Update: The tracker is live and can be accessed here.
My friend and colleague Nat Malkus, deputy director of Education Policy Studies at AEI, is about to launch the Return to Learn Tracker, a new resource for monitoring school reopenings and instructional plans across all U.S. districts with three or more schools. I spoke with Nat about what the tracker will be able to tell us about the state of school reopening and how he hopes it’ll be used, now and going forward. Here’s what he had to say.
Rick: What is the Return to Learn Tracker?
Nat: The Return to Learn Tracker (R2L) is a tool dedicated to learning how public schools across the country are responding to the COVID-19 pandemic. R2L identifies the current instructional model of all regular public school districts with three or more schools, classifying them as fully in person, fully remote, or a hybrid model. It does so by monitoring district websites each week to capture how instructional models change with fluctuating infection rates. The data collected by the tracker is combined with external data sources and presented in the R2L dashboard, allowing viewers to see overall patterns and to break them down by weekly local COVID-19 caseloads, broadband access, 2020 voting patterns, poverty, race, and a dozen or so other measures.
Rick: How is this different from what’s already out there, such as what Education Week, the CDC, or Department of Education are doing?
Nat: The R2L tracker monitors the largest number of districts on a weekly basis and presents the data by numerous variables. This makes it the most comprehensive tool for timely tracking of district instructional models. Many states collect information on their districts, but the frequency, completeness, and accuracy of those collections are all over the map. As for the Department of Education, part of the initial impetus for this tracker was to provide data that simply wasn’t there. Robin Lake, director of the Center on Reinventing Public Education, aptly captured this recently, saying, “It’s a little shocking that we haven’t had basic data on school and district status and health data.” It looks like the ED will finally be moving on this — in late January, President Biden signed an Executive Order directing the department to collect data that will help capture the impact of the pandemic on students and educators. This effort, which looks like it will be a more-detailed monthly sample survey, will be enormously helpful — and will complement the weekly data on all districts with three or more schools provided by the R2L tracker.
Rick: So, how many districts are open right now? How have those numbers changed this year?
Nat: Just over one third of districts are currently open with an option for fully in-person instruction five days per week for all students. Less than 1 in 5 districts are fully remote, except for very small groups of students targeted for in-person instruction. That leaves just below one half of districts in the hybrid category, including districts where all students have an option for in-person instruction four days a week or less or where some grades return to buildings for some in-person instruction while other grades don’t. There was a shift toward more districts only offering remote learning in the winter, in anticipation of the winter holidays and in response to surging COVID cases. Over the course of November and December, remote-only districts increased from about 20 percent districts to over one quarter of districts. Since early January, remote-only has dropped by almost one third.
Rick: What has the public narrative gotten wrong about school reopening?
Nat: A big thing is how many schools and districts are, in fact, open and how many started the year that way, something we tracked in a report released last fall. That often gets lost in the pandemic coverage, which tends to emphasize fully remote districts. Certainly, there are many districts that remained closed and where reopening was met with major resistance, but there are many that opened with sensible mitigation efforts and without the pandemic fallout many feared. I think those districts deserve attention and credit for being brave and resolute in trying times. They point the way forward.
Rick: What did this effort involve?
Nat: R2L uses novel methods for data collection involving web scraping and machine learning, so it’s taken several months to get it up and running. The first step was gathering baseline data on instructional models for the 8,400 or so districts we wanted to track. We partnered with The College Crisis Initiative at Davidson College and with MCH Strategic Data, which provided their “COVID-19 IMPACT: School District Status” data set, to assemble data that allowed us to track all 8,400 districts. We monitor changes weekly by scraping content from district websites, which basically means we automatically download new posts from every district. We use a machine-learning algorithm to flag indicators of a change in instructional model, then we comb through the relevant data to identify changes and update our time-series data. Our R2L researchers’ survey and quality-assurance work is the final step of data collection each week.
Rick: Who might find this useful, and what should they use it for?
Nat: This tracker is useful for any education leader, educator, parent, or policymaker concerned with how to best meet kids’ educational needs during this pivotal time in public education. Up-to-date, representative, and disaggregated data on schools’ instruction plans and how they change can provide the knowledge necessary to make sense of district responses to help district leaders make informed decisions about reopening. School communities can use the dashboard’s data to see how their plans compare with other districts with similar caseloads to their own and use that to inform their own decisions. And education researchers can use the data as they try to answer questions about the pandemic’s impacts on schools and students.
Rick: What are a couple of the interesting trends that you’ve noticed in the data so far?
Nat: The patterns by politics are glaring. Districts that voted for Biden are far, far more likely to have been fully remote or solidly hybrid for most of the year, and Trump districts are far more likely to be fully in person. Of course, those gaps align with other big differences by urbanicity, race, broadband access, and even mask usage, but the trends are persistent across a wide range of COVID-19 case rates. I think that highlights two things. First, attitudes and beliefs are far more powerful motivators than widely available indicators of pandemic risk. Second, there just isn’t an agreed upon method for what it means to use “the science” to assess schools’ pandemic risks. If there were, we would see clearer patterns in how case rates affect reopening. Our hope is that the R2L data might be a useful contribution to align stakeholders’ beliefs and attitudes with what we know from research and what is happening on the ground.
This interview has been edited and condensed for clarity.
This post originally appeared on Rick Hess Straight Up.