in a STEM field. About one in five of students in the

Table 1 Percent of students that declare and leave STEM fields by race and gender

Declare STEM Leave STEM

Male N Female N Male N Female N

Black 22 353 19 638 47 98 41 64

Hispanic 23 384 14** 532 34 75 44 88

Asian 29 417 18*** 542 14 86 34*** 104

White 24 475 17** 523 32 64 39 74

Numbers do not coincide due to lack of response to certain questionsT-tests by gender∗ p < .05, ∗∗ p < .01, ∗∗∗ p < .001

123


NLSF sample arrived at college intending to major in science, engineering or math.As shown in Table 1, this percentage varies somewhat by race/ethnicity and gender,with Asian men being most likely to express an intention to major in STEM (29 %)followed by White, Hispanic and Black men at 24, 23 and 22 %, respectively. In allcases, except for African-Americans, women were far less likely to enter intending tomajor in STEM than their male counterparts. Specifically, 18 % of Black and Asianwomen intended to major in STEM while 17 % of White women and only 14 % ofHispanic women did so.

Table 2 shows the results from a logistic regression predicting whether a studentdeclared a STEM major at college entrance versus being undeclared or declaringanother major. In all cases, Asian males are used as the comparison group given thepositive stereotype associated with their abilities in STEM fields Stereotypes of Asian-American academic ability are generally quite positive, particularly those pertainingto STEM fields (Ho and Jackson 2001). This reflects the more general stereotype ofAsian Americans as hard workers with high intelligence associated with the “modelminority” myth (Sue et al. 1995). Asian-American men are especially well-suited as acomparison because they have escaped the negative gender stereotypes still ascribedto Asian-American women and are explicitly regarded as high performers in STEMfields relative even to white men (Gupta et al. 2011; Lin et al. 2005).

As shown in Model 1, STEM declarers had significantly higher high school GPAsthan did those who had not declared STEM majors (B = 2.09). However, income,the number of AP courses taken, family income, and whether at least one parent hadattended college had no significant effects on the likelihood of being STEM majors.Turning to gender and race, Model 2 shows that females were significantly less likelyto declare a STEM major than men (B = 0.59). Hispanics and Whites were bothless likely than Asians to enter college with a declared STEM major, (B = 0.88) and(B = 0.80) respectively, although not significantly. Blacks, on the other hand, weremore likely to enter with a STEM major than Asians (B = 1.06), but not signifi-cantly. Model 3 replaces race and gender variables with interaction terms.8 In thiscase, White (B = 0.50), Asian (B = 0.51), Hispanic (B = 0.79) and Black (B = 0.87)women were all significantly less likely to have declared STEM majors than theirmale counterparts.9

Having found that those who declared STEM majors are in some ways differentthan those who entered college undecided or as non-STEM majors we now ask whethermen and women from different racial groups who declared STEM majors experiencethe same degree of group and general anxiety. Table 3 displays the means and standarddeviations.

While gender appears to play a minimal role in differences among mean groupperformance anxiety, the results of a one-way analysis of variance indicate that racehas a significant effect (F = 44.39, p < .001). As shown in Table 3, Black men and

8 We were unable to run a third model in which interaction terms and basic variables were used due toissues of multicollinearity.9 Please note: when White men were used as the control group instead of Asian men the results (not shown)were virtually identical. However, while the effect of being a White male was negative but insignificant,being an Asian male was positive but insignificant.

123


Tabl

e2

Log

istic

regr

essi

onof

stud

ents

’in

tent

tom

ajor

inST

EM

field

s

Mod

el1

Mod

el2

Mod

el3

Exp

(β)

βSE

Exp

(β)

βSE

Exp

(β)

βSE

Bac

kgro

und

char

acte

rist

ics

Fam

ilyin

com

e0.

87−0

.14

(−0.

08)

0.84

*−0

.17

(−0.

08)

0.84

−0.1

7*(−

0.08

)

1≥

Pare

ntco

llege

grad

1.07

0.07

(−0.

12)

1.07

0.07

(−0.

12)

1.07

0.06

(−0.

12)

Num

ber

ofA

Pco

urse

s1.

030.

03(−

0.02

)1.

020.

02(−

0.02

)1.

020.

02(−

0.02

)

GPA

2.09

0.74

***

−0.1

42.

320.

84**

*(−

0.15

)2.

290.

83**

*(−

0.15

)

Rac

e

Bla

ck–

––

1.06

0.06

(−0.

12)

––

–

His

pani

c–

––

0.8

−0.2

2(−

0.12

)–

––

Whi

te–

––

0.88

−0.1

3(−

0.11

)–

––

Fem

ale

––

–0.

