Praxis Course: DSCI310: Data In Action
Semester: Spring 2026
Faculty Advisor/Professor: Jennifer Spohrer
Community Partner: Bryn Mawr Center for Career and Civic Engagement Center
Praxis Site Supervisor: Ellie Esmond
Praxis Poster:
DSCI310 Poster_Voter engagement
Further Context:
Since 2016, Bryn Mawr College has voluntarily shared its deidentified enrollment data with NSLVE (National Study of Learning, Voting, and Engagement), which matches it against publicly available voter files to understand voting patterns on college campuses. Our project, completed
in partnership with Bryn Mawr’s Career and Civic Engagement Center, set out to replicate this report, creating a locally hosted version that doesn’t depend on national funding or outside organizations. The demand for an independently run study grew from the recent scrutiny NSLVE and its parent organization, Tufts University’s Tisch College of Civic Life, has faced under the current federal administration over data privacy concerns. Our study responded by replicating the methods while addressing those concerns directly: conducting the study in-house rather than through an outside organization, communications and data shared solely among the team, and a public report to be generated later using fully anonymized data.
The idea was to use college-level demographic data and match it with publicly available data from Montgomery County across multiple election cycles. Soon after starting, we realized we couldn’t fully replicate the NSLVE methodology given our constraints. While NSLVE uses demographic and voting data submitted directly by colleges, we had access only to Montgomery County voter registration data and had to filter for registrants with Bryn Mawr campus box addresses to identify likely student voters. The enrollment records needed for a full replication were not available to us. Another limitation that NSLVE also acknowledges is that many students do a mail-in ballot in their home county when they are enrolled in Bryn Mawr, which leads to an undercount of engaged students. An additional constraint was that publicly available datasets pre-2026 were not clean enough to analyze—missing column headers, floating numbers, and inconsistent formatting meant we ultimately worked with the 2026 Montgomery
County data.
Our 2026 data came with significant limitations. Unlike the NSLVE, which includes variables like race, ethnicity, and education level, our Montgomery County dataset had none of those demographic breakdowns, leaving us with age and party registration as our primary analytical variables. Earlier datasets were also too inconsistent to use (missing column headers, floating numbers, and unclear formatting) and we had no way to match voter records directly to enrollment data. Critically, our dataset included only a single DateLastVoted field rather than separate columns for each election cycle, meaning we could not isolate who voted in which specific election. A student who voted in 2020 but not since would show 2020 as their last vote, while a student who voted in both 2020 and 2024 would show only 2024, making it impossible to cleanly attribute participation to any one cycle. Given this constraint, we used all available data to answer a broader question: had each student voted in at least one election since 2020? Working within those constraints, we calculated age as of Election Day from date of birth, binned students into age groups matching NSLVE’s categories, and built pivot tables tracking 2024 presidential and 2025 municipal election participation as best we could from the available data.
Of the 1,438 total Montgomery County registrants in the 19010 zip code, 1,206 (about 83.8%) had campus box addresses, suggesting they are likely students. Combining the 2024 and 2025 cycles, we identified 551 civically engaged students (45.7% of locally registered BMC students) who voted in at least one of those two elections. The 22-24 age group showed the highest 2024 presidential turnout at 25.9%, while the 2025 municipal election saw 37.3% participation overall. We found that 1,110 of 1,206 registered students (92%) had voted in at least one election cycle since 2020, though this figure should be interpreted cautiously, as it relies on a single DateLastVoted field rather than full voting history, meaning students who voted in 2020 or 2022 but not since would not appear in our count, and the figure may be somewhat inflated for recent cycles. All of these figures are known undercounts (students registered at out-of-county home addresses cannot be tracked) but the data demonstrates that students who do register locally are meaningfully and consistently engaged in democracy.
We documented every methodological decision and limitation so that the next team to take on this project will not face the same obstacles from scratch. The most important thing we learned is that missing and unclear data is not a dead end, it can be used to infer information and tell its own story about where gaps in civic infrastructure or data collection exist.
To complement the data analysis, we designed a survey on Qualtrics to understand voting behavior and preferences among Bryn Mawr students, with the goal of identifying areas where the Voting Education and Support office can better serve students and make the case for a polling station on campus. We used branching logic to tailor the survey experience to each student’s voting eligibility, status, and experience, and included international students to inform them about civic engagement beyond simply casting a ballot. Throughout the design process, we applied Data Action principles from class i.e. purpose, policy, biases, ground-truthing, and participatory ethics to ensure the survey was relevant to the entire Bryn Mawr population. The survey is set to be deployed on April 30, 2026 at the Montgomery County Voter Drive at Bryn Mawr College.
This project demonstrated that a locally produced voter engagement report is feasible, even with imperfect data. The biggest lesson we learned was that finding creative ways to work with the data you have, rather than waiting for ideal conditions, is itself a data science skill. Next steps in this project include using survey results to refine the Civic Engagement Center’s
outreach strategies and publishing a public-facing report in accordance with data privacy guidelines. We hope this locally produced mini-report serves as a foundation for Bryn Mawr to continue tracking student voter engagement independently, regardless of what happens to national data infrastructure, and that the groundwork we laid makes the next iteration of this project faster, cleaner, and more complete.