The Southern California Consortium for Data Science consists of an intersegmental alliance of 8 partnering institutions: 3 CCs, 4 CSUs and 1 UC. The team of 19 PIs/co-PIs is based in Statistics/Math & Stats departments and brings wide ranging expertise in Data Science (DS) education. Leveraging its breadth, the proposed consortium will develop shared instructional resources and event templates that can be replicated and utilized across all partners. SCCDS is focused on two primary goals: (i) improve transfer pathways through curriculum alignment, course articulation and bridges for incoming transfer students; and, (ii) intersegmental outreach to promote data science careers among community college and high school students through hosting of DS focused events. As part of launching new introductory
DS courses and scaling up existing ones, the Consortium will engage in professional development, especially centered on inclusive pedagogy and DS ethics. With all project activities, our vision is to
increase the number of DS Transfers and broaden their diversity through an ongoing and authentic collaboration across the Consortium, incorporation of best practices that are culturally relevant
and inclusive, programming and recruitment efforts that focus on students’ and industry needs, and data-driven strategies for closing equity gaps.
Project Details
Principal Investigators
Mike Ludkovski, UCSB (PI)
Kelly Spoon, San Diego Mesa College (PI)
Ladera Barbee, LBCC (PI)
Edward Pineda-Castro, LACC (PI)
Jimmy Risk, CPP (PI)
Alona Kryshchenko, CSUCI (PI)
Richard Levine, SDSU (PI)
Babette Benken, CSULB (PI)
Kee Lam, LACC (Co-PI)
Armando Rivera-Figueroa, LACC (Co-PI)
Adam King, CPP (Co-PI)
Isaac Quintanilla Salinas, CSUCI (Co-PI)
Kagba Suaray, CSULB (Co-PI)
Henry Scharf , SDSU (Co-PI)
Sharon Tettegah, UCSB (Co-PI)
Alex Franks, UCSB (Co-PI)
Uma Ravat, UCSB (Co-PI)
Jack Miller, UCSB (Co-PI)
Juan Bernal, SD Mesa (Co-PI)
Grant Amount
$1,300,000
Tags
Resources:
See Southern California Consortium for Data Science project’s OER and other resources in CARLE (Curated Asset Repository for Learning Excellence)