59−0

.54*

**(−

0.08

)–

––

Rac

e-ge

nder

inte

ract

ions

Bla

ckm

ale

––

––

––

0.87

−0.1

4(−

0.18

)

Bla

ckfe

mal

e–

––

––

–0.

63−0

.47*

*(−

0.15

)

His

pani

cm

ale

––

––

––

0.79

−0.2

3(−

0.16

)

His

pani

cfe

mal

e–

––

––

–0.

41−0

.89*

**(−

0.17

)

Asi

anfe

mal

e–

––

––

–0.

51−0

.68*

**(−

0.16

)

Whi

tem

ale

––

––

––

0.8

−0.2

2(−

0.15

)

Whi

tefe

mal

e–

––

––

–0.

50−0

.70*

**(−

0.16

)

Con

stan

t−4

.16*

**(−

0.53

)−4

.14*

**(−

0.56

)−4

.02*

**(−

0.56

)

χ2

38.9

5***

86.6

8***

89.6

4***

Log

likel

ihoo

d−1

97.6

1−1

893.

75−1

892.

27

∗ p<

.05,

∗∗p

<.0

1,∗∗

∗ p<

.001

123


Table 3 ANOVA of mean group anxiety and general anxiety by race and gender

Group anxiety General anxiety

Mean SD N Mean SD N

Black male 17.12 7.19 77 4.86 4.41 77

Black female 17.76 6.47 111 3.87 4.42 111

Hispanic male 13.44 7.52 86 5.02 4.11 86

Hispanic female 13.99 7.18 72 4.04 4.05 73

Asian male 12.88 6.06 117 5.37 3.92 117

Asian female 12.88 5.70 91 5.15 4.01 91

White male 10.05 5.93 107 4.26 3.00 107

White female 9.73 5.84 83 4.51 3.31 83

SS Btw Races 5532.52 123.18

F 44.39*** 2.67*∗ p < .05, ∗∗ p < .01, ∗∗∗ p < .001

women by far score the highest on group based performance anxiety with means of17.12 and 17.16. Hispanic women are and men have significantly lower group anxietylevels of 13.99 and 13.44. Asians’ group based performance anxiety is slightly loweron average; both men and women have a mean group anxiety of 12.88. Whites havethe lowest mean group anxiety levels such that White men and White women havegroup anxiety averages of 10.05 and 9.73 respectively.

We also examined the mean general anxiety for each racial-gender group. Asian menand women report the highest levels of general performance anxiety of 5.37 and 5.15respectively, but are followed closely by Hispanic men who average 5.02. Black menand White women report average scores of 4.86 and 4.51 which are close to White menand Hispanic women whose mean general anxiety levels are 4.26 and 4.04 respectively.Black women have the lowest average general performance anxiety averaging 3.87.

While it is evident that men and women of different racial groups experience sig-nificantly different levels of group based anxiety (stereotype threat), the impact of thatanxiety is a separate issue. We turn to our primary research question: how does groupbased performance anxiety influence the attrition of different racial and gender groupsfrom STEM majors.

Table 4 shows a series of logistic regressions predicting the odds of leaving a STEMmajor for those students who entered college as STEM majors. Model 1 shows that stu-dents with higher high school GPA’s are significantly less like to leave a STEM majors,although the number of AP courses taken, whether at least one parent had attendedcollege, and family income all had insignificant effects. This finding provides mixedsupport for the work by Massey et al. (2006) which found that the academic dis-advantages of minority students help explain racial differences in college academicperformance. However, this model does not lend support to our general expectationthat stereotype threat has a positive impact on STEM attrition.

Model 2 adds controls for race and gender, all of which are positively associated withthe odds of leaving a STEM major. Because Asians had the lowest rate of attrition fromSTEM majors—23 %—and have a positive stereotype related to their performance in

123


Table 4 Logistic regression analysis of attrition from STEM majors

Model 1 Model 2 Model 3

β SE β SE β SE

Background characteristicsFamily income −0.12 (−0.17) −0.10 (−0.18) −0.13 (−0.18)

1 ≥ Parent college grad −0.16 (−0.24) −0.22 (−0.25) −0.20 (−0.25)

Number of AP courses −0.08 (−0.05) −0.04 (−0.05) −0.04 (−0.05)

GPA −0.79** (−0.29) −0.85** (−0.3) −0.78* (−0.31)

Anxiety

General −0.01 (−0.02) 0.00 (−0.02) −0.01 (−0.02)

Group 0.01 (−0.01) 0.01 (−0.01) −0.07* (−0.03)

Race

Black – – 0.64* (−0.26) −0.44 (−0.74)

Hispanic – – 0.65* (−0.26) −0.06 (−0.75)

White – – 0.64** (−0.25) −0.57 (−0.76)

Female – – 0.45* (−0.17) 0.30 (−0.55)

General anxiety

Black male – – – – 0.04 (−0.05)

