Catching students before their absences become chronic could be as simple as looking at past patterns, says one researcher who has developed a new tool that allows districts to analyze kids’ risk of missing too much class time—before the school year even starts.
Research has shown that schools can combat chronic absenteeism—defined as missing at least 10% of school days—when they are proactive with communication about attendance expectations, empathetic to families’ struggles, and start intervening before too many absences pile up.
Now, a new tool forecasts students’ likelihood of becoming chronically absent at the start of the school year, based on past years’ attendance data that most districts already have on hand.
The new Absence Forecast, created by researchers at the American Enterprise Institute who collect district- and state-level absence data, allows districts to input students’ past-year attendance records for each month and other information, such as the number of absences they have so far in the current school year, their grade level, and whether they are eligible for free and reduced-price lunches. In response, the tool spits out a prediction of how likely it is that the student will become chronically absent on a scale of 0-100%.
“We don’t want you to have to be a researcher to use this—we want you to be a district leader who could gather the data and get answers easily,” said Nat Malkus, one of the developers of the tool and deputy director of education policy studies at AEI, a right-leaning think tank. “A lot of schools and districts are just not aware that they can act earlier—that they have the information, they have the data they can act on right out of the gate.”
Absenteeism is a problem that’s been top of mind for school districts in recent years. Nationally, chronic absenteeism peaked at about 28% in the 2021-22 school year, according to data from the Return to Learn tracker maintained by AEI. Of the 41 states that have reported data from 2024-25, 34 have shown declining rates of chronic absenteeism, but none have returned to pre-pandemic levels, according to the tracker.
The Absence Forecast isn’t the first tool of its kind, but Malkus said AEI is one of a few to develop an early-warning system that has been rigorously tested and is free for districts to use.
AEI first developed two separate tools to test the model’s accuracy in different states—Indiana and Rhode Island.
In tests, the model correctly predicted whether students would become chronically absent 88-92% of the time, according to a report from AEI issued as part of the tool’s launch. The models developed for each state showed similar accuracy when researchers entered the other state’s data into the tool, as well.
In other words, the models designed for a specific state worked for other states, too, regardless of differences in student populations, geography, and other factors. In testing, they were also similarly accurate in predicting chronic absenteeism that happened both before and after the pandemic, despite major changes to attendance patterns during the pandemic.
Based on those pilots, AEI then developed its universal tool that schools or districts in any state can use.
“If you’re just using current-year data, you’ve got to wait until October before you have any inkling of who’s got a problem. Our whole point with this thing is you don’t actually have to wait,” Malkus said. “If you want to target absenteeism, let’s target it before they have absences, when we can actually break the cycle.”
To ensure students’ and schools’ data are safe, the Absence Forecast was designed so information is not uploaded to external servers, according to the AEI report. Instead, the data is uploaded into the user’s own computer’s memory within an online browser, and the data is processed on the person’s own computer. Alternatively, the tool is available as a downloadable application that works fully offline.
Districts can use the predictions and data to provide families resources and check in at the beginning of the school year about the importance of attendance, and can use it throughout the year to monitor students’ absences and track whether interventions they’ve used are working, driving down their risk of chronic absenteeism.
“An unsuccessful intervention, or a student’s worsening attendance, will see those predicted risks tend to go up, signaling to districts that they should follow up with and reengage students,” the report said. “On the other hand, for successful interventions or a student’s improved attendance, the Absence Forecast will likely show a noticeable drop in a student’s risk of becoming chronically absent.”
With these data in hand, Malkus said he hopes “districts can walk away with more information to keep up the fight against chronic absenteeism.”
