How to Identify a Student in Trouble

Posted by Jeff WatsonO

December 1, 2017

Identifying which students are struggling to keep up with their peers — and why — can be a challenge. Learn how the right data solution can help change that.


As of 2015, just under 6 percent of 16- to 24-year-olds in the United States were classified as high school dropouts, meaning they had not earned a high school credential — either a diploma or an equivalency credential like a GED — and were no longer enrolled in school. While this nationwide dropout rate represents significant progress — nearly 11 percent of the same age group were dropouts in 2000 — it still means that almost two million young people across the country are starting their adult lives without completing their secondary education.


In order to further reduce dropout rates — and, more broadly, improve other important (if less critical) student outcomes like college readiness — teachers and school administrators must develop and implement processes that identify at-risk students as early and accurately as possible. An effective early warning system is key to efforts not only to assess risk, but to deploy and assess interventions designed to help struggling students get back on track, as well.


While educators typically have access to all of the data they need to pinpoint and assist at-risk students, they are often stymied by the intrinsic messiness of broad-based data collection. All of the information they need is somewhere in their district’s records; the challenge is bringing it all together and leveraging it effectively. This is made particularly difficult by the depth and breadth of student data that schools must monitor in order to reduce dropout rates and improve overall outcomes.


The Not-So-Simple ABCs


According to the U.S. Department of Education, among school districts that have early warning systems in place, 92 percent track student attendance, 91 percent track course grades, and 79 percent track serious disciplinary incidents like suspensions and expulsions. These indicators closely mirror the pillars of the “ABC” model, namely, attendance, behavior, and course performance. While certainly not the only factors that come into play — schools use, on average, six different indicators to trigger interventions for at-risk students — students who show problematic tendencies in any one of these three major categories are very frequently the ones who are in desperate need of additional services.


For instance, according to research conducted by the University of Chicago, “Freshmen who miss more than two weeks of school flunk, on average, at least two classes — no matter whether they arrive at high school with top test scores or below-average test scores.” Conversely, around 9 in 10 freshmen who miss less than a week of school each semester end up graduating, regardless of their 8th grade standardized test scores.


And, as the research makes clear, these kinds of early struggles have a direct effect on students’ future performance in high school. Indeed, “more than 95 percent of students with a B average or better in their freshman year graduate” — 80 percent with a 3.0 GPA or better. Students who average anything less than a C during their freshman year, on the other hand, are more likely to drop out than graduate.


That being said, it’s difficult to monitor comprehensive qualitative metrics like grades early on in a student’s educational journey. Fortunately, a student’s behavior — especially in elementary school, especially if it’s aggressive — often serves as an accurate predictor of their long-term success. A 2013 studyin a school district just outside the nation’s capital found that students who were suspended merely oncein first grade were five times less likely to graduate high school than their peers.


In addition to these “ABCs,” educators should consider tracking key demographic characteristics — family mobility, poverty, language-learner status, etc. — and, if possible, disruptive “life events” — teen parenthood, involvement with the justice system, time-consuming employment, etc. — as these can all influence the likelihood of an individual student not only graduating, but experiencing academic success.


The Power of an Effective Early Warning System


Integrating information about all of these risk factors can be tremendously challenging, different teachers, schools, and districts often have different methods of collecting and storing it. Fortunately, data management platforms like Hoonuit are specifically designed to streamline these processes, and can help every stakeholder keep track of the kind of critical indicators that predict when a student or group of students is at risk of a bad outcome.


In addition to simplifying data collection and organization, Hoonuit’s cutting-edge early warning solutionuses predictive analytics to examine a wide range of indicators simultaneously and uncover at-risk students who might fly under the radar of more traditional performance monitoring infrastructures.


Educators’ ultimate goal is to ensure that all of their students are on the path toward graduation — and, ideally, even bigger and better things — and implementing a platform like Hoonuit is a great way to pinpoint struggling students, figure out why they are falling behind, and deliver exactly the resources and attention they need to get back on track.


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