Black female – – – – −0.04 (−0.04)

Hispanic male – – – – 0.03 (−0.06)

Hispanic female – – – – −0.05 (−0.06)

Asian female – – – – −0.03 (−0.06)

White male – – – – −0.05 (−0.07)

White female – – – – −0.04 (−0.06)

Group anxiety

Black male – – – – 0.08* (−0.03)

Black female – – – – 0.09** (−0.03)

Hispanic male – – – – 0.04 (−0.04)

Hispanic female – – – – 0.09* (−0.04)

Asian female – – – – 0.06 (−0.04)

White male – – – – 0.11** (−0.04)

White female – – – – 0.12** (−0.04)

Constant 2.53* (−1.11) 1.95 (−1.16) 2.50* (−1.23)

χ2 17.42** 34.81** 55.27***

Log likelihood −402.49 −393.80 −383.57

N=637∗ p < .05,∗∗ p < .01,∗∗∗ p < .001

STEM fields, we again used this as our reference group. Accordingly, Black, Hispanicand female identities all increase the likelihood of STEM attrition relative to Asianor male identities. Surprisingly, however, Whiteness also increases the likelihood ofSTEM attrition. While we anticipated that White women had a greater likelihood ofSTEM attrition, our assumption was based on the anticipated negative effects of their

123


gender, not their race. The results in Model 2, however, indicate that being White ascompared to being Asian, regardless of gender, has a positive influence on attrition.Thus being Black, Hispanic, White and female, all increase the likelihood of attritionfrom STEM majors.

In Model 3, we add interactions between each racial and gender category withgroup anxiety and general anxiety. Due to issues of multicollinearity among categori-cal variables, however, we were unable to provide a model which examines the basicand interaction terms for race and gender together in addition to race-gender-anxietyinteractions. Following the recommendations of Hair et al. (1995) we did not includethe variable primarily responsible. In this case, it meant the exclusion of race-genderinteractions. Although we recognize that centering one of the independent variablesis a popular alternative, in these models, the categorical, not continuous variables arecollinear which precludes centering as an option.

This model provides strong support to our hypotheses that minority and/or femalestatus coupled with group anxiety increases the likelihood of STEM attrition. Theresults indicate that the experience of stereotype threat among Black and White menand women, as well as Hispanic women significantly increase the likelihood of STEMattrition relative to Asian Men. Although we had not anticipated stereotype threatto have an impact on attrition from STEM among Whites men, the experience ofstereotype threat among Black and White men and women have a similar effect onthe log odds. Specifically, a 1 standard deviation increase in Black male and Blackfemale group based performance anxiety (b = 0.08, std = 7.43) (b = 0.09, std = 8.86)respectively produces, on average, a 0.59 (b = 0.08*7.43) and (0.09*8.86) increase inthe log odds of both Black men and Black women leaving STEM. Similarly a standarddeviation increase in group anxiety among White men (b = 0.11, std = 5.87) increasesthe log odds of attrition by 0.65 and by 0.61 and 0.57 for White and Hispanic womenrespectively. In contrast, general anxiety interactions had no significant impact on thelog odds of attrition for any group.

Contrary to our expectations, however, White men experiencing group based anx-iety were also more likely to leave STEM majors, while Hispanic men were not.Coupled with findings from Table 2 it is clear that while White men experience lessgroup-based performance anxiety than all other groups except White women, theirexperience of stereotype threat is positively associated with attrition.10

11 Discussion

This study examined the effects of stereotype threat on the attrition of minorities andwomen from science, technology, math and engineering majors. As Table 1 shows,for some women and minorities the primary issue is not a lack of interest in STEM.White, Asian and Hispanic women do indeed declare STEM majors at significantlylower rates than their male counterparts. However, the percent of Black and Hispanic

10 Please note: when White men were used as the control group instead of Asian men the results (notshown) were almost identical. The only major difference was that Asian male group anxiety was sig-nificantly negatively associated with attrition from STEM fields while White male group anxiety wassignificantly positively associated with attrition.

123


men who declare STEM majors upon college entrance is actually close in size to thatof White men, while Asian men declare STEM majors at a significantly higher ratethan all other groups. Likewise, Black women declare stem majors at rates not sig-nificantly different than those of Black men. Instead, the rate of attrition from STEMmajors within the first two years of college appears to be significantly higher amongAfrican-Americans, Hispanic women, and White women than it is among White menand Asian men. This helps to account for the significant disparity in the proportionsof Black, Hispanic female, and White female college graduates with STEM degreesrelative to White and Asian men.

