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High School Students Make Data Science Research Accessible
The School of Data Science hosted a celebratory evening on April 22 in the Capital One Hub, bringing together students, faculty, and community members for the second annual Data Science Research Demystification Project showcase. The event highlighted the work of more than 40 high school students from local Charlottesville secondary schools who spent weeks translating complex academic research into clear, accessible language.
The demystification project, now in its second year, reflects the School’s broader mission to make data science relevant, understandable, and impactful beyond the university. In an addition to the program pilot’s initial cohort of just students from the Renaissance School, this year included students from Albemarle High School, Renaissance School, and St. Anne’s-Belfield School.
Organized by the Office of Community Affairs, the program pairs high school students with published research from School of Data Science faculty. Over the course of the project, students read and analyzed scholarly papers, built vocabulary lists, and ultimately produced one- to two-page summaries written at a sixth to eighth grade reading level. Some groups extended their work even further, creating animated videos or translating their summaries into American Sign Language (ASL).
Opening the event, Emma Cox, the program coordinator and School events manager, emphasized the importance of accessibility in research communication. Drawing on a metaphor from “The Lord of the Rings,” she described academic writing as something that can take “a really long time to say anything,” likening it to the slow, deliberate speech of tree-like Ents. The students, she explained, serve as “research ambassadors,” distilling dense, jargon-filled papers into language that more people can understand. This work is especially meaningful given that a significant portion of U.S. adults read at or below a middle-school level, making accessible communication not just beneficial, but necessary.
Mar Hicks, an associate professor of data science and faculty sponsor, reinforced this message by situating the project within a larger social context. Emphasizing the interdisciplinary nature of data science, Hicks noted that the field is not only about technical tools but also about understanding how data operates within broader social, political, and economic systems. Making research more legible, Hicks argued, helps communities better understand how data is used and empowers them to hold institutions accountable.
“By participating in this program, you have helped us in that mission to get a few more steps toward making data science into something that isn't locked behind doors and done by very specific people with specific interests and goals,” Hicks said. In this way, the demystification project is much more than an academic exercise; it is an accessible endeavor that helps bridge gaps between researchers and the public.
Faculty contributions played a key role in the program’s success. Papers from researchers provided the foundation for student work, exposing participants to a wide range of topics within data science. This year, students worked with the following papers authored by data science faculty:
- “Characterizing advanced heart failure risk and hemodynamic phenotypes using interpretable machine learning” by associate professor Prince Afriyie et al.
- “Stressor‐Evoked Brain Activity, Cardiovascular Reactivity, and Subclinical Atherosclerosis in Midlife Adults” by assistant professor Javier Rasero et al.
- "The Neurogenetics of Functional Connectivity Alterations in Autism: Insights From Subtyping in 657 Individuals” by assistant professor Javier Rasero et al.
- “The Potential Impact of Disruptive AI Innovations on U.S. Occupations” by professor YY Ahn, et al.
- “Quantifying Hierarchy and Prestige in U.S. Ballet Academies as Social Predictors of Career Success” by assistant professor Alex Gates et al.
- “A Mathematical Introduction to Neural Networks” by associate professor Gianluca Guadagni
- “The Baby and the Black Box: A History of Software, Sexism, and the Sound Barrier” by associate professor and faculty sponsor Mar Hicks
Student presentations offered insights into both the research topics and the learning process behind them. Beyond actionable and accessible plain language versions of the papers that students created, the true takeaways of their presentations included the learned importance of accessibility and the personal impact the project had.
One student concluded at the end of their presentation that: “Overall, this helped us understand that we're actually a lot more capable of understanding things and learning things than we necessarily think we are.” Another shared that synthesizing research from Rasero’s paper on the neurogenetics of autism helped them better understand their little brother with autism by learning more about the diagnosis and its effect on the brain.
Across all presentations, students consistently pointed to the same core takeaways. Many emphasized the importance of time management, particularly when balancing the project with other academic responsibilities. Others highlighted the expansion of their vocabulary and their growing confidence in tackling unfamiliar material. Perhaps most significantly, students reflected a shift in their perspectives. Research papers that once felt intimidating and inaccessible became understandable after being equipped with the necessary analytical and rhetorical tools.
A Renaissance student who was able to participate in the project both years commented on their experience with the program. “This demystification project has been a pleasure to work on,” they said. “I'm excited to see it expand in the coming years. Working on the pilot program last year was a great experience, and seeing it grow and expand to all these different schools has been great to see.”
Accessibility remained a central theme throughout the evening. The inclusion of ASL translations and multimedia elements demonstrated a commitment to reaching diverse audiences and recognizing different modes of communication. Students who created ASL versions of their work spoke about the challenges of translating not just language but structure, noting that written English and ASL follow different grammatical systems.
“Many people assume that deaf and hard of hearing people can just read a written article,” the student team explained. “While this is true, in some cases, written English has a completely different grammatical structure to ASL, and many deaf and hard of hearing people learn English as a second language to ASL if they learn it at all. This is why ASL translations are so important.” Their efforts highlighted the importance of considering accessibility in multiple dimensions.
Now in its second year, the Data Science Research Demystification Project continues to expand, strengthening connections between the School of Data Science and the local community. By equipping students with the tools to interpret and communicate complex ideas, the program advances the School’s mission of making data science accessible to all.
