Tutoring has long been recognized as a valuable form of academic support—but its full impact often goes unmeasured. When campuses start collecting and analyzing data about their tutoring programs, they gain more than just statistics. They unlock insights that can drive smarter decisions, expand access, and make a lasting difference in student success.
That’s the real power of tutoring data.
Institutions may already track participation or total hours logged, but these high-level metrics only skim the surface. When used thoughtfully, data can reveal patterns, surface equity gaps, guide resource allocation, and help institutions better understand what’s working—and why. In other words, good data tells a story, and campuses that listen closely can use that story to evolve and improve their academic support strategies.
Looking Beyond the Basics
Most campuses begin with the basics: how many students showed up, how many sessions took place, how many tutors were involved. These numbers are easy to collect and helpful to know—but they don’t tell you much about student behavior, course-level needs, or the effectiveness of the tutoring itself.
By going deeper, institutions can start to see meaningful patterns. Who is using tutoring services, and who isn’t? Are students coming back for multiple sessions, or dropping off after one visit? Are there certain times of day when demand spikes? Are some tutors consistently rated higher by students, and what are they doing differently?
These types of insights offer a much more complete picture of tutoring engagement. They also help campuses proactively identify and respond to changing student needs in real time.
Transforming Feedback into Fuel
One of the most undervalued types of data is qualitative feedback from students themselves. Too often, this information is gathered (if at all) and then tucked away without much analysis. But comments from students can offer invaluable clues about what makes a tutoring session successful—or not.
When students say things like “My tutor helped me feel more confident about the material” or “She explained it in a way my professor never had,” they’re revealing what matters most in a tutoring interaction: relational connection, clarity, and trust. On the flip side, if students indicate that a session felt rushed or unhelpful, that’s an opportunity to revisit training, expectations, or even tutor matching.
By systematically collecting and reviewing this type of feedback, institutions can continuously improve the quality of their tutoring programs. It also offers an organic way to recognize outstanding peer tutors and share success stories that highlight the value of the program—something that’s especially important when advocating for continued or expanded funding.
Data as a Driver for Equity
Tutoring isn’t just about academic reinforcement—it’s also a tool for equity. But equitable support doesn’t happen by accident. Without data, it’s nearly impossible to know whether tutoring is truly reaching the students who need it most.
A well-designed data strategy can help identify gaps in access. Are underrepresented students showing up to sessions at the same rate as their peers? Are students in gateway courses engaging with support early enough in the semester to make a difference? Are those at higher risk of stopping out connecting with peer tutors before it’s too late?
These are questions data can help answer—and that answers can help solve.
By proactively identifying and addressing these gaps, campuses can build tutoring programs that don’t just serve students who already know how to seek out help, but also intentionally reach those who might otherwise fall through the cracks. That’s where the real equity work happens.
Making the Case for Tutoring Through Data
One of the most important roles tutoring data can play is in helping program leaders tell their story. Whether you’re making the case to maintain funding, expand services, or integrate tutoring into a broader student success initiative, having reliable, specific data makes the conversation more compelling.
Rather than simply saying, “Students benefit from tutoring,” imagine being able to say: “In Fall 2024, 82% of students who attended three or more peer tutoring sessions in gateway math courses passed their class, compared to 63% of those who didn’t.” Or, “We saw a 30% increase in tutoring usage after shifting to course-specific peer tutors trained in cultural competence.” Those numbers—and the stories behind them—resonate with institutional stakeholders in ways that vague anecdotes never will.
From Data to Direction
Ultimately, good tutoring data should lead to action. It should inform tutor recruitment and training. It should shape outreach strategies to students. It should influence when and how support is offered. And it should help campus leaders understand what’s working and what needs to change.
Tutoring is one of the most relational and responsive forms of academic support, but that doesn’t mean it should be immune to data-driven decision-making. In fact, the combination of personalized peer learning and smart, intentional data use is what makes the most powerful programs stand out.
When institutions commit to gathering, interpreting, and acting on tutoring data, they aren’t just measuring success—they’re multiplying it.
Want to learn how your campus can use tutoring data to drive meaningful change? Reach out to the team at Knack—we’d love to show you how we’re helping institutions turn insights into action and build more equitable, impactful support for every student.