Prior studies on attrition from STEM claim that a lack of preparation and low socio-economic status are the primary culprits in the dearth of minority and female scientistsand engineers. Descriptive statistics (not shown) reveal that African-Americans andHispanics who enter college intending to major in STEM do so with less prepara-tion (as measured by the number of AP courses taken and slightly lower GPAs) andlower socioeconomic backgrounds than do their Asian and White peers. Similarly,women who initially declare STEM majors enter with slightly less preparation thando their male counterparts. Yet the findings presented in Table 2 demonstrate that onlysome aspects of preparation play a key role in determining whether students chooseto major in STEM even when race and gender are taken into consideration. However,accounting for who stays in STEM from each race or gender is a separate issue whichrequires the addition of factors besides preparation and socioeconomic status. Ourstudy focused on whether stereotype threat is one such factor.

Although psychologists have examined the impact of stereotype threat on womenand minorities in short-term testing situations many times, few have explored howstereotype threat can impact these groups in long-term settings or decision-making.The present study adds to a small but growing body of research concerning the waysin which stereotype threat impacts decision-making in long-term circumstances. Carrand Steele (2010) for example, found that stereotype threat increased women’s aver-sion to risking taking in financial decisions. Similarly Alter et al. (2010) found thatstereotype threat impairs performance by stimulating avoidance behaviors such asnon-participation. Our results show that the experience of stereotype threat also elicitsdecisions by college students to stay or leave STEM fields.

Massey and Fischer (2005), whose research we build on, demonstrated thatperformance anxiety does hamper the academic performance of racial minorities. Weextend these findings to determine whether group based performance anxiety (stereo-type threat) plays a role in the low proportion of Black, Hispanic, and female scientistsand engineers and their high rates of attrition from these majors. Because Massey andFischer’s (2005) research was based on what they referred to as “felt performanceburden” a composite of both our group and general anxiety measures, however, wefirst investigated the relationship between race, gender, and group based performanceanxiety. Consistent with prior psychological studies, we found in Table 3 that Whitesand Asians experienced less stereotype threat than their Black and Hispanic coun-terparts. Contrary to prior findings, however, gender had no significant effect on theexperience of group anxiety. However, as we noted in our findings, while the experi-ence of stereotype threat may be stronger or weaker depending on race and/or gender,the effects of it are a separate issue.

123


The results in Table 4 primarily confirm our hypotheses concerning the impact ofstereotype threat among racial and/or gender groups on attrition from STEM majors.In particular, the experiences of stereotype threat among Black men and women as wellas White and Hispanic women have a significant influence on STEM attrition. Thisfinding provides strong evidence that stereotype threat takes place not only in testingsituations, but in ongoing activities. Thus stereotype threat not only negatively affectsthe test taking abilities of women and minorities, but it inhibits major life experiencesas well.

Also of major interest was our unanticipated finding that the experience of ste-reotype threat among Whites, particularly White males, has a positive effect on theirlikelihood of leaving STEM. That is, like women and minorities, White men experi-encing stereotype threat were more likely to drop out of STEM majors. As expected,Whites, especially White men, experienced a low level of stereotype threat. Yet ourresults indicate that those who do experience some degree of group based performanceanxiety suffered in the same ways as their minority and female counterparts. Given thelack of negative stereotypes regarding academia or STEM fields about White males,this is a difficult finding to interpret. We conjecture that the awareness of their dwin-dling numbers in college and STEM, coupled with the visible and perceived dominanceof Asian men in these fields, may cause insecurity among White males equivalent toa latent stereotype. Asians are indeed overrepresented in STEM fields. According torecent IPEDS data, STEM majors overall comprised 15 % of graduates in 2005–2006but over a quarter of Asians (26 %) graduated in that year from these fields of study(compared to 14 % of Whites).11

An important question to consider in applying the findings of these studies is: wouldour results be the same if we examined patterns among students at less selective schoolsthan the 28 which were sampled in the NLSF? Psychologists at universities with wideranges of selectivity have conducted lab experiments with similar and sometimes iden-tical findings to one another. This suggests that stereotype threat may function in thesame ways regardless of the level of selectivity of an institution. Owens and Massey(2011) have pointed to the virtue of using longitudinal surveys to study more long-lasting situations in which stereotype threat might occur. Analyses using survey dataare not meant to replace the exceptional experimental work conducted, but rather tocomplement it and provide longitudinal data unavailable for most experiments. Wecaution readers, however, that despite drawing on experimental research from a diver-sity of institutions to predict and interpret our findings, our sample was drawn from28 selective and highly selective tertiary institutions. As such, we believe our findingscan only be generalized to similarly selective schools.

11 Statistics based on number of bachelors degrees awarded by major by race/ethnicity and gender for2005–2006 as reported in Table 275 in the Condition of Education 2007 (http://nces.ed.gov/programs/digest/d07/tables/dt07_275.asp). Note: while 43, 38 and 39 % of Blacks, Hispanics, and women respec-tively who initially declared STEM majors left, only 34, 23 and 29 % respectively of Whites, Asians, andHispanics did so.

