Modeling Women's Elective Choices in Computing

dc.contributor.authorBradley, Stevenen
dc.contributor.authorParker, Mirandaen
dc.contributor.authorAltin, Rukiyeen
dc.contributor.authorBarker, Leciaen
dc.contributor.authorHooshangi, Saraen
dc.contributor.authorKunkeler, Thomen
dc.contributor.authorLennon, Ruthen
dc.contributor.authorMcNeill, Fionaen
dc.contributor.authorMinguillón, Juliàen
dc.contributor.authorParkinson, Jacken
dc.contributor.authorPeltsverger, Svetlanaen
dc.contributor.authorSibia, Naazen
dc.date.accessioned2024-03-01T13:17:56Zen
dc.date.available2024-03-01T13:17:56Zen
dc.date.issued2023-12-22en
dc.date.updated2024-01-01T08:55:53Zen
dc.description.abstractEvidence-based strategies suggest ways to reduce the gender gap in computing. For example, elective classes are valuable in enabling students to choose in which directions to expand their computing knowledge in areas aligned with their interests. The availability of electives of interest may also make computing programs of study more meaningful to women. However, research on which elective computing topics are more appealing to women is often class or institution specific. In this study, we investigate differences in enrollment within undergraduate-level elective classes in computing to study differences between women and men. The study combined data from nine institutions from both Western Europe and North America and included 272 different classes with 49,710 student enrollments. These classes were encoded using ACM curriculum guidelines and combined with the enrollment data to build a hierarchical statistical model of factors affecting student choice. Our model shows which elective topics are less popular with all students (including fundamentals of programming languages and parallel and distributed computing), and which elective topics are more popular with women students (including mathematical and statistical foundations, human computer interaction and society, ethics, and professionalism). Understanding which classes appeal to different students can help departments gain insight of student choices and develop programs accordingly. Additionally, these choices can also help departments explore whether some students are less likely to choose certain classes than others, indicating potential barriers to participation in computing.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1145/3623762.3633497en
dc.identifier.urihttps://hdl.handle.net/10919/118226en
dc.language.isoenen
dc.publisherACMen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.holderThe author(s)en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleModeling Women's Elective Choices in Computingen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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