Projects

Python 4 All

With the support of a microgrant, the original “Coding Community” project aims to expand its impact by strengthening its Python programming content in three ways. This includes adding technical support and producing tutorial videos on core Python topics, enabling students to choose videos that best fit their interests and contexts. The project will hire undergraduate research assistants, providing opportunities for historically marginalized students and all assistants with training in culturally responsive pedagogy. In parallel with content development, the team will

Active Learning Strategies Workshop for STEM Math Faculty

This project aims to proactively address equity gaps for racialized minorities in calculus courses at El Camino College, responding to a nationwide call for racial and social justice in 2020. Despite the increased accessibility to transfer-level math courses through AB 705, disparities persist, notably seen in Math 190 (Calc 1), where the overall success rate was 50.7%. However, when disaggregated by race, the success rate for Black/African American and Latinx students was only 38.5%, compared to 68.2% for White students.

Growing Grading for Growth in STEM

This project builds on the successful development of Standards-Based Grading curriculum, assessment, and practices of the “Grading for Growth in Calculus” project led by an intersegmental faculty team from California State University, Monterey Bay and Hartnell College. In the initial effort, an innovative Standards-Based Grading (SBG) system was created for Calculus I courses resulting in improved student grades. The goal of the current project is to expand the benefits of SBG for students earlier on in the Calculus sequence and

Cohort Coordinator for Data Science Education

The Cohort Coordinator for Data Science Education plays a pivotal role in California’s efforts to expand access to high-quality data science (DS) instruction across the state’s public higher education systems. This team supports coordination, communication, and collaboration among institutions participating in the California Learning Lab’s Data Science Grand Challenge and the California Alliance for Data Science Education (CADSE), ensuring alignment with statewide transfer initiatives such as the Transfer Model Curriculum (TMC) and the UC Data Science Transfer Pathway. What the Cohort

Southern California Consortium for Data Science

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

Building Inclusive and Collaborative Foundations in Data Science

Berkeley CC, CC of San Francisco, Laney College, UC Berkeley, and UC Merced propose to develop Data Science (DS) programs that embody the Foundations of Data Science (FDS) framework, meet the needs of students through a localized curriculum, and provide a roadmap for transfer to remove institutional barriers for a DS degree at a 4-year institution. Partners will build a broader framework for FDS that combines computational and statistical thinking in the context of real-world problem-solving and its societal and

Greater LA Data Science Pathways (GLADS-PATH)

The Greater LA Data Science Pathways aims to: (i) bring together partners at the high-school, 2-year and 4-year level with a common goal of creating flexible pathways (ii) develop a Network Improvement Community (NIC) among the partnering institutions to share best practices on curriculum development as well as strategies for student success, (ii) support transfer students through the creation of Bridge programs, (iv) develop an Undergraduate Learning Assistant (ULA) program, and (v) extend Data Science education through the development of

INCLUDE

The INCLUDE project seeks to build an inclusive pathway for students to pursue a BS in Data Science (DS). CSUEB will upgrade its DS concentration to a full B.S. in DS, with interdisciplinary pathways for students to pursue. The grant will focus on: 1) increasing who pursues a career in data science through targeted outreach at the community college (CC) level, 2) developing new courses in math, that break away from the traditional Calc I-Calc II pathways that most DS

Programs for Institutional Pathway Engagement–acceLerating INfrastructure and Education (PIPE-LINE)

Project PIPE-LINE (Programs for Institutional Pathway Engagement – acceLerating INfrastructure and Education), is a Pathways Development proposal in response to the California Learning Lab Grand Challenge: Building Critical Mass for Data Science Request for Proposals. It offers a collaborative and sustainable program for developing pathways and overcoming equity gaps in data science learning with California State University, Fullerton (CSUF) as the host organization and a diverse set of partnering organizations including: University of California, Irvine (UCI) and two California Community

Collaborative Design of Interdisciplinary, Inclusive, Introductory Data Science Course Modules

UC Merced, UC Berkeley, and Laney College are collaborating to create interdisciplinary “course modules” with socially-centered data applications to be taught in a variety of introductory courses in math, computing, and data science. A complete “course module” will be a coordinated, open-sourced collection of instructional videos, computing labs, small-group discussions, projects, assessments, instructional pedagogy guides, and other curricular materials that can be adopted partly or wholly as 1-3 weeks of coursework. Each scaffolded course module will provide baseline training in

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