123

http://nces.ed.gov/programs/digest/d07/tables/dt07_275.asp

http://nces.ed.gov/programs/digest/d07/tables/dt07_275.asp


12 Conclusions

The lack of minorities and women in STEM professions and their related scarcity inSTEM college majors has been the source of much concern. This paper has found thatthe lack of graduating majors in these fields is not due solely to a lack of initial inter-est in STEM majors, but rather occurs through attrition from these majors during thecourse of college. We explored two explanations for this attrition—lack of academicpreparation and stereotype threat. We find that those who had stronger grades in highschool were in fact more likely to be early declarers of STEM majors, suggesting thatthose who came into college wanting to major in these fields were positively selectedin terms of academic preparation. We also show little evidence of an initial race gap inexpressing a desire to major in STEM fields at college entrance. The puzzle remainsthen, what happens after students enter college that steers them away from the STEMmajors they initially intended to pursue.

The primary explanation we explored in this paper was stereotype threat. Our mainmeasure of stereotype threat, which we termed group based performance anxiety, tapsthe extent to which students attribute their own performance as reflective of the aca-demic competence of their race and/or gender group. Black STEM majors had thehighest group based performance anxiety, followed by Hispanics and Asians. Whiteshad the lowest scores on this measure.

Net of other controls, we find that those who express higher levels of groupbased performance anxiety have significantly higher odds of leaving STEM majors.Regardless of scores on group based performance anxiety, male and female stu-dents from all racial/ethnic groups (with the exception of Hispanic men and Asianwomen) have higher odds of leaving STEM compared to Asian men. Women’s oddsof leaving STEM are higher than males net of other factors. Cumulatively, thismeans that non-Asian and female students with higher levels of group based per-formance anxiety are predicted to be at the greatest risk of attrition from STEMmajors. These findings suggest that stereotype threat is instrumental in under-mining the ambitions of minority and female students from majoring in STEMfields.

While most of the other research on stereotype threat has focused specifically onacademic performance, our study is unique in that we examine the role of stereotypethreat on students’ propensity to remain in what are often considered to be more chal-lenging majors. Although we are looking at a concrete action rather than performanceper se, our results are consistent with the findings from performance-based stud-ies. These performance-based studies have found that minorities and women tend tounderperform in tests when the test taking conditions invoke a negative group stereo-type about which test takers may be anxious about confirming. Similarly, we find thatHispanics, Blacks, and women from all groups disproportionately leave STEM majorsfor which their underrepresentation has at times been attributed to lack of competencein these fields.

There are several challenges that lie ahead for colleges and universities wishing toretain greater numbers of women and minorities in STEM majors. The initial interestof these groups in STEM majors is encouraging. More needs to be done, however, tounderstand the process by which students choose to leave these majors. Our findings

123


suggest that stereotype threat plays a role in their attrition. Fortunately other researchhas found that there are ways to reduce the negative effect of stereotype threat on out-comes for vulnerable groups, some of which may be applicable to the case of leavingSTEM majors.

One method to reduce stereotype threat is having more role models from vulnerablegroups. While minorities and women are underrepresented among STEM majors, theyare virtually absent among the faculty in these fields. Contrary to claims that the raceand gender of faculty have minimal influence on students’ interests (Cole and Barber2003), stronger efforts to recruit and retain minority and female scholars in sciencesand engineering would most certainly help with retraining vulnerable students in thesemajors. Even if teachers are not of the same race/ethnicity or gender as the student,there are mentoring techniques that can reduce the effects of stereotype threat. Cohenet al. (1999) find that students who received constructive criticism to communicatehigh standards while at the same time receiving assurances that they could meet thesestandards resulted in students feeling less that they would be judged based on ste-reotypes. Although it is evident that educators have yet to directly examine how todiminish stereotype threat, recognition of the role that stereotype threat plays in thedearth of minorities and women in science, math and engineering fields is a crucialfirst step in rectifying the problem.

References

Alberta, G. M., Castellanos, J., Lopez, A. G. L., & Rosales, R. (2005). An examination of aca-demic nonpersistence decisions of Latino undergraduates. Hispanic Journal of Behavioral Sci-ences, 27(2), 202–223.

Alter, A. L., Aronson, J., Darley, J. M., Rodriguez, C., & Ruble, D. N. (2010). Rising to the threat:Reducing stereotype threat by reframing the threat as a challenge. Journal of Experimental SocialPsychology, 46(1), 166–171.

Alva, S. A., & de Los Reyes, R. (1999). Psychosocial stress, internalized symptoms, and the academicachievement of Hispanic adolescents. Journal of Adolescent Research, 14(3), 343–358.

