Stereotype and Women’s Math Performance 1
Running Head: STEREOTYPE AND WOMEN’S MATH PERFORMANCE
Stereotype Threat and its Effect on Women's Ability in Mathematics
Alexandra Feltes
The University of Akron
Stereotype and Women’s Math Performance 2
Abstract
In the last few decades, the roles of men and women in society have changed
dramatically. Despite this development, stereotypes pervade our culture and are capable of
having harmful effects. Specifically, when women perform mathematics, they risk being
negatively influenced by the stereotype that they have weaker abilities in this area. In this study,
an online mathematics test was given to two groups of female students at the University of
Akron to measure the effects of these beliefs. For one half of the participants, the directions of
test one were designed to reduce the current negative stereotype and put each participant at ease.
For the other half, test two directions explicitly stated that women were not expected to perform
well on the math test. The average scores from each were then compared using independent ttests to determine if this negative stereotype affects women when taking a mathematics exam.
The findings indicated no significant difference between the scores of group one and two,
indicating a possible reduction in the way this stereotype threat affects women.
Stereotype and Women’s Math Performance 3
Stereotype Threat and its Effect on Women's Ability in Mathematics.
Social psychologists investigate different aspects of human behavior and social factors that
influence individual thoughts, feelings, and actions. Of these, stereotypes and prejudices
frequently generate negative consequences for those who are the target of stereotypic or
prejudicial ideas. Research into these phenomena investigate the motivational origin of
prejudice, their effect on society’s perception and behavior, and examine processes through
which stereotypes are created (Spencer, Steele, & Quinn, 1999). Even though male and female
gender roles overlap, stereotypes have remained constant about traditional male and female
responsibilities (Davies, Spencer, Quinn, & Gerhardstein, 2010). Specifically, mathematics
continues to be a male-dominated area of study (Davies, Spencer, Quinn, & Gerhardstein).
According to Quinn and Spencer (2001), academic stereotypes are remarkably well-known
in this society. Following the current stereotypes, women are superior in the fields of reading and
English while men are superior in the fields of science and mathematics. Books, mass media, the
Internet, and teachers are only some of the various channels through which these stereotypes are
transmitted. Starting from an early age, society instructs children on the proper gender-based
careers they should pursue, eventually affecting how they are treated in academic settings and
what major they choose in college (Quinn & Spencer, 2001).
Mathematics questions frustrate everyone, from professors researching the most complex
problems to grade school children just learning basic calculations. Nevertheless, Davies et al.
(2010) state that an alarming disparity exists between male and female students when they
choose college majors. Among those men and women who possess equal skills and experience
in high school mathematics, only 19% of women chose college majors that involved a moderate
Stereotype and Women’s Math Performance 4
level of math, such as economics and architecture, while 43% of men chose majors in these same
disciplines (Lefevre, Kulak, & Heymans, 1992).
A psychological threat in which one feels that he/she will be viewed through a negative
stereotype is called a stereotype threat. It can impair performance in such a way that validates the
stereotype. Research that examines the adverse effects stereotype threats have on an individual’s
performance has been conducted on female students undergoing mathematical assessments,
students living in low socioeconomic circumstances undergoing testing for intellectual ability,
and African American students undergoing standardized testing (Pronin, Steele, & Ross, 2003).
Cadinu et al. (2005) propose that stereotypes negatively affect the performance of minority
groups by diverting their cognitions to task-irrelevant worries. Women taking a mathematics test
have more induced anxiety about confirming this stereotype, reducing their available cognitive
resources and consequently, leading to poorer performance (Cadinu, Maass, Rosabianca, &
Kiesner, 2005).
The purpose of this study is to determine whether the stereotype that women are not
proficient in mathematics will affect their performance on a mathematics test when explicitly
informed of this bias prior to attempting the exam. This research studies the effect, if any, this
stereotype has on women who are presented with a math test and after being notified beforehand
of the prejudice. The research design involves one math test that was given online through the
Human Participants Research (HPR) website to two separate groups of female undergraduate
students attending the University of Akron.
