Closing the Data Literacy Culture Gap

Colleges and universities face difficult choices—tight resources, accountability demands, shifting student demographics, and rapid technology evolution. In that context, data should be a stabilizer: a shared language for asking better questions, prioritizing investments, improving student outcomes, and closing the loop on decisions. But across institutions, the ability to use information well is uneven. Skills vary widely, practices are inconsistent, and culture often defaults to tradition over evidence.

Accreditors and state systems increasingly expect transparent, data-informed practices and evidence of action. The challenge is not a lack of data, but the absence of durable, institution-wide capacity; that is, common concepts and vocabulary, repeatable habits, replicable processes, and the confidence to use information well in everyday decisions.

The State of Data Literacy

Since 2015, the Association for Institutional Research (AIR) National Survey has provided the most comprehensive, longitudinal look at the data function in U.S. higher education. As the only longitudinal survey of its kind, it is a cornerstone resource that informs AIR Data & Decisions Consulting’s frameworks and guidance to institutions. Conducted every three years, the survey tracks how IR/IE offices are structured, staffed, and resourced, and how they contribute to institutional data capacity and decision-making.

The 2018, 2021, and 2024 administrations of the AIR National Survey included questions about data literacy, allowing us to trace shifts over time. The survey results highlight three key takeaways about the state of data literacy:

Training matters. Institutions that provide data literacy training show strikingly higher ratings of employee capability—nearly double—compared to those that do not. Intentional training clearly moves the needle.
Progress is real—but incomplete. Institutions that offer training grew from less than one-third in 2018 to nearly 60% in 2024. That’s meaningful progress, but not universal, and coverage varies by IR office size and resources.
Training alone isn’t sufficient. Even where training exists, many leaders still rate their institutions’ data literacy as “Not Occurring” or “Reactive”. Programs are often misaligned, infrequent, or disconnected from decision moments.

Culture Eats Strategy

The AIR National Survey also points to culture as a key lever: institutions at which leaders model and reinforce data use see significantly greater employee use of information. Training can raise awareness, but culture determines whether those skills are applied consistently in day-to-day work. As Jordan Morrow argues in “Be Data Literate: The Data Literacy Skills Everyone Needs to Succeed,” a missing organizational strategy forces employees to guess, and ambiguity leads people back to old habits.

In contrast, when leaders ask for data, cite evidence, and celebrate its use, the signal is unmistakable—data matters. Such behaviors set a tone across departments, fostering a culture where using data is not just encouraged but expected.

Barriers to Progress

Across institutions, we hear a lot of the same friction points:

Capacity and coordination. Small IR/IE teams juggle compliance, reporting, ad hoc requests, and tool support. Designing a full data literacy program requires hundreds of decisions and curricula expertise.
Consistency and continuity. One-off workshops don’t shift norms. Without shared vocabulary, processes, and leadership, gains fade with turnover and competing priorities.
Evidence expectations. Accreditors and states want documented use of evidence and repeatable artifacts embedded in practice.

What Works: Elements of a Successful Data Literacy Program

AIR developed the Data Literacy Institute (DLI) in direct response to what the field has made clear: institutions face urgent expectations to build data literacy, but many lack the capacity, structures, and ready-made curricula to do so.

DLI responds directly to what the AIR National Survey shows: training, coverage and capacity, and culture matter. It equips institutions with a scalable, team-based model that overcomes the barriers institutions have identified. What’s more, it works toward building a culture of evidence so that data use becomes the way of working.

Experience across multiple cohorts has provided insight into what makes for a successful data literacy program:

Built for teams. Successful programs engage cross-functional groups rather than isolated individuals. DLI brings together up to 30 people from varied roles and units to build shared mindsets, habits, vocabulary, and relationships.
Structured for practice. Programs must connect concepts to real decision cycles, not just abstract knowledge. In DLI, participants move through a 12-week, practice-first cycle—from framing questions through use of evidence to close the loop.
Applied learning. Training sticks when tied to institutional challenges. DLI engages teams in applying concepts to real problems, culminating in a capstone project addressing a student success challenge.
Focused on momentum and credibility. Programs succeed when participants become champions of change. DLI cohorts create visible “data fellows” who guide colleagues and normalize data use in daily decisions.
Designed for sustainability. Without long-term structures, progress fades. DLI equips institutions with curriculum, pacing, facilitation guides, exercises, and assessments that can be licensed for ongoing onboarding, professional development, and accreditation cycles.
Backed by leadership sponsorship. Effective programs signal clear expectations and remove barriers. DLI engages leaders to set tone and provide visible support.
Repeated in cadence. Culture shifts when cohorts build over time into a network of champions. DLI’s cohort model is designed to be replicated, expanding internal networks of “data fellows.”

The Bottom Line

The findings on data literacy are unambiguous: training moves capability, and culture multiplies it. Higher education is moving forward, but progress is uneven, and ad hoc efforts fade. The institutions that will thrive are the ones that treat data literacy as more than a workshop or one-off professional development event—rather, as a discipline rooted in institutional values: shared language, repeatable habits, real decisions, and visible leadership.

Sherrin Get Started: Translate Intention to Lasting Practice

If you’re interested in a team-based, cross-functional, practice-first experience that reduces the burden on busy offices, builds a visible network of data fellows, AIR welcomes your inquiry. Institutions can also license the curriculum for long-term sustainability, integrating it into professional development and accreditation cycles. Reach out to start the conversation.