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19 pages, 363 KiB  
Article
The Impact of Math-Gender Stereotypes on Students’ Academic Performance: Evidence from China
by Yilei Luo and Xinqi Chen
J. Intell. 2024, 12(8), 75; https://doi.org/10.3390/jintelligence12080075 - 1 Aug 2024
Viewed by 788
Abstract
This study investigates the impact of math-gender stereotypes on students’ academic performance using data from the China Education Panel Survey (CEPS), which surveyed nationally representative middle schools in China. Our sample comprises over 2000 seventh-grade students, with an average age of 13 and [...] Read more.
This study investigates the impact of math-gender stereotypes on students’ academic performance using data from the China Education Panel Survey (CEPS), which surveyed nationally representative middle schools in China. Our sample comprises over 2000 seventh-grade students, with an average age of 13 and a standard deviation of 0.711. Among these students, 52.4% are male, and 47.6% are female. Employing a fixed effects model and instrumental variable, our findings are as follows. First, over half of the male students believe that boys are better at math than girls, and they also perceive that their parents and society hold the same belief. In contrast, fewer than half of the female students hold this belief or perception. Intriguingly, among these students, female math performance surpasses that of males. Second, stereotypes hinder female math performance, especially among low-achieving ones, while benefiting high-achieving male students. Finally, perceptions of societal stereotypes have the greatest effect on math performance, followed by self-stereotypes and perceptions of parental stereotypes. Understanding the implications of these findings highlights the importance of addressing math-gender stereotypes to promote equal participation and success for both genders in STEM fields. Full article
25 pages, 885 KiB  
Article
Perceptions of Skills Needed for STEM Jobs: Links to Academic Self-Concepts, Job Interests, Job Gender Stereotypes, and Spatial Ability in Young Adults
by Margaret L. Signorella and Lynn S. Liben
J. Intell. 2024, 12(7), 63; https://doi.org/10.3390/jintelligence12070063 - 27 Jun 2024
Viewed by 908
Abstract
Gender gaps in spatial skills—a domain relevant to STEM jobs—have been hypothesized to contribute to women’s underrepresentation in STEM fields. To study emerging adults’ beliefs about skill sets and jobs, we asked college students (N = 300) about the relevance of spatial, [...] Read more.
Gender gaps in spatial skills—a domain relevant to STEM jobs—have been hypothesized to contribute to women’s underrepresentation in STEM fields. To study emerging adults’ beliefs about skill sets and jobs, we asked college students (N = 300) about the relevance of spatial, mathematical, science and verbal skills for each of 82 jobs. Analyses of responses revealed four job clusters—quantitative, basic & applied science, spatial, and verbal. Students’ ratings of individual jobs and job clusters were similar to judgments of professional job analysts (O*NET). Both groups connected STEM jobs to science, math, and spatial skills. To investigate whether students’ interests in STEM and other jobs are related to their own self-concepts, beliefs about jobs, and spatial performance, we asked students in another sample (N = 292) to rate their self-concepts in various academic domains, rate personal interest in each of the 82 jobs, judge cultural gender stereotypes of those jobs, and complete a spatial task. Consistent with prior research, jobs judged to draw on math, science, or spatial skills were rated as more strongly culturally stereotyped for men than women; jobs judged to draw on verbal skills were more strongly culturally stereotyped for women than men. Structural equation modeling showed that for both women and men, spatial task scores directly (and indirectly through spatial self-concept) related to greater interest in the job cluster closest to the one O*NET labeled “STEM”. Findings suggest that pre-college interventions that improve spatial skills might be effective for increasing spatial self-concepts and the pursuit of STEM careers among students from traditionally under-represented groups, including women. Full article
(This article belongs to the Special Issue Spatial Intelligence and Learning)
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<p>Structural equation model predicting interest in basic &amp; applied science cluster jobs. (* <span class="html-italic">p</span> &lt; .05; ** <span class="html-italic">p</span> &lt; .01).</p>
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<p>Structural equation model predicting interest in quantitative cluster jobs. (* <span class="html-italic">p</span> &lt; .05; ** <span class="html-italic">p</span> &lt; .01).</p>
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15 pages, 838 KiB  
Article
A Gender Bias in Curriculum-Based Measurement across Content Domains: Insights from a German Study
by Florian Klapproth and Holger von der Lippe
Educ. Sci. 2024, 14(1), 76; https://doi.org/10.3390/educsci14010076 - 9 Jan 2024
Viewed by 1298
Abstract
By immediately responding to achievement progress data, teachers can improve students’ performance by using curriculum-based measurement. However, there are studies showing that teachers are prone to make biased judgments about the students providing the data. The present investigation experimentally examined whether pre-service teachers [...] Read more.
