Is Math For All? Latent Profile Analysis of Gender Stereotypes and Self-Perceptions



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Background: Girls and women remain underrepresented in STEM fields. These gender gaps are in part due to negative gender stereotypes (shared perceptions of gender groups), such as the belief that boys are better than girls at math. These stereotypes can shape students’ self-perceptions, including their views of their own ability and interest toward a domain. In turn, self-perceptions can determine STEM choices and performance. As girls (but not boys) tend to be negatively stereotyped in STEM fields, girls may be demotivated to enter or persist in these fields. However, most research on STEM motivation is based on variable-centered analyses (e.g., regression) focusing on relations among variables. Thus, several important research questions which focus on individuals remain unaddressed. One key question is whether students can be arranged into groups, such that different groups have different patterns of self-perceptions and stereotypes. Purpose: This dissertation utilized a latent profile analysis to identify groups of students based on self-perceptions and stereotypes about boys’ and girls’ math attributes (ability and interest). A secondary purpose was to explore how STEM outcomes (math grades, STEM major intentions) and demographic predictors (socioeconomic status, racial/ethnic minority, educational level) were associated with profile membership. Methods: Three datasets collected through online surveys between 2019 and 2021 were used. Sample sizes were 999 (500 girls; Grades 6-12), 1,267 (669 girls; Grades 6-12), and 865 (469 girls; Grades 7-10) diverse students in the U.S. Results: Across datasets and genders, five profiles emerged, representing beliefs that math is For All, For Me, For Few, For Others, and For Some. The results revealed that profile membership was related to STEM outcomes and students’ demographics. Students in the For All and For Me profiles typically had higher math grades and STEM intentions than those in other profiles. There was some evidence showing that students with low socioeconomic status, minority status, or high school status were overrepresented in the For Few profile (versus For All). Conclusion: The findings advance the understanding of how self and group perceptions may cohere and which combinations of these beliefs may be most positive and most negative. This dissertation suggests that motivational interventions should promote the belief that all students can be successful and enjoy math.



Self-perceptions, Gender stereotypes, Situated expectancy-value theory, Balanced identity theory