Earlier this month, schools and communities across the country celebrated Teacher Appreciation Day to recognize the work of teachers, one of the largest occupations in the U.S. workforce and, arguably, one of the most consequential for the long-term progress of our nation. Yet even as we celebrate this workforce, we are still far from understanding it in a coherent way: where teachers are needed, how they move into and through the profession, and how preparation pathways connect to workforce outcomes.
A recent national scan of teacher workforce data systems by researchers Paul Bruno (University of Illinois at Urbana Champaign) and Tuan Nguyen (University of Missouri), in partnership with Craft, highlights just how fragmented that understanding remains. Drs. Bruno and Nguyen examined what data states collect, what they make public, and how. What emerged was not just a story of gaps, but of fragmentation across agencies, definitions, and the teacher pipeline itself. This disjointedness has real consequences for our ability to diagnose workforce challenges, evaluate teacher preparation pathways, and design proactive policies to address the greatest needs.
Here are the main insights our team at Craft Education took away from their report.
Insight 1: Fragmentation is structural.
Systems that track teacher preparation and those that track teachers in the workforce were built separately. As a result, they operate independently, and in most cases, this prevents answering fundamental questions such as: “Which programs produce teachers who stay?” This is true even in states that have made strides in creating teacher data systems. In other states, these systems have only been minimally developed or are not yet fully operational. This degree of fragmentation—with many states not providing basic data, and even states with working data systems struggling to connect their systems—means answering even the most basic questions about the workforce consistently across states is not possible. The disconnect between teacher preparation and teacher workforce data systems reflects a deeper institutional divide between higher education and K-12.
Insight 2: Vacancies are one key signal to the health of the teacher workforce, and also the most underdeveloped one.
As mentioned in another Craft Insights blog, few states know the extent and distribution of their teacher shortages, even though they affect many regions and subject areas across the United States. Although the number of vacancies is the closest proxy to actual shortages a state or district could track, they are one of the weakest parts of the system. Very few states report vacancies, and when they do, data are often aggregated or hard to access. This is not surprising, since data systems are developed to track what exists, not what is missing. Vacancies are also difficult to define. For example, is a classroom staffed by a long-term substitute actually filled, or does that constitute a vacancy? Therefore, vacancies are not typically collected in standard systems. The metric that policymakers most want is conceptually and operationally difficult.
Insight 3: Definitions are the hidden barrier to advancing coherent data systems across states.
The challenge to state teacher workforce data systems is not just missing data; it is non-comparable data. The report highlights that states define key concepts differently, such as turnover, leaving, and underqualification. In other cases, definitions are unclear or inconsistently applied. Turnover, for example, could include multiple distinct categories such as teachers who exit the profession entirely, move to another school, or switch to a non-teaching role. Different states group these differently, report only on some of them, or don’t define clearly what “turnover” includes. This is not just a technical issue. It limits, in practice, cross-state learning and cumulative research.
Insight 4: Accessibility shapes who can use the data
The authors examine not only the publicly available evidence of data collection, but also whether states make the data available for download, or if they produce some basic analytics with it via dashboards. This distinction matters because the way data are presented determines whether and how they can inform decisions. While most states have a teacher workforce dashboard, the amount of information these dashboards convey varies substantially from state to state. And though dashboards increase accessibility and can help attract attention, downloadable data are what enable deeper analysis and allow users to combine data across sources. Visibility without usability limits the value of even well collected data.
Insight 5: Granularity impacts usefulness
The authors also note at what level the data they find are disaggregated. This is important because, while state-level data provide a general sense of the magnitude of a problem, they do not allow for accurate diagnoses of regional disparities, like localized or subject-specific shortages. They also fail to surface inequities across schools, districts, and regions. The authors find that most of the data are reported at the state level, with limited availability at the district or school level. Teacher labor markets are local and subject-specific. Aggregate data obscure the problem and limit their ability to guide action.
What exemplar states reveal—or don’t
A small number of states demonstrate that more comprehensive and accessible workforce data systems are possible. States like Illinois and Pennsylvania have built systems that showcase multiple measures of the teacher workforce, such as vacancies, turnover, and underqualification. They make them available at more granular levels, sometimes down to districts and schools. These systems often combine interactive dashboards with downloadable datasets, allowing policymakers and researchers to engage with the data in different ways. They also tend to provide clearer definitions of key metrics, making the data easier to interpret and use.
At the same time, even these stronger examples highlight the limits of current approaches. In many cases, data are still distributed across multiple platforms or tools rather than integrated into a single, coherent system. And, crucially, while they provide better visibility into parts of the workforce, they do not fully bridge the divide between data on teacher preparation and active members of the teacher workforce. In that sense, these exemplars demonstrate what’s possible and how far the field still has to go.
From visibility to understanding
Taken together, these findings suggest that the challenge facing the field is not just one of data availability, but rather of system design. Fragmented data systems, inconsistent definitions, limited accessibility, and insufficient granularity all contribute to a partial and potentially misleading view of the teacher workforce. Where data exist, they often can’t be connected in ways that allow for a meaningful analysis of how teacher candidates move through the profession. As a result, decisions about recruitment, preparation, and workforce investment are made without a clear and consistent understanding of the underlying dynamics. If we want to get serious about strengthening the teacher workforce, we need to move towards coherent and connected systems of information. Without that, even high-quality data will continue to produce only a limited view of the workforce we’re trying to grow and support.
