Collaborative development of a new introductory, interdisciplinary course for computing, data science, and society.
The introductory Data Science curriculum is at the intersection of computing, statistics, and the social and behavioral sciences. The course consists of scaffolded modules designed to promote effective engagement with modern socio-technical systems.
This partnership developes course modules in teams composed of members from institution with the intention of sharing interdisciplinary knowledge, experience with a variety of students, and range of classroom practices.
Project Events¶
Spring 2026: Second Spark seminar offering at UC Merced! Second offering at Folsom Lake City College!
Fall 2025: Full curriculum taught at UC Berkeley and Tuskegee University! First offering at Folsom Lake City College!
Summer 2025: Sample curriculum published at the National Workshop. See Workshop Slides
Fall 2024: First offering at Laney College! First academic-year offering at UC Berkeley!
Summer 2024: UC Berkeley Data 6 starts implementing some of the new curriculum. Almost ready to share...!
June 2024: We are excited to welcome LA City College, who will be teaching Data 6 starting this Fall 2024.
June 2024: We held an in-person curriculum workshop co-located with the National Workshop on Data Science Education at UC Berkeley! Please see our presentation slides.
Spring 2024: Exploratory course offering with UC Merced’s Spark Seminar, targeted towards campus freshmen from all disciplines.
Fall 2023: Initial collaboration and idea design.
Summer 2023: Pilot set of modules in UC Berkeley’s Summer Data 6.
Curriculum Overview¶
This project has developed a course with four course modules, each built as 2-4 week units and designed by interdisciplinary, inter-institutional teams:
Fundamental Data Structures for Data Science. Williams and Bortfeld (chairs).
Visualization, Gender, and Education. Yan (chair).
Social Application Core: Algorithms and Functions. Marcia (chair).
Text processing and data analysis. Ndoye (chair).
Access our full curriculum.
Why DUBOIS?¶
At the core of our activities, we would like to support Data science for Undergraduates to Broaden Opportunities for advancing an Inclusive Society. W.E.B. Du Bois was a prominent 20th century African American activist who leveraged data science and visualization to advocate for Pan-African civil rights.
Usage and License¶
We appreciate email communication to track partial or full course adoption. Please contact the Principal Investigators by email if you would like to use this work. Send a quick email describing your institutional affiliation, course title, target semester, and estimated student enrollment.
Unless otherwise mentioned, all contents are licensed for free consumption under the following license: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-SA 4.0)
Acknkowledgments and Support¶
This project is funded by the following sources:
This material is based upon work supported by the U.S. National Science Foundation under Grant Nos. 2245877, 2245878, 2245879. NSF IUSE CUE. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
California Learning Lab. Collaborative Design of Interdisciplinary, Inclusive, Introductory Data Science Course Modules [link]