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This paper describes the design and development of a web-based Data Science Learning Platform (DSLP) aimed at making hands-on data science learning accessible to non computing majors with little or no programming background. The platform works as middleware between users such as students or instructors, and data science libraries (in Python or R), creating an accessible lab environment. It allows students to focus on the high-level workflow of processing and analyzing data, offering varying levels of coding support to accommodate diverse programming skills. Additionally, this paper briefly presents some sample hands-on exercises of using the DSLP to analyze data and interpret the analysis results.more » « lessFree, publicly-accessible full text available June 22, 2026
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Xumin Liu; Erik Golen (, Proceedings ASEE annual conference)
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Liu, Xumin; Golen, Erik; Raj, Rajendra K.; Fluet, Kimberly (, Proceedings of the 2nd International Workshop on Data Systems Education: Bridging education practice with education research)
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Liu, Xumin; Golen, Erik; Raj, Rajendra K. (, Proceedings of the 53rd ACM Technical Symposium on Computer Science Education)
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Liu, Xumin; Golen, Erik; Raj, Rajendra K. (, Proceedings of the 53rd ACM Technical Symposium on Computer Science Education)
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Liu, X.; Golen, E.; Raj, R. (, ASEE annual conference exposition proceedings)
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