By immediately responding to achievement progress data, teachers can improve students’ performance by using curriculum-based measurement. However, there are studies showing that teachers are prone to make biased judgments about the students providing the data. The present investigation experimentally examined whether pre-service teachers in Germany were biased by the use of gender stereotypes when judging students’ achievement derived from progress data. N = 100 pre-service teachers received graphs that depicted the development of either oral reading fluency or math achievement of girls and boys over a time interval of 11 weeks. The results obtained confirmed the hypotheses partially. The participants did not favor girls over boys on average. However, they judged achievement in reading to be higher for girls than for boys, and math achievement to be higher for boys than for girls. The results suggest that gender stereotypes (boys are good at math, girls are good at reading) are still prevalent in pre-service teachers. Full article
(This article belongs to the Section Education and Psychology)
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<p>Experimental vignettes of boys of the reading condition. <span class="html-italic">Note</span>. Upper panel: Steep linear trend of the data; lower panel: flat linear trend of the data; left panel: high variability of the data; right panel: low variability of the data. The names of the students were shown on the vignettes to indicate the gender of the student. The meaning of the three different lines (solid: goal line; dotted: trend line; solid with data points: student progress data) was explained to the participants. The original labeling of the axes was in German.</p>
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20 pages, 337 KiB  
Article
Measuring Implicit STEM and Math Attitudes in Adolescents Online with the Brief Implicit Association Test
by Regina Reichardt, Celina Rottmann, Laura Russo, Kathrin J. Emmerdinger and Sigrun Schirner
Educ. Sci. 2023, 13(9), 899; https://doi.org/10.3390/educsci13090899 - 6 Sep 2023
Cited by 1 | Viewed by 1501
Abstract
Despite societal efforts toward enhancing gender equality, females are still underrepresented in STEM (science, technology, engineering, mathematics). Prominent explanations draw on gender differences in attitudes about STEM (with females holding more negative attitudes than males), which result from the gender stereotype that STEM [...] Read more.
Despite societal efforts toward enhancing gender equality, females are still underrepresented in STEM (science, technology, engineering, mathematics). Prominent explanations draw on gender differences in attitudes about STEM (with females holding more negative attitudes than males), which result from the gender stereotype that STEM is a male domain. While a lot of research has focused on explicit attitudes, little is known about implicit attitudes toward STEM. The present research sought to examine implicit attitudes among adolescents, and how they relate to other STEM cognitions. We measured implicit attitudes about the STEM concept as a whole, and about math in particular. For this purpose, we developed two Brief Implicit Associations Tests (BIATs) and administered them online in a sample of adolescents (N = 517). We additionally measured a variety of self-reported motivational and social-psychological variables (interest, aspiration, self-concept of ability, and sense of belonging to the math and STEM community, respectively), which previous research has identified as factors contributing to the gender gap in STEM participation. Our findings confirm the reliability and validity of both the STEM BIAT and the Math BIAT. Moreover, implicit STEM attitudes predicted interest in and aspiration for STEM, self-concept of STEM ability, and sense of belonging to the STEM community. Similarly, implicit math attitudes predicted interest in and aspiration for math, and sense of belonging to the math community (but not self-concept of math ability). Our findings confirm that our novel online BIATs are efficient measurement tools of implicit attitudes in adolescents. Moreover, our findings underscore the significance of implicit attitudes in the STEM domain. Full article
(This article belongs to the Special Issue Sticking with STEM: Who Comes, Who Stays, Who Goes, and Why?)
