Data Storytelling, Endowment Inequality, and the IF Retreat at Howard

Kenton Rambsy, Dana Williams, Keyanah Nurse

By Kenton Rambsy 

The American Council of Learned Societies (ACLS) launched the Intention Foundry (IF) to support inclusive change in higher education. Funded by the Mellon Foundation and originally designed by Dr. Jovonne Bickerstaff, IF brings together scholars, administrators, and academic society leaders to pursue practical responses to long-standing inequities in the academy. Now led by Dr. Keyanah Nurse, IF emphasizes community building, intentional design, and collaborative problem-solving. 

This summer, the IF retreat took place at Howard University from June 3 to June 5, 2025. The event marked the culmination of a semester-long virtual institute. Alongside my co-steering committee members, Marian Toledo Candelaria and Jennifer Gammage, I helped develop and facilitate a curriculum centered on data storytelling. As the data storytelling specialist in the Center for Applied Data Science and Analytics (CADSA) at Howard, I brought elements of our instructional model to the retreat. Our work showed what happens when social justice priorities align with technical training and critical thinking.

We introduced participants to the FLOAT Method—Formulate, Locate, Organize, Analyze, and Tell—and guided them in using Tableau Public to build data stories. To anchor the institute, we used a shared dataset on HBCU endowments. This decision allowed participants to work from a common reference point and explore structural inequality through data. We added comparative figures from select PWIs to underscore the vast wealth gap.

 
Howard’s endowment stands at just over one billion dollars, the highest among HBCUs. Yet even that amount falls far behind elite institutions like Harvard, which holds over fifty billion. Most HBCUs operate with endowments below fifty million. This activity helped participants see how data can illuminate underfunding, especially when presented in accessible and visual formats.

Two of my Black Data Lab interns at Howard supported the retreat as technical assistants. Cierra Larke, a recent graduate from our data science program, created a visualization that mapped endowments and enrollment numbers across all HBCUs. Emily Duru, a PhD student in English, designed a dashboard  comparing top HBCUs with public and private PWIs.

In my opening remarks, I referenced the Supreme Court’s 2023 decision to end affirmative action. Justice Clarence Thomas, citing an NSF study, argued that HBCUs already produce a disproportionate number of Black judges, lawyers, and scientists. He framed that success as evidence that HBCUs do not need further support. His statement misreads the issue. Outcomes achieved under resource constraints should not be used to justify disinvestment.

The IF retreat demonstrated how data storytelling can clarify urgent problems and prepare scholars to engage broader publics. Howard provided a fitting setting for this work. We used the institute to cultivate technical fluency, historical awareness, and collective insight. It was a clear example of what becomes possible when equity-focused pedagogy meets the tools of data analysis.

Related:

• How HBCUs Do More with Less: A Visualization by Emily Duru