Marguerite Roza and Chad Aldeman
Published October 5, 2022 on The Hill
Last month, the U.S. Department of Education launched an effort to address teacher shortages. Secretary Miguel Cardona went on national TV to call attention to the school staffing crisis and announce the initiative. But is there a national staffing crisis? Are vacancies higher than normal? If so, in what subjects and in which schools?
The truth is no one knows. There is no useful teacher labor data in U.S. schools. Some local leaders, and a few reporters, have tracked down the number of job openings in their communities, but the Education Department doesn’t have large-scale data on the issue, and most states don’t, either. Some analysts and writers suggest there is no shortage.
The absence of data is not unique to the teacher labor market. In public education, we lack timely information on what should be the most basic of metrics. Good luck getting real-time data on how many children are enrolled in public schools, are chronically absent, or are making academic progress as a result of federally funded relief efforts. We don’t have it on a national level. States don’t have it. Neither do most districts.
The dearth of data in education is reaching four-alarm status. This fall, after three pandemic-affected school years, there is little to no data on which interventions are working to get which students up to speed in what subjects.
Schools need data to guide how they spend their massive federal relief funds to get students back on track. Making decisions without data means that we invest in programs but don’t change course if they’re not working. It means we have no idea if the fleet of newly hired counselors has any effect on mental health. It means instead of targeting remedial fractions to students who need it, we either re-teach fractions to everyone or to no one.
Data-free schooling means the system can’t learn as it goes and improve on what it does. It means students aren’t getting the full value from the nation’s investment in public schooling.
Why has public education missed out on the data revolution that transformed so many other industries over the past few decades? Hours after stores close on Black Friday, news reports blast out the latest sales trends. And yet, during the pandemic, states couldn’t even say which of their schools were closed or open and, if they had remote learning in effect, how many students were attending.
In contrast to other sectors, education seems to be allergic to data. We don’t get the macro numbers, nor are we willing to gather localized data on how students are doing.
To be clear, this isn’t a call for more standardized testing. In fact, some of the resistance to data may be a reaction to earlier accountability-focused efforts that felt more punitive than constructive. At issue here is data that’s useful for teachers, parents and students so they can do their part to drive improvement. In one survey, more than half of students report not receiving any regular data on their learning, or on whether they’re on track to graduate — information they want and need so they, too, can participate in ways that yield progress.
In other sectors, leaders are obsessed with gathering data from their users and processes so they can get better at what they do. Often, data is scooped up as part of the production and delivery process. The Square credit card reader, for example, assembles information on each and every purchase at a neighborhood bakery so the owner can better understand the sale of scones to analyze patterns by days of the week or months of the year.
We need data collection processes that allow schools to gather information — in real time — on how kids are doing. For example, learning platforms such as Zearn could tell us in the early months of the pandemic, without any additional testing, the harmful effect that remote learning was having on kids’ math progress, especially for the poorest students. It took two years for the system to uncover the devastating impacts that the digital tools surfaced nearly immediately.
States, districts, schools and classrooms should be hoovering up data just as eagerly as the neighborhood bakery. But most have not bought into the idea that data generated by digital tools can help in the learning process. Some of the resistance stems from a fear of viewing kids as widgets; schooling is different, more human, than other sectors. But is it?
Consider the parallels between academic goals and fitness goals. Both take motivation and sustained hard work over time. Apps such as DuoLingo and Peloton have used data to figure out what kinds of things work and provide customized feedback to keep individuals motivated and making progress.
Here’s one way to chip away at this data desert: State education agencies can use a share of the nearly $20 billion they got in relief funds to create real-time reporting systems to track daily student attendance, monthly learning, real-time labor trends by role and location, and much more.
Next, the Department of Education must do more to generate timely data that can inform today’s decisions, including the secretary’s initiative on teacher shortages. The new Pulse Survey is good progress. But most of the federal financial data, including on relief funds, is inadequate or woefully behind.
It will take commitment at every level for public education to join the data revolution. This generation of students especially depends on our figuring out which investments will help them recover and get back on track.
Why has public education missed out on the data revolution that transformed so many other industries over the past few decades? And what can be done to chip away at this data desert?
On October 12, Edunomics Lab hosted a panel discussion with Mark Schneider, Director of IES, Shalinee Sharma from Zearn, Kaya Henderson from Reconstruction and the former Chancellor of DC Public Schools, and Nat Malkus from the American Enterprise Institute. They shared ideas for moving education forward by making data more accessible, actionable, and timely.