25 pages, 1505 KiB  
Article
“Who’s Better at Math, Boys or Girls?”: Changes in Adolescents’ Math Gender Stereotypes and Their Motivational Beliefs from Early to Late Adolescence
by Christine R. Starr, Yannan Gao, Charlott Rubach, Glona Lee, Nayssan Safavian, Anna-Lena Dicke, Jacquelynne S. Eccles and Sandra D. Simpkins
Educ. Sci. 2023, 13(9), 866; https://doi.org/10.3390/educsci13090866 - 25 Aug 2023
Cited by 3 | Viewed by 2162
Abstract
Though adults tend to endorse the stereotype that boys are better than girls in math, children tend to favor their own gender or be gender egalitarian. When do individuals start endorsing the traditional stereotype that boys are better? Using two longitudinal U.S. datasets [...] Read more.
Though adults tend to endorse the stereotype that boys are better than girls in math, children tend to favor their own gender or be gender egalitarian. When do individuals start endorsing the traditional stereotype that boys are better? Using two longitudinal U.S. datasets that span 1993 to 2011, we examined three questions: (1) What are the developmental changes in adolescents’ gender stereotypes about math abilities from early to late adolescence? (2) Do the developmental changes vary based on gender and race/ethnicity? (3) Are adolescents’ stereotypes related to their math motivational beliefs? Finally, (4) do these patterns replicate across two datasets that vary in historical time? Adolescents in grades 8/9 and 11 were asked whether girls or boys are better at math (n’s = 1186 and 23,340, 49–53% girls, 30–54% White, 13–60% Black, 1–22% Latinx, and 2% to 4% Asian). Early adolescents were more likely to be gender egalitarian or favor their own gender. By late adolescence, adolescents’ stereotypes typically shifted towards the traditional stereotype that boys are better. In terms of race/ethnicity, White and Asian adolescents significantly favored boys, whereas Black and Latinx adolescents were more likely to endorse gender egalitarian beliefs. Adolescents’ stereotypes were significantly related to their expectancy beliefs, negatively for girls and positively for boys. Full article
(This article belongs to the Special Issue Sticking with STEM: Who Comes, Who Stays, Who Goes, and Why?)
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<p>Adolescents’ math gender stereotypes: effect sizes (Cohen’s d) by grade and gender. Effect sizes to the left indicate bias towards girls/females, and effect sizes to the right indicate bias towards boys/males. HSLS SOURCE: U.S. Department of Education, Institute of Education Sciences, National Center for Education Statistics, High School Longitudinal Study of 2009 (HSLS:09), Base Year and First Year Follow-Up.</p>
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<p>(<b>a</b>) Boys’ math gender stereotypes frequencies. (<b>b</b>) Girls’ math gender stereotypes frequencies. Frequency of answers to the question “Who’s better at math?” by gender and grade. HSLS SOURCE: U.S. Department of Education, Institute of Education Sciences, National Center for Education Statistics, High School Longitudinal Study of 2009 (HSLS:09), Base Year and First Year Follow-Up.</p>
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<p>(<b>a</b>) Black adolescents’ math gender stereotypes: effect sizes by grade and gender. (<b>b</b>) White adolescents’ math gender stereotypes: effect sizes by grade and gender. (<b>c</b>) Asian adolescents’ math gender stereotypes: effect sizes by grade and gender. (<b>d</b>) Latinx adolescents’ math gender stereotypes: effect sizes by grade and gender.</p>
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<p>(<b>a</b>) Black adolescents’ math gender stereotypes: effect sizes by grade and gender. (<b>b</b>) White adolescents’ math gender stereotypes: effect sizes by grade and gender. (<b>c</b>) Asian adolescents’ math gender stereotypes: effect sizes by grade and gender. (<b>d</b>) Latinx adolescents’ math gender stereotypes: effect sizes by grade and gender.</p>
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24 pages, 2230 KiB  
Article
Toward Gender Equality in Education—Teachers’ Beliefs about Gender and Math
by Jana Lindner, Elena Makarova, Deborah Bernhard and Dorothee Brovelli
Educ. Sci. 2022, 12(6), 373; https://doi.org/10.3390/educsci12060373 - 26 May 2022
Cited by 8 | Viewed by 7630
Abstract
Math has a strong gender-related image, even among teachers. As teachers hold beliefs about their work, their role, their subject, and their students, they shape girls’ and boys’ mathematical beliefs and attitudes. Research during the past 20 years has shown that teachers’ gender [...] Read more.