Aronson, J., Quinn, D. M., & Spencer, S. J. (1998). Stereotype threat and the academic underperformanceof minorities and women. In J. K. Swim, C. Stangor, & J. K. Swim (Eds.), Prejudice: The target’sperspective (pp. 83–103). San Diego, CA, USA: Academic Press.

Beckham, J. C., Carbonell, J. L., & Gustafson, D. J. (1988). Are there sex differences in problemsolving? An investigation of problem context and sex role type. Journal of Psychology, 122(1), 21.

Benbow, C. P., Lubinski, D., Shea, D. L., & Eftekhari-Sanjani, H. (2000). Sex differences in mathematicalreasoning ability at age 13: Their status 20 years later. Psychological Science, 11, 474–480.

Benbow, C. P., & Stanley, J. C. (1980). Sex differences in mathematical ability. Fact or artifact?.Science, 210, 1262–1264.

Blascovich, J., Spencer, S. J., Quinn, D. M., & Steele, C. M. (2001). African Americans and highblood pressure: The role of stereotype threat. Psychological Science, 12(3; 3), 225–229.

Brown, T. L. (2000). Gender differences in African American students’ satisfaction with college. Journalof College Student Development, 41(5), 479–487.

Campbell, J. R., & Beaudry, J. S. (1998). Gender gap linked to differential socialization for high-achievingsenior mathematics students. The Journal of Educational Research, 91(140), 140–147.

Carr, P. B., & Steele, C. M. (2010). Stereotype threat affects financial decision making. PsychologicalScience, 21(10), 1411–1416.

Charles, C. Z., Fischer, M. J., Mooney, M. A., & Massey, D. S. (2009). Taming the river: Negotiatingthe academic, financial, and social currents in selective colleges and universities. Princeton,NJ: Princeton University Press.

123


Chavous, T. M., Harris, A., Rivas, D., Helaire, L., & Green, L. (2004). Racial stereotypes and gender incontext: African Americans at predominantly black and predominantly white colleges. Sex Roles,51(1–2), 1–16. Retrieved from CSA Sociological Abstracts database.

Cheryan, S., & Bodenhausen, G. V. (2000). When positive stereotypes threaten intellectual performance:The psychological hazards of “model minority” status. Psychological Science, 11(5), 399–402.

Cohen, C. J., & Nee, C. E. (2000). Educational attainment and sex differentials in African Americancommunities. American Behavioral Scientist, 43(7), 1159–1206.

Cohen, G. L., Steele, C. M., & Ross, L. D. (1999). The mentor’s dilemma: Providing critical feedbackacross the racial divide. Personality and Social Psychology Bulletin, 25(10), 1302–1318.

Cohen, L. L., & Swim, J. K. (1995). The differential impact of gender ratios on women and men: Tokenism,self-confidence, and expectations. Personality and Social Psychology Bulletin, 21(9), 876–884.

Cole, S., & Barber, E. G. (2003). Increasing faculty diversity: The occupational choices of high-achievingminority students. Cambridge, Mass.: Harvard University Press.

Crocker, J., & Major, B. (1989). Social stigma and self esteem: The self-protective properties ofstigma. Psychological Review, 96(4), 608–630.

Darling-Hammond, L. (2004). The color line in American education: Race, resources, and studentachievement. Du Bois Review: Social Science Research on Race, 1(2), 213–246.

Eccles, J. S., Jacobs, J. E., & Harold, R. D. (1990). Gender role stereotypes, expectancy effects, andparents’ socialization of gender differences. Journal of Social Issues, 46, 183–201.

Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review ofPsychology, 53, 109–132.

Ehrmann, N. (2007). From the ghetto to the ivory tower: Gendered effects of segregation on elite-collegecompletion. Social Science Quarterly, 88(5), 1392–1414.

Elliott, R., Strenta, C., Adair, R., Matier, M., & Scott, J. (1996). The role of ethnicity in choosing andleaving science in highly selective institutions. Research in Higher Education, 37(6), 681–709.

Espiritu, Y. L. (1997). Asian American women and men: Labor, laws and love. Thousand Oaks, CA: SagePublications.

Fennema, E., & Sherman, J. (1977). Sex-related differences in mathematics achievement, spatialvisualization, and affective factors. American Education Journal, 14, 51–71.

Fischer, M. J., & Massey, D. S. (2007). The effects of affirmative action in higher education. SocialScience Research, 36(2), 531–549.

Geary, D. C. (1996). Sexual selection and sex differences in mathematical abilities. Behavioral andBrain Sciences, 19, 229–284.

Georgiou, S. N., Stavrinides, P., & Kalavana, T. (2007). Is victor better than victoria at maths?. EducationalPsychology in Practice, 23(4), 329–342.

