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DSXP Data Science Experiential Pathways: Scalable Intersegmental Workforce Training Program

Published onJan 31, 2025
DSXP Data Science Experiential Pathways: Scalable Intersegmental Workforce Training Program

Real-world data science experiences addressing societal challenges offer highly engaging learning opportunities for students at all levels. These projects foster key data science skills like data visualization, cleaning, analysis, decision-making, inference, and effective communication. Teamwork, near-peer mentoring, and collaboration with experts from education, industry, government, and nonprofits further enhance this multidisciplinary learning approach. This short talks session showcases an integrated "Data Science Experiential Pathways" (DSXP) model, pilot-tested in 2024 with high schools, community colleges, and universities. Co-chaired by Anthony Suen (UC Berkeley Data Science Discovery program) and Judy Cameron (DataJam Director, University of Pittsburgh), the session will feature: 1. Judy Cameron discussing DataJam, a decade-long national project-based data science program and competition for high school and community college students, 2. Luella Fu (SFSU professor) on a DataJam Mentor training program for undergraduates, 3. Kyla Oh and/or Denise Hum (Laney & Skyline Community Colleges faculty) sharing their experiences advising DataJam teams, 4. Anthony Suen on his Data Science Discovery program's role in facilitating student and mentor exchanges within DataJam and setting up Discovery Projects in domain areas like transportation, and 5. Sarah Stone (Director of Data Science for Social Good at University of Washington) shares her experience on leading intensive summer research fellowships. This scalable, integrated DSXP model holds the potential to transform data science education and workforce training, addressing societal challenges while preparing future data scientists.

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