Math has a strong gender-related image, even among teachers. As teachers hold beliefs about their work, their role, their subject, and their students, they shape girls’ and boys’ mathematical beliefs and attitudes. Research during the past 20 years has shown that teachers’ gender beliefs about mathematics significantly favor boys, thereby reinforcing girls’ low math ability self-concept. Still, there is a lack of studies that examine teachers’ gender-related beliefs based on their underlying assumptions. Our study provides the first empirical evidence of the relationship between general gender stereotypes and math stereotypes. To this end, we used partial correlation and MANCOVA to analyze data from an online survey in 2019/2020 conducted in Switzerland (195 women, 80 men) as part of a cross-cultural comparison study. We therefore created a differentiated profile of prospective teachers by examining their beliefs about their self-image, their image of men and women in society, their essentialist and gender role ideology beliefs, and their math stereotypes. Then, we linked prospective teachers’ beliefs about gender (based on 48 characteristics) to their beliefs about mathematics and about girls’ and boys’ competencies in math. The extensive analysis provides knowledge about prospective teachers and is particularly important for teacher education. Full article
(This article belongs to the Special Issue Mathematics Education and Implications to Educational Psychology)
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<p>Prospective teachers’ beliefs about communal gender stereotypes for women in society (1.00 = not at all desirable, 7.00 = very desirable).</p>
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<p>Prospective teachers’ beliefs about communal gender stereotypes for men in society (1.00 = not at all desirable, 7.00 = very desirable).</p>
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<p>Prospective teachers’ beliefs about weak gender stereotypes for women in society (1.00 = not at all desirable, 7.00 = very desirable).</p>
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<p>Prospective teachers’ beliefs about weak gender stereotypes for men in society (1.00 = not at all desirable, 7.00 = very desirable).</p>
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<p>Prospective teachers’ beliefs about dominant gender stereotypes for women in society (1.00 = not at all desirable, 7.00 = very desirable).</p>
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<p>Prospective teachers’ beliefs about dominant gender stereotypes for men in society (1.00 = not at all desirable, 7.00 = very desirable).</p>
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<p>Prospective teachers’ beliefs about agentic gender stereotypes for women in society (1.00 = not at all desirable, 7.00 = very desirable).</p>
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<p>Prospective teachers’ beliefs about agentic gender stereotypes for men in society (1.00 = not at all desirable, 7.00 = very desirable).</p>
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29 pages, 28725 KiB  
Article
The Place of Gender Stereotypes in the Network of Cognitive Abilities, Self-Perceived Ability and Intrinsic Value of School in School Children Depending on Sex and Preferences in STEM
by Victoria Ismatullina, Timofey Adamovich, Ilya Zakharov, Georgy Vasin and Ivan Voronin
Behav. Sci. 2022, 12(3), 75; https://doi.org/10.3390/bs12030075 - 10 Mar 2022
Cited by 4 | Viewed by 3502
Abstract
Adolescents face many barriers on the path towards a STEM profession, especially girls. We examine the gender stereotypes, cognitive abilities, self-perceived ability and intrinsic values of 546 Russian school children from 12 to 17 years old by sex and STEM preferences. In our [...] Read more.
