Wang, SusanJaneja, VandanaHarding, DavidVon Vacano, ClaudiaLobo, Daniel2025-01-082025-01-082023-03Wang, Susan, Vandana Janeja, David Harding, Claudia Von Vacano, and Daniel Lobo. “ADOPTING DATA SCIENCE CURRICULA: A STUDENT CENTRIC EVALUATION,” March 2023, 8309–15. https://doi.org/10.21125/inted.2023.2276.https://doi.org/10.21125/inted.2023.2276http://hdl.handle.net/11603/3715617th International Technology, Education and Development Conference, 6-8 March, 2023, Valencia, SpainWith the advent of data science as a new discipline and high demand for a skilled workforce, educators are increasingly recognizing the value of translating courses and programs that have been shown to be successful and sharing lessons learned in increasing diversity in data science education. In this paper, we describe and analyze our experiences translating a lower-division data science curriculum from the University of California, Berkeley’s Data 8 Foundations of Data Science course to other settings with very different student populations and institutional contexts at the University of Maryland, Baltimore County and Mills College during Fall 2021. It is essential to motivate students to meaningfully take part in their journey into a data science career. We wanted to consider their perceptions and motivations to take the foundations course and the next steps emerging from the foundations course.7 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.UMBC Cybersecurity InstituteCurriculum AdoptionDiversity in EducationInstitutional ContextSurvey EvaluationCourse AdaptationPerceptions of Data ScienceEthics in Data ScienceEquity and InclusionText