The Social Sciences D-Lab recently launched a new program to prepare postdocs to lead research and teaching that emphasize equity, cultural relevance and ethical practice in data science.
In partnership with the Berkeley School of Education (BSE) and the College of Computing, Data Science, and Society (CDSS), the two-year Berkeley Data Science Education Fellowship provides three postdocs with monthly skill-building workshops, teaching opportunities and multidisciplinary research opportunities.
“In today’s AI-driven world, ensuring that data science is both inclusive and ethical is not just valuable, it is essential. This fellowship reflects our commitment in the Social Sciences to advancing data science education in ways that safeguard society while broadening opportunity,” Berkeley Social Sciences Dean Raka Ray said.
The fellowship aims to teach postdocs how to build data science curricula that are responsive to the student populations they are working with, such as K-12 students interested in data science, traditional undergraduates, or community college students and transfers.
The program hopes to bring more communication in the field of data science education, with fellows that come from different backgrounds and bring diverse perspectives.
"This is an all-hands-on-deck effort," said Claudia Natalia von Vacano, executive director of the Social Sciences D-Lab and co-principal investigator. "Our previous Data Science at Scale research, led by Principal Investigator David J. Harding and Rodolfo Mendoza, over the last six years, indicate that women of color, particularly Black and Latina women, face significant barriers in data science. They report experiencing specific racist and sexist comments that discourage them from staying in the field."
In response, von Vacano said they are “working to create safe spaces and support systems to encourage women of color to persevere within the D-Lab and in collaboration with the Data Scholars program run by the CDSS, a program created and supported by the D-Lab."
Berkeley Data Science Education Fellowship builds on the work of the Social Sciences D-Lab, Dean Ray said. For over a decade, the D-Lab has been a crucial resource in supporting students, faculty, and staff in data-intensive social science research.
In the first year of the fellowship, fellows will rotate through projects in CDSS, BSE and D-Lab. One project includes how AI can help facilitate better pedagogy and educational outcomes.
In the second year, fellows will pair up with faculty mentors and launch an independent research project. Through workshops and large-format introductory courses, fellows will also gain data science teaching experience.
“Data science education is moving very, very quickly. And the thing about moving quickly is you don’t want people left behind,” said Michelle Wilkerson, the fellowship’s principal investigator. “Data science education happens at so many different levels — K-12, community colleges, courses here at Berkeley. This is really an opportunity to start thinking long-term about how we can work towards coherence with so many different ideas of what data science is.”
Wilkerson hopes the fellows will leave the program with stronger cross-unit collaboration, improved accessibility in data science education, and the capacity to serve as intellectual foundations for the future of the field.
