Diversifying and Advancing the Future of Social Work Science: Teaching and Evaluating Data Science with HBCU Students

Rapid advances in technology are driving the need for a workforce possessing data science skills across industries. Better access to science, technology, engineering, and mathematics (STEM) education among Black and other marginalized students has been the center of the discussion in education. Social work science is not often mentioned in these discussions, yet a data-capable social work workforce that leverages data-driven solutions to social problems is necessary for advancing social work research in the coming years. Disparities in science are indicative of the need for the expansion of data science research that advocates for social justice and the transformation of new knowledge into equitable opportunities. Scholars at a Historically Black College and University (HBCU) have engaged in participatory action research (PAR) in the form of faculty/staff workshops, curriculum development workgroups, and research affinity cohorts to increase the number of Black undergraduate and graduate social work students equipped with data science knowledge that will result in greater societal impact addressing critical social problems. This work aims to build on the legacy of W. E. B. DuBois' pioneering data-driven analysis and visualization techniques and continues ongoing efforts to challenge racially biased scientific methods that continue to impact social work and health disparities science. The purpose of this roundtable is to present information on the process of developing and implementing a cohort-based program of social work students at a HBCU and to generate discussion about its relevance for Black social work students, social problems impacting members of the African Diaspora, and opportunities to enrich the conversation about recentering and democratizing social work research. Within this roundtable format, five presenters will discuss their experiences with the project proposal, the implementation of the first cohort of students (Summer 2022), and salient knowledge ascertained while engaging in the project. To this end, the first two presenters will discuss data science in social work education (one from the undergraduate perspective, and one from the graduate student perspective). The third will discuss the emphasis to decolonize standard methodology while teaching data science using the DIASPORA Model. The fourth presenter will discuss the importance of mentoring Black social work students in the areas of data science. Finally, the fifth presenter will discuss funding opportunities for Black students. In addition to facilitating the conversation between presenters and participants, the organizer will discuss the outcomes and implications from evaluating the project. Participants will be encouraged to engage in the discussion by exploring their experiences with Black social work students regarding the development of research agendas that centers on the technology of data science in social work research. Black social work students are represented on all campuses in varying numbers. We hope this roundtable will enhance research scholars' ability to recognize disparities in social work research and rectify them by offering more opportunities for contributions from Black social work students.