Gupta, A., Szymanski, D. M., & Leong, F. T. L. (2011). The “model minority myth”: Internalizedracialism of positive stereotypes as correlates of psychological distress, and attitudes towardhelp-seeking. Asian American Journal of Psychology, 2(2), 101–114.

Hair, J. F., Black, B., Babin, B., Anderson, R. E., & Tatham, R. L. (1995). Multivariate data analysis(4th ed.). New Jersey: Prentice Hall.

Hedges, L. V., & Nowell, A. (1995). Sex differences in mental test scores, variability, and numbers ofhigh-scoring individuals. Science, 269, 41–45.

Herrnstein, R. J., & Murray, C. A. (1994). The bell curve: Intelligence and class structure in Americanlife. New York: Free Press.

Ho, C. C., & Jackson, J. W. (2001). Attitudes toward Asian Americans: Theory and measurement.Journal of Applied Social Psychology, 31, 1553–1581.

Holden, C. (1998). Boys + girls + math. Science, 279(5356), 1459.Hurtado, S., Carter, D. F., & Spuler, A. (1996). Latino student transition to college: Assessing difficulties

and factors in successful college adjustment. Research in Higher Education, 37(2), 135–157.Inzlicht, M., & Ben-Zeev, T. (2000). A threatening intellectual environment: Why females are suscepti-

ble to experiencing problem-solving deficits in the presence of males. Psychological Science, 11,365–371.

Kang, L. H. (1993). The desiring of Asian female bodies: Interracial romance and cinematic subjec-tion. Visual Anthropology Review, 9(1), 5–21.

Lederman, D. (June 17, 1992). Blacks make up large proportion of scholarship atheletes, yet their overallenrollment lags at division I colleges. Chronicle of Higher Education, 38, A1–A1, A30–A34.

123


Lin, M. H., Kwan, V. S. Y., Cheung, A., & Fiske, S. T. (2005). Stereotype content model explainsprejudice for an envied outgroup: Scale of anti-Asian American stereotypes. Personality and SocialPsychology Bulletin, 31(1), 34–47.

Major, B., & Schmader, T. (1998). Coping with stigma through psychological disengagement. In J. K.Swim, & C. Stangor (Eds.), Prejudice: The Target’s perspective (pp. 219–241)

Major, B., Spencer, S. J., Schmader, T., Wolfe, C., & Crocker, J. (1998). Coping with negative stereotypesabout intellectual performance: The role of psychological disengagement. Personality and SocialPsychology Bulletin, 24(1), 34–50.

Massey, D. S., & Fischer, M. J. (2005). Stereotype threat and academic performance: New findingsfrom a racially diverse sample of college freshmen. Du bois review: Social science research onrace, 2(1), 45–67. doi:10.1017/S1742058X05050058.

Massey, D. S., Charles, C. Z., Lundy, G. F., & Fischer, M. J. (2006). The source of the river: Thesocial origins of freshmen at America’s selective colleges and universities. Princeton, NJ: PrincetonUniversity Press.

National Science Foundation, Division of Science Resources Statistics. (2007). S&E degrees, by Race/Ethnicity of recipients: 1995–2004 No NSF 07-308. Arlington, VA: National Science Foundation.

Nussbaum, D. A., & Steele, C. M. (2007). Situational disengagement and persistence in the face ofadversity. Journal of Experimental Social Psychology, 43, 127–134.

Owens, J., & Massey, D. S. (2011). Stereotype threat and college academic performance: A latentvariables approach. Social Science Research, 40(1), 150–166.

Park, L. E., Cook, K. E., & Greenwald, A. G. (2001). Implicit indicators of women’s persistence inmath, science, and engineering Psi Chi Journal of Undergraduate Research, 6, 145-145-152.

Quinn, D. M., & Spencer, S. J. (2001). The interference of stereotype threat with women’s generationof mathematical problem-solving strategies. Journal of Social Issues, 57(1), 55–71.

Rinehart, J., & Watson, K. (1998). A campus climate survey at texas A&M university. Proceedingsof the 1998 women in engineering conference: Creating a global engineering community throughpartnerships, (93-100), West Lafayette, IN.

Rivas-Drake, D., & Mooney, M. (2008). Profiles of Latino adaptation at elite colleges and universi-ties. American Journal of Community Psychology, 42(1–2), 1–16.

Robinson, N. M., Abbott, R. D., Berninger, V. W., & Busse, J. (1996). The structure of abilitiesin mathematically precocious young children: Gender similarities and differences. Journal ofEducational Psychology, 88(341), 341–352.

Schmader, T., & Johns, M. (2003). Converging evidence that stereotype threat reduces working memorycapacity. Journal of Personality and Social Psychology, 85(3), 440–452.

