Diversity is multi-dimensional and universities are in a particularly powerful position to engage structurally disadvantaged communities such as redlined neighborhoods, thereby providing a platform for upward mobility. Of the Secretary’s Advisor on Equity (SAE) five overarching DEI priorities, data science is the first action, ‘to address broad gaps in data collection to facilitate data-informed decision-making’. MDS3 addresses equity and diversity needs for more efficient, safe, reliable materials in the Stockpile Stewardship Program (SSP) and provides direct access to data-informed decision making for the nation’s security. The COE team will investigate root causes for baseline inequities in the workforce pipeline for SSP and injustices that can be addressed by engaging communities such as urban and rural neighborhoods that suffer environmental and economic inequalities due to geographic, geopolitical or low-income regions, veterans, and individuals facing other barriers to success such as digital access gaps and spatial mismatch related to jobs, housing, and economic mobility. Through a detailed metrics based plan, the COE leverages its data collection efforts into measurable action-based goals to:
- Engage local partners as recruitment sources and offer advanced data science curricula to teach both trade and academic skills, incentivized by making connections with lab and industrial based jobs at the end of each course.
- Catalyze and grow relationships with Project Lead the Way Schools in the Cleveland Metropolitan School District and Cleveland Heights University Heights School District through hands-on workshops and experiential learning opportunities on a semester basis.
- Coordinate with intra-University partners to identify and engage individuals from the community.
- Utilize supplemental funding opportunities to bolster resources and ensure student personnel are adequately supported and do not face undue financial barriers – i.e. having to choose between paid summer work and a research opportunity.
- Complete annual COE DEI audit to acquire data on team diversity, Center practices and needs, and utilize this data to inform recruitment strategies.
- Establish a confidential feedback system to allow channels for personnel to identify potential barriers to success, ensuring a positive and healthy environment for all team members to thrive.
In addition to workforce training, MDS3 will establish diverse and equitable student and community education programs and utilize an appreciative inquiry method to inform how programming evolves. While CWRU has a long tradition of supporting diverse students through many established programs, it is equally as important for the NNSA and our collaborators to have established workforce pipelines that provide access to personnel from historically underrepresented demographics and engage siloed or otherwise under-engaged communities.
Applied Data Science Curricula for Partner Institutions
Joint Undergraduate and Graduate Courses
At Case Western Reserve University, Dr. Roger French has developed a groundbreaking Applied Data Science curriculum with an accompanying model for providing foundational data science curriculum to partnering institutions at no cost. As the Kyocera Professor in Materials Science and Engineering with a Secondary Appointment in Computer and Data Science, Professor French has developed an innovative curriculum that taps into an area of significant research interest, equipping students with a unique competitive edge that cuts across many industries. Whether innovating for the future or working to improve the decision-making process, data lies at the heart of the challenge.
Participating students will complete two courses in an academic year with an optional third, introductory course for students who have not already completed an introductory computer programming course.
As the institution offering the curriculum, Case Western Reserve University provides:
- Structured course content which can be conducted remotely and synchronously in two to three semesters
- Teaching Assistant support for the first student cohort, after which Teaching Assistant responsibilitiesmay
- be transitioned to students at the partner institution that have completed the curriculum
- Free of charge – no funding obligation for the partner institution
