2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Pathways into Statistics and Data Science for Academically Talented Undergraduate Students with Low Incomes

Presented at Track 2: Technical Session 1: Pathways into Statistics and Data Science for Low-Income, Academically Talented Undergraduate Students

Statistics and data science (SDS) is a rapidly growing field, yet this growth is disparate, with individuals holding marginalized identities underrepresented. The developing nature of SDS poses an opportunity to broaden representation and bolster equity via student recruitment and to do so relatively early in the life of the field. In this paper, we investigate how and why a group of academically talented college students with low incomes came to major or minor in SDS. Qualitative coding of student interviews revealed they mostly came to SDS indirectly, were drawn to SDS at least in part by its applied nature, and are unanimously enthusiastic about SDS. These insights into students’ experiences with SDS can inform future recruitment efforts aimed at creating a more equitable field.

Authors

Dr. Erin Carll University of Washington [biography]

Erin Carll is the associate director at the University of Washington Center for Evaluation and Research for STEM Equity (CERSE). Her evaluation and research focus on efforts to expand equity and inclusion in the STEM fields, including through community building and leveraging existing assets. She currently serves on the Women in Engineering ProActive Network (WEPAN) Board of Directors and the Society for Women Engineers Research Advisory Council. Erin has published research in the fields of engineering education as well as the sociology of housing, neighborhoods, and the carceral system. She earned a PhD and MA in sociology as well as a certificate in demographic methods and a concentration in social statistics from the University of Washington. Erin also holds an MA and BA in Russian and Eastern European studies, and an AA in liberal arts and sciences.
Aryaa Rajouria University of Washington
Rebecca Schachtman University of Washington
Judith E Canner http://orcid.org/https://0000-0002-0625-2319
Dr. Jackie Bryce Miller University of California, Santa Barbara [biography]

Dr. Jack Miller (they/them) is a Teaching Professor in the Department of Statistics and Applied Probability at the University of California, Santa Barbara. Jack is passionate about diversity, equity, inclusion, and belonging in statistics and data science education and is also interested in leveraging technology for student understanding.
Abel Rodriguez University of Washington

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on February 9, 2025, and to all visitors after the conference ends on February 11, 2025

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