Schmader, T., Johns, M., & Barquissau, M. (2004). The costs of accepting gender differences: Therole of stereotype endorsement in women’s experience in the math domain. Sex Roles, 50(11–12),835–850.

Schmader, T., Major, B., & Gramzow, R. H. (2001). Coping with ethnic stereotypes in the academic domain:Perceived injustice and psychological disengagement. The Journal of Social Issues, 57(1), 93–111.

Shih, M., Pittinsky, T. L., & Ambady, N. (1999). Stereotype susceptibility: Identity salience and shiftsin quantitative performance. Psychological Science, 10, 80–83.

Sinclair, S., Hardin, C. D., & Lowery, B. S. (2006). Self-stereotyping in the context of multiple socialidentities. Journal of Personality and Social Psychology, 90(4), 529–542.

Smedley, B. D., Myers, H. F., & Harrell, S. P. (1993). Minority-status stresses and the college adjustmentof ethnic minority freshmen. The Journal of Higher Education, 64(4), 434–452.

Spencer, S. J., Steele, C. M., & Quinn, D. M. (1999). Stereotype threat and women’s math performance.Journal of Experimental Social Psychology, 35, 4–28.

Stangor, C., & Sechrist, G. (1998). Conceptualizing the determinants of academic choice and taskperformance across social groups. In J. K. Swim, & C. Stangor (Eds.), Prejudice: The target’sperspective (pp. 105–124). San Diego, CA: Academic Press.

Steele, C. M. (1997). A threat in the air: How stereotypes shape intellectual identity and perfor-mance. American Psychologist, 52(6), 613–629.

Steele, C. M., & Aronson, J. (1995). Stereotype threat and the intellectual test performance of AfricanAmericans. Journal of Personality and Social Psychology, 69(5), 797–811.

Steele, J., James, J. B., & Barnett, R. C. (2002a). Learning in a Man’s world: Examining the perceptionsof undergraduate women in male-dominated academic areas. Psychology of Women Quarterly,26(1), 46–50.

123

http://dx.doi.org/10.1017/S1742058X05050058


Steele, C. M., Spencer, S. J., & Aronson, J. (2002b). Contending with group image: The psychologyof stereotype and social identity threat. In M. P. Zanna & M. P. Zanna (Eds.), Advances inexperimental social psychology, vol. 34 (pp. 379–440). San Diego, CA, USA: Academic Press.

Sue, S., Sue, D. W, Sue, L., & Takeuchi, D. T. (1995). Psychopathology among Asian Americans:A model minority? Cultural Diversity and Mental Health, 1, 39–51.

Sy, S. R., & Brittian, A. (2008). The impact of family obligations on young women’s decisions duringthe transition to college: A comparison of Latina, European American, and Asian Americanstudents. Sex Roles: A Journal of Research, 58(9–10), 729–737.

The success story of one minority group in the U.S., (December 26, 1966). U.S. News & World Report,73–76.

Torres, K. C., & Charles, C. Z. (2004). Metastereotypes and the black-white divide: A qualitative view ofrace on an elite college campus. Du Bois Review: Social Science Research on Race, 1(1), 115–149.

Updegraff, K. A., & Eccles, J. S. (1996). Course enrollment as self-regulatory behavior: Who takesoptional high school math courses?. Learning and Individual Differences, 8(3), 239–259.

Wheeler, S. C., & Petty, R. E. (2001). The effects of stereotype activation on behavior: A review ofpossible mechanisms. Psychological Bulletin, 127(6), 797–826.

Wong, P., Lai, C. F., Nagasawa, R., & Lin, T. (1998). Asian Americans as a model minority:Self-perceptions and perceptions by other racial groups. Sociological Perspectives, 41(1), 95–118.

Zia, Helen Asian American Dreams: The Emergence of an American People. (2001). Asian Americandreams: The emergence of an American people (1st ed.) Farrar, Straus and Giroux.

Author Biographies

Maya A. Beasley, Ph.D. is an Associate Professor in the Department of Sociology at the University ofConnecticut and serves on the Board of Advisors for the African American Studies Institute. Her first book,Opting Out: Losing the Potential of America’s Young Black Elite was published in 2011. She is currentlyworking on a second manuscript examining the impacts of the types of professions in which female andminority college graduates are most prevalent and least represented.

Mary J. Fischer, Ph.D. is an Associate Professor in the Department of Sociology at the University ofConnecticut. She has published widely on education and immigration. Among her numerous publications,Professor Fischer is a co-author of The Source of the River: The Social Origins of Freshmen at America’sSelective Colleges and Universities and Taming the River: Negotiating the Academic, Financial, and SocialCurrents in Selective Colleges and Universities.

123

why they leave: the impact of stereotype threat on the ... 2012.pdf · 430 m. a. beasley, m. j....

Documents