Adolescents face many barriers on the path towards a STEM profession, especially girls. We examine the gender stereotypes, cognitive abilities, self-perceived ability and intrinsic values of 546 Russian school children from 12 to 17 years old by sex and STEM preferences. In our sample, STEM students compared to no-STEM have higher cognitive abilities, intrinsic motivation towards math and science, are more confident in their math abilities and perceive math as being easier. Boys scored higher in science, math and overall academic self-efficacy, intrinsic learning motivation and math’s importance for future careers. Meanwhile, girls displayed higher levels of gender stereotypes related to STEM and lower self-efficacy in math. A network analysis was conducted to identify the structure of psychological traits and the position of the stem-related stereotypes among them. The analysis arrived at substantially different results when adolescents were grouped by sex or preference towards STEM. It also demonstrated that gender stereotypes are connected with cognitive abilities, with a stronger link in the no-STEM group. Such stereotypes play a more important role for girls than boys and, jointly with the general self-efficacy of cognitive and academic abilities, are associated with the factors that distinguish groups of adolescents in their future careers. Full article
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<p>Group values of spatial abilities (<b>a</b>) and Raven score (<b>b</b>) in STEM and No-STEM groups.</p>
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<p>Group values for intrinsic motivation in math (<b>a</b>), ability self-perception in math (<b>b</b>), intrinsic motivation in science (<b>c</b>) and ability self-perception in science (<b>d</b>).</p>
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<p>Post hoc analysis of ability self-perception in math (<b>a</b>), science (<b>b</b>) and in total (<b>c</b>) by sex and STEM/No-STEM groups.</p>
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<p>Group values in perceived difficulty in math in STEM and No-STEM groups.</p>
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<p>Group values in friends’ attitude towards math in STEM and No-STEM groups.</p>
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<p>Estimated network (<b>a</b>) and corresponding MST (<b>b</b>) for the STEM group. Thicker lines between variables indicates stronger connection; different colors indicate membership of variables to a specific cluster. Two-color nodes belong to two clusters simultaneously. Three clusters emerge in the network: (1) NI—Non-verbal intelligence, SA—Spatial ability, SGS—STEM-related gender stereotypes; (2) SA—Spatial ability, ASPT—Ability self-perceptions, IMT—Intrinsic motivation; (3) ASPT—Ability self-perceptions, IMT—Intrinsic motivation, ASPM—Ability self-perceptions in math, EAM—Educational aspirations in math, IMM—Intrinsic Motivation for math, FAM—Friends’ attitudes towards math, PDM—Perceived difficulty of math. Non-clustered: ASPT—Ability self-perceptions.</p>
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<p>Estimated network (<b>a</b>) and corresponding MST (<b>b</b>) for the No-STEM group. Thicker lines between variables indicates stronger connection; different colors indicate membership of variables to a specific cluster. Two-color nodes belong to two clusters simultaneously. Three clusters emerge in the network: (1) NI—Non-verbal intelligence, SA—Spatial ability, SGS—STEM-related gender stereotypes, PDM—Perceived difficulty of math; (2) SGS—STEM-related gender stereotypes, ASPS—Ability self-perceptions in science; IMS—Intrinsic Motivation for science; (3) PDM—Perceived difficulty of math, EAM—Educational aspirations in math, IMM—Intrinsic Motivation for math, FAM—Friends’ attitudes towards math, ASPM—Ability self-perceptions in math, IMT—Intrinsic motivation. Non-clustered: ASPS—Ability self-perceptions in science; IMS—Intrinsic Motivation for science.</p>
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<p>Estimated network (<b>a</b>) and corresponding MST (<b>b</b>) for the females. Thicker lines between variables indicate stronger connection; different colors indicate membership of variables to a specific cluster. Two-color nodes belong to two clusters simultaneously. Two clusters emerge in the network: (1) SA—Spatial ability, FAM—Friends’ attitudes towards math, IMS—Intrinsic Motivation for science, ASPS—Ability self-perceptions in science, ASPT—Ability self-perceptions, ASPM—Ability self-perceptions in math, IMT—Intrinsic motivation; (2) IMT—Intrinsic motivation, ASPM—Ability self-perceptions in math, IMM—Intrinsic Motivation for math, PDM—Perceived difficulty of math, EAM—Educational aspirations in math. Non-clustered: NI—Non-verbal intelligence, SGS—STEM-related gender stereotypes.</p>
