Institutions Are Investing in Data. It’s Not Reaching the Classroom

The Breakdown

The gap here isn’t between ambition and resources. It’s between where investment is going and where impact needs to land.

Administrators’ top digital learning priorities center on flexibility for all students (48%), retention (41%) and enrollment growth (37%). Those are the right goals. But course-level analytics ranks last at 9%. That tension is hard to square. You can’t optimize for retention and enrollment if you can’t see what’s happening at the course level.

Only 35% of faculty adjust instruction based on student performance data. Only 11% use disaggregated student data. The infrastructure investments administrators are planning need to result in faculty-facing tools that surface actionable signals, not campus-wide dashboards that require navigation to be useful.

Dr. Zone sees this as a persistent cultural problem as much as a technical one. “This has been an issue for a long time. We have a drumbeat of ‘data-driven decision making,’ but access to data is not enough.” The gap, she argues, speaks to a leadership and innovation culture that institutions haven’t fully closed, even as their investment in data infrastructure grows.

Part of what makes closing that gap urgent is understanding what the learning platform is. The LMS isn’t one tool among many — it’s the connective tissue of the entire institution. When it’s working well, it provides the signals that enable student success across every touchpoint: advising, faculty outreach, retention interventions, assessment design and more. And because the platform is where teaching, learning, compliance and student data all converge, its security and stability aren’t peripheral concerns; they’re foundational ones.

An institution can have the best data strategy in the world, but if the infrastructure holding that data isn’t secure, the consequences extend far beyond a single system. Treating platform selection as a commodity procurement decision rather than a strategic one carries risk that only becomes visible when something goes wrong.

Dr. Ford raised the C+ data quality grade as both a problem and an opening. The fact that it hasn’t moved in two years signals a persistent gap, but it also means there’s real room to improve. The institutions that close that gap will be in a much stronger position to act on the student success data they’re investing in collecting.

She also drew a direct line between the data infrastructure conversation and what needs to change at the classroom level: the investment in data quality only matters if it results in tools faculty can act on, requiring instructional design, faculty development and platform design working together — not infrastructure improvements that stop at the institutional level.