Stereotype and Women’s Math Performance 5
Method
Participants
Seventy-five female undergraduate students enrolled at the University of Akron
voluntarily participated in this research. Of those, each participant was randomly assigned to
either the neutral group or the stereotype group. The neutral group contained 39 students (i.e., 15
freshman, 6 sophomores, 11 juniors, and 7 seniors) while the stereotype group consisted of 36
students (i.e., 14 freshman 9 sophomores, 5 juniors, and 8 seniors). Since participation in this
research was open to any student registered in a psychology class, not all participants were
studying a major in psychology. The majority of participants in both the neutral and stereotype
group have taken one or two mathematics classes while in college (see Table 2).
Materials
Each test contained 27 multiple-choice questions. The survey was available through the
University of Akron’s online research website. Both the neutral and stereotype group received
the same exams. The test questions were broken down into four different sub-categories: base,
easy, moderate, and difficult (see Appendix A). The base questions acted as a filter for those
participants who blindly guessed through the majority of questions. Those participants who
answered two or more of these problems incorrectly were not taken into account when
statistically comparing the mean scores of each group.
Procedures
While the math tests were the same, each group was provided with a different set of
instructions prior to working through the math problems. The neutral group received directions
stating that the scores would not be evaluated based on performance, and that their responses
would help determine if the test is valid and the questions are of the appropriate difficulty. They
Stereotype and Women’s Math Performance 6
were instructed to attempt this test to the best of their ability in order to ensure that each
participant gives adequate effort to answer each question (see Appendix B). Then, upon
receiving the completed exams, each answer was scored for correctness. These neutral directions
were given with the goal of minimizing the stereotype threat a participant may have when taking
a mathematics test.
Instructions provided to the stereotype group were meant to raise the stereotype threat
concerning women in mathematics, in order to determine if the participants’ performances on the
test were affected. The scores for each group of participants were then compared to determine if
any statistical differences exists. These instructions were designed to implant the explicit
stereotype about women’s inferiority in math in order to study the effect this bias has on women.
After reading the prejudiced directions, I predicted that this group of women would produce
significantly lower scores than those who were given the stereotype-free instructions.
Each participant was asked to answer three manipulation questions after reading the
directions. This is to ensure that each student read and fully comprehended the instructions. For
those who did not answer one of these questions correctly, their answers were discounted. The
actual test questions remained the same for both groups to maintain consistency between the two
sets of participants.
Results
Participants’ responses for both the neutral and stereotype groups for all categories are
summarized in Table 1. Out of the seventy-five participants, thirty-nine were randomly selected
to receive the neutral directions while thirty-six received the prejudiced instructions. The total
number of incorrect responses were recorded for both the neutral (Mean = 12.97, SD = 4.75) and
the stereotype (Mean = 12.22, SD = 5.07) group, where the minimum and maximum number of
Stereotype and Women’s Math Performance 7
possible incorrect answers are zero and twenty-seven, respectively. The actual scores for both the
neutral group and stereotype ranged from one to twenty incorrect answers. The data suggests a
minimal difference between the average number wrong for the two sets of participants. A two
sample t-test indicated no statistically significant difference between the total number of
incorrect answers between those given the neutral directions and those given the stereotypical
instructions (t(73) = .663, p = .509).
For purposes of statistical analysis, the total number of questions was separated into four
sub-categories reflecting item difficulty (i.e., base, easy, medium, difficult). Beginning with the
base questions, participants had the opportunity of answering a maximum of three problems
incorrectly. In terms of items wrong, the neutral group (Mean = 0.231, SD = .485) and stereotype
group (Mean = 0.222, SD = .485) again revealed no numerical difference between both sets of
participants. No statistically significance difference exists for both groups between the number
of incorrect responses to the base level of difficulty (t(73) = .076, p = .939). Comparing the
results of the easy questions between the two groups revealed similar results to previous
analyses. With the possibility of six incorrect responses, the neutral group (Mean = 2.436, SD =
1.500) and stereotype group (Mean = 2.167, SD = 1.464) displayed no statistically significant
difference in this sub-category (t(73) = .785, p = .435).