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<p>Estimated network (<b>a</b>) and corresponding MST (<b>b</b>) for the males. Thicker lines between variables indicate stronger connection; different colors indicate membership of variables to a specific cluster. Two-color nodes belong to two clusters simultaneously. Three clusters emerge in the network: (1) IMM—Intrinsic Motivation for math, PDM—Perceived difficulty of math, EAM—Educational aspirations in math, IMT—Intrinsic motivation, ASPT—Ability self-perceptions, ASPM—Ability self-perceptions in math, SA- Spatial ability; NI—Non-verbal intelligence, SGS—STEM-related gender stereotypes; (2) SA—Spatial ability; NI—Non-verbal intelligence, SGS—STEM-related gender stereotypes; (3) FAM—Friends’ attitudes towards math, IMT—Intrinsic motivation; IMM—Intrinsic Motivation for math. Non-clustered: ASPS—Ability self-perceptions in science; IMS—Intrinsic Motivation for science.</p>
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<p>Example of the tasks Raven’s Standard Progressive Matrices (<b>a</b>) series A and (<b>b</b>) series F.</p>
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<p>Example of tasks of “Paper folding” Test.</p>
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<p>Example of tasks of “Shape rotation” Test.</p>
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<p>Example of tasks of “Pattern assembly” Test.</p>
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8 pages, 708 KiB  
Article
Cubes or Pellets in Mental-Rotation Tests: Effects on Gender Differences and on the Performance in a Subsequent Math Test
by Martina Rahe and Claudia Quaiser-Pohl
Behav. Sci. 2020, 10(1), 12; https://doi.org/10.3390/bs10010012 - 23 Dec 2019
Cited by 7 | Viewed by 5165
Abstract
In mental rotation, males consistently outperform females in performance and confidence. Both can affect math anxiety. In the present study, 107 undergraduate students (85 female) solved a mental-rotation test either with cube (C-MRT) or pellet (P-MRT) figures as stimulus material, then reported their [...] Read more.
In mental rotation, males consistently outperform females in performance and confidence. Both can affect math anxiety. In the present study, 107 undergraduate students (85 female) solved a mental-rotation test either with cube (C-MRT) or pellet (P-MRT) figures as stimulus material, then reported their confidence in their ability in the test, and solved a math test. Males performed better than females in both test versions: In the C-MRT, with a large effect, and in the P-MRT, with a small effect, and reported higher scores in their confidence. In math test performance, males scored higher than females when they solved the math test after the C-MRT but not after the P-MRT. The interactions of gender and stimulus material were not significant. Correlations between confidence and math test performance were large for males and not significant for females. Stereotype threat and lift effects are discussed as possible reasons for the varying effects of the stimulus material on the MRT performance of male and female participants. Full article
(This article belongs to the Special Issue XVI European Congress of Psychology)
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<p>Example items (C-MRT in the upper row and P-MRT in the lower row).</p>
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<p>Mental-rotation score as a function of rotational objects and participants’ gender. Error bars indicate SE.</p>
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<p>Math-test performance as a function of rotational objects of the previously solved MRT and participants’ gender. Error bars indicate SE.</p>
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9 pages, 232 KiB  
Article
The Myth That Only Brilliant People Are Good at Math and Its Implications for Diversity
by Eleanor K. Chestnut, Ryan F. Lei, Sarah-Jane Leslie and Andrei Cimpian
Educ. Sci. 2018, 8(2), 65; https://doi.org/10.3390/educsci8020065 - 4 May 2018
Cited by 37 | Viewed by 23802
Abstract
A common misconception about math is that it requires raw intellectual talent or “brilliance.” Only students who possess this sort of brilliance are assumed to be capable of success in math-related subjects. This harmful myth has far-reaching consequences for the success of girls [...] Read more.
