Bridging the Gender Gap: Examining Academic and Social Factors Influencing the Persistence of Women in Mathematics and Statistics

Authors

  • Faustina Baah University of Missouri-Columbia

DOI:

https://doi.org/10.63084/cognexus.v1i01.57

Keywords:

Mathematics, Statistics, Women in STEM, Academic support, Social belonging, Gender diversity

Abstract

Women remain underrepresented in mathematics and statistics despite efforts to increase gender diversity in STEM. This study shares initial results from a larger study that examines the academic and social factors influencing the persistence of undergraduate women in mathematics-intensive programs, with a particular focus on academic development and social support factors. Using a mixed-methods research design, survey responses from 24 undergraduate women and qualitative focus group discussions were analyzed to assess key retention factors. Findings from the survey responses indicate that participants in this study rated academic development factors such as coursework relevance and performance (91%) as well as the quality of instruction (70%) as more influential on persistence than social support structures, including peer interactions (38%) and faculty-student interaction (41%). The study highlights a critical research gap in understanding the long-term persistence of women beyond Calculus I. Recommendations include expanding faculty mentorship programs, integrating experiential learning opportunities, and implementing departmental policies to foster inclusive STEM environments. Future research should explore longitudinal studies, workforce transitions, and innovative pedagogical strategies to enhance retention. Addressing these challenges is crucial for creating gender-equitable STEM education and increasing the representation and persistence of women in mathematics and statistics-related careers.

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Published

2025-01-31

How to Cite

Faustina Baah. (2025). Bridging the Gender Gap: Examining Academic and Social Factors Influencing the Persistence of Women in Mathematics and Statistics . CogNexus, 1(01), 251–267. https://doi.org/10.63084/cognexus.v1i01.57

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