With regard to the moderate sub-category, participants in the neutral (Mean = 6.436, SD
= 2.511) and stereotype (Mean = 6.139, SD = 2.769) groups had the opportunity of answering a
maximum of eleven problems incorrectly. Similar to previous results, the data indicates no
statistically significant difference for this sub-group of questions (t(73) = .487, p = .628). Along
with the moderate problems, participants in the neutral (Mean = 3.878, SD = 1.525) and
stereotype (Mean = 3.694, SD = 1.770) group showed little difference in the average number of
Stereotype and Women’s Math Performance 8
incorrect responses with regard to the difficult sub-category, regardless of which directions they
received. No statistically significant difference exists when analyzing this specific sub-category
(t(73) = .466, p = .643). The data indicates that for every category (i.e., total, base, easy,
moderate, and difficult incorrect) the group that received the neutral directions answered, on
average, a greater number of questions incorrectly than those that received the stereotype
instructions.
Discussion
Situations where women run the risk of being judged by a negative stereotype can yield a
disruptive state that interferes with their performance (Davies et al., 2010). In this case, I studied
whether priming the stereotype that females are not proficient in mathematics will produce a
state strong enough to increase the number of incorrect answers on a math exam. This did not
occur in this study.
Many plausible reasons exist as to why these women were not affected by this stereotype.
One of the simplest explanations is that there was not a sufficient number of participants to see a
significant difference between the scores of both groups. Wiley (1995) explains that small
sample sizes may be inadequate to support research hypotheses. Believing that numbers are
irrelevant in order to ensure accuracy and validity is a common misconception when performing
research. While seventy-five participants may be adequate to statistically analyze, it may not be
enough to get a true sampling of the population. Performing this experiment again using a larger
sample size could possibly yield a different result.
Since the answers to the exam depended on which directions they received, seeing no
significant difference in the scores may indicate that the instructions were not strong enough to
elicit a reaction from the participants. Having women read about a negative stereotype may not
Stereotype and Women’s Math Performance 9
have been as influential as listening to or visually witnessing that same stereotype. The women
that participated in this research were all undergraduate students who were probably more
interested in earning extra credit than understanding and considering the purpose of this
experiment. Thus, it is reasonable to believe that many participants simply glanced over the
instructions just enough to answer the manipulation questions correctly.
Oswald and Harvey (2000) conducted an experiment measuring this stereotype threat
where women were placed in a hostile environment prior to attempting a math exam. Participants
viewed a derogatory cartoon about their mathematical abilities and where then informed that
women perform worse than men on the test they were about to attempt. The interaction between
the hostile environment and the stereotype threat significantly affected the females’ performance
on the math exam (Oswald & Harvey, 2000). A stereotype threat may then have less influence
over the participants in non-threatening environments.
Explicitly stating that women are not meant to perform well on this math exam could
have possibly motivated most participants instead of discouraging their efforts. While many
participants may be aware of this stereotype, her personal beliefs may not be congruent with the
stereotype. Being explicitly told that one will perform poorly on a certain exam may serve to
motivate one’s efforts, focusing more on successfully accomplishing the task instead of why one
should not answer the questions accurately.
Whatever the reason, seeing no significant difference between the neutral and stereotype
group may indicate that the gender gap of women in mathematics has lessened and more women
are choosing careers in areas previously unattainable. The percentage of women who graduated
from medical schools increased significantly from 7.7% to 45.1% from 1964-2003 (Lambert &
Holmboe, 2003). Seeing more females with careers in math and science may inspire younger
Stereotype and Women’s Math Performance 10
generations of women to pursue those same professions. Niederle and Vesterlund (2009) indicate
that the mean scores for women on math exams are only slightly greater than for males.
Standardized tests such as the mathematics SAT, AP calculus tests, and the quantitative portions
of GREs continue to display a decrease in this gender gap (Niederle & Vesterlund, 2009).
It is evident that more research needs to be done, investigating the negative effects
stereotypes have on those targeted by prejudicial ideas. This complex problem not only affects
women, but those of different religions, races, and cultures as well. Understanding negative
stereotypes and improving upon them will reduce societal barriers increasing the chance of
minority group members’ success.
