your own course-recommendation algorithm. What is it designed to do?
Our algorithm is an open-source recommendation engine that identifies for community college students courses they can take that fulfill degree and transfer requirements and that maximize their predicted probability of academic success. We made the tool both to generate recommendations for students and to support advisors to provide more tailored guidance when they’re meeting with students about course registration. At many community colleges advisors have at least 1,000 students on their caseload and just may not have the time to research course maps that best position each student for success. Our algorithm hopefully saves advisors time and supports them to provide students with more tailored guidance about educational pathways that advance their degree and transfer goals.
Q. How does your longstanding partnership with the Virginia Community College System inform a project like this?
This kind of project wouldn’t be possible without the close and ongoing partnership of the Virginia Community College System and the individual colleges. The System’s incredible data systems are what make it possible for us to bring data science methods to bear, and we rely on close collaborations with college staff to design and implement interventions that are well-suited to the local context and student population.
Q: How will you be testing your design and what do you hope to see?
We test all of our innovations through randomized controlled trials—the same rigorous evaluation strategy used in medicine, for example, to test COVID vaccines. We hope to see whether providing these personalized course recommendations leads students to accumulate more credits that count for transfer and degree and to make additional progress towards their degree or transfer goals.
Q: What makes you hopeful about the future use of these data systems in education?
Both undergrads and graduate students are increasingly taking the kinds of data science courses that equip them with the skills they need to bring to bear Netflix-style algorithms to solve public sector problems. I’m most excited to see how future researchers partner with public agencies and organizations to deploy algorithms and other machine learning strategies in ways that make it easier for historically marginalized populations to achieve educational and workforce success.
