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Introducing Women to Data Science: Investigating the Gender Gap in a Learning Initiative on Kaggle

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dc.contributor.authorTwyman, Marlon
dc.contributor.authorMajchrzak, Ann
dc.date.accessioned2023-12-26T18:52:51Z
dc.date.available2023-12-26T18:52:51Z
dc.date.issued2024-01-03
dc.identifier.doihttps://doi.org/10.24251/HICSS.2024.861
dc.identifier.isbn978-0-9981331-7-1
dc.identifier.otherec092780-a2ef-4800-9d10-d53b4b58ff35
dc.identifier.urihttps://hdl.handle.net/10125/107247
dc.language.isoeng
dc.relation.ispartofProceedings of the 57th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectSTEM Education and Workforce Development: Addressing Equity and Inclusion for Underserved Populations
dc.subjectdata science
dc.subjectgender gaps
dc.subjectinformal learning
dc.subjectonline communities
dc.subjectstem
dc.titleIntroducing Women to Data Science: Investigating the Gender Gap in a Learning Initiative on Kaggle
dc.typeConference Paper
dc.type.dcmiText
dcterms.abstractUnlike many STEM fields, data science has emerged with online communities serving as prominent spaces for professional development and learning. This paper explores factors that contribute to gender differences regarding perceptions of satisfaction and difficulty in a learning initiative for data science hosted by the Kaggle community. We investigate multiple factors: prior experience and skills, professional role, and communication within a learning community. Our results, based on a survey of 2,707 aspiring data scientists, suggest that learners who identify as women do not perceive assignments to be more difficult than men, but complete fewer assignments. The increasing difficulty of the learning experience affected all learners, but men were still able to complete the hardest assignments at a higher rate than women despite experiencing similar barriers. Overall, the findings demonstrate how learning initiatives in technically intensive domains contribute to different outcomes between groups.
dcterms.extent10 pages
prism.startingpage7184

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STEM Education and Workforce Development: Addressing Equity and Inclusion for Underserved Populations