Stereotype and Women’s Math Performance 11
References
Cadinu, M., Maass, A., Rosabianca, A., & Kiesner, J. Why Do Women Underperform Under
Stereotype Threat? American Psychological Society, 16(7), 572-578.
Davies, P. G., Spencer, S. J., Quinn, D. M., & Gerhardstein, R. (2010). Consuming Images: How
Television Commercials that Elicit Stereotype Threat Can Restrain Women. Personality
and Social Psychology Bulletin, 28, 1615-1628.
Lambert, E.M. & Holmboe, E.S. (2005). The Relationship between Specialty Choice
and Gender of U.S. Medical Students. Academic Medicine, 80, 797-802.
LeFevre, J., Kulak, A.G. , & Heymans, S. L. (1992). Factors influencing the selection of
university majors varying in mathematical content.” Canadian Journal of Behavioral
Science, 24(3), Jul 1992, 276-289.
Pronin, E., Steele, C. M. , & Ross, L. (2003). Identity bifurcation in response to stereotype
threat: Women and mathematics. Journal of Experimental Social Psychology, 40(2), 152168.
Niederle, M. & Vesterlund, L. (2009). Explaining the Gender Gap in Math Test Scores:
The Role of Competition.
Oswald, D. & Harvey, R. (2000). Hostile Environments, Stereotype Threat, and Math
Performance among Undergraduate Women. Current Psychology: Developmental,
Learning, Personality, and Social, 19(4), 338-356.
Quinn, D.M. & Spencer, S.J. (2001). The Interference of Stereotype Threat With Women’s
Generation of Mathematical Problem-Solving Strategies. Journal of Social Issues, 57, 5571.
Stereotype and Women’s Math Performance 12
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.
Wiley, J.(1995). Sample size in qualitative research. Research in Nursing & Health, 18(2), 179183
Stereotype and Women’s Math Performance 13
Appendix A
Sample Questions of the Four Sub-categories
1. Base: Is 16 an even number?
2. Easy: Solve (6 + 3+ 12 ÷ 3) × 5 + 11 = _________
3. Moderate: Find an equivalent expression for
4. Difficult: Solve for x:
×
, where
Stereotype and Women’s Math Performance 14
Appendix B
Neutral Group Directions:
This math test is comprised of twenty-seven (27) questions ranging from fairly simple to
difficult. Please attempt each problem to the best of your ability. Men and women perform equally well
on these types of mathematical problems. However, these questions will not be graded and compared
to others’ scores. The purpose of this test is to determine which of these questions are of the
appropriate difficulty. You are allowed to use a calculator and any scratch paper you may need. The
extra credit will not be affected by how many problems you answer correctly.
Stereotype group directions:
This math test is comprised of twenty-seven (27) questions ranging from fairly simple to
difficult. Please attempt each problem to the best of you ability. According to Quinn and Spencer (2001),
there is a significant gender gap on mathematics tests. Parents, teachers, and the public media often
portray women as having less mathematical ability than men. Low expectations from these sources lead
women to achieve lower math test scores than men (Quinn & Spencer, 2001). In this study, the math
problems you are asked to solve will be used to evaluate why women are less proficient than men in
mathematics. In general, men perform better on the following test. Each question will be graded for
correctness and compared to others’ scores on the same test. You are allowed a calculator and any
other scratch paper you may need. The extra credit will not be affected by how many problems you
answer correctly.
Stereotype and Women’s Math Performance 15
Table 1: Statistical Analyses of the Research Data
Categories of Questions
Neutral
Mean (SD)
Stereotype
Mean (SD)
Total Wrong
12.974 (4.743)
12.222 (5.077)
Base Wrong
0.231 (0.485)
0.222 (0.485)
Easy Wrong
2.436 (1.500)
2.167 (1.464)
Moderate Wrong
6.436 (2.511)
6.134 (2.769)
Difficult Wrong
3.872 (1.525)
3.694 (1.770)
Note:
No statistically significant difference exists between groups in any category
Stereotype and Women’s Math Performance 16
Table 2: Number of College Mathematics Courses Taken
None
1-2
3-4
5 or more
Neutral Group
5
30
4
0
Stereotype Group
8
18
8
2