A common misconception about math is that it requires raw intellectual talent or “brilliance.” Only students who possess this sort of brilliance are assumed to be capable of success in math-related subjects. This harmful myth has far-reaching consequences for the success of girls and children from ethnic-minority backgrounds in these subjects. Because women and minorities are stereotyped as lacking brilliance, the myth that success in math requires this trait is a barrier that students from these groups have to overcome. In the first part of this paper, we detail the pervasiveness of this myth and explore its relation to gender and race gaps in math and beyond. In the second part, we highlight some potential sources of this myth in children’s everyday experiences and offer some strategies for debunking it. Full article
(This article belongs to the Special Issue Dispelling Myths about Mathematics)
21 pages, 2022 KiB  
Article
Negative Gender Ideologies and Gender-Science Stereotypes Are More Pervasive in Male-Dominated Academic Disciplines
by Sarah Banchefsky and Bernadette Park
Soc. Sci. 2018, 7(2), 27; https://doi.org/10.3390/socsci7020027 - 11 Feb 2018
Cited by 47 | Viewed by 14739
Abstract
Male-dominated work environments often possess masculine cultures that are unwelcoming to women. The present work investigated whether male-dominated academic environments were characterized by gender ideologies with negative implications for women. A survey of 2622 undergraduates across a variety of academic majors examined how [...] Read more.
Male-dominated work environments often possess masculine cultures that are unwelcoming to women. The present work investigated whether male-dominated academic environments were characterized by gender ideologies with negative implications for women. A survey of 2622 undergraduates across a variety of academic majors examined how gender imbalance within the major corresponded with students’ gender ideologies. We hypothesized that men in male-dominated domains might justify their dominance and prototypical status by adopting gender ideologies and stereotypes that denigrate women and treat men as the normative and superior group. Confirming this hypothesis, men in increasingly male-dominated academic majors were more likely to endorse Assimilationism—that women should adapt and conform to masculine work norms in order to succeed—and Segregationism—that men and women should pursue traditional social roles and careers. Moreover, they were less likely to endorse Gender Blindness—that attention to gender should be minimized. They were also more likely to agree with the gender-science stereotype that men do better in math and science than women. In contrast, gender imbalance in the major did not influence women’s gender ideologies, and women in increasingly male-dominated majors were significantly less likely to endorse the gender-science stereotype. Full article
(This article belongs to the Special Issue Women in Male-Dominated Domains)
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<p>Endorsement of the gender ideologies by gender. Each dot represents a data point. <span class="html-italic">n</span> for women was 1610, <span class="html-italic">n</span> for men was 1012. Triangles represent the average endorsement of each ideology for men and women.</p>
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<p>Gender representation in common academic majors within the sample (i.e., that is, majors declared by at least one percent of participants in the sample (<span class="html-italic">n</span> = 26).</p>
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<p>A path analysis of the relationship between percent men in the major and gender-science stereotypes for women and men. Although not depicted for simplicity, covariates included semester collected and academic year; moreover, ideologies were allowed to correlate with one another. Unstandardized regression coefficients are provided outside of parentheses; standardized regression coefficients are provided in parentheses. Asterisks indicate significance of relationships (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001). The relationship between percent men in the major and gender-science stereotype endorsement was significantly different for women and men; all other paths were not significantly different.</p>
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<p>The relationship between percent men in the major and gender-science stereotype, by gender. Regression lines represent partial relationships controlling for academic year and semester of data collection. For men, gender-science stereotypes increased as percent men in the major increased. For women, gender-science stereotypes decreased as percent men increased.</p>
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