The New Faces of At-Risk Students: Breaking Stereotypes and Building Support 

Forty years ago, A Nation at Risk sounded the alarm on America’s education system, warning of a “rising tide of mediocrity” that threatened the country’s future. After four decades of ambitious reforms, the faces of at-risk students are far more nuanced than the rebellious troublemakers often portrayed in pop culture. Forget the leather-clad Danny Zukos, the mischievous Zack Morrises, or the charismatic Ferris Buellers. The reality is that at-risk students don’t always fit a mold, making it extremely challenging for school leaders to identify all who need more support before it’s too late. 

Understanding the Complexity of Risk Indicators 

Contrary to the binary view of dropouts versus graduates, recent research indicates that students disengage from school for a wide variety of reasons, with each reason manifesting in different constellations of risk factors that often appear well before they leave school. This means that efforts to identify students and re-engage them need to be flexible. One research study identified three distinct profiles of at-risk students, shedding light on the diverse faces behind the statistics.¹ 

A single risk factor rarely causes a student to drop out. Instead, “the likelihood that a student will drop out increases when multiple risk factors are present.”² Therefore, a composite of risk factors should be used to guide identification and intervention efforts. Factors like attendance, behavior, and course performance can be addressed through strategic interventions. These, often called the ABCs—are the most predictive indicators of high school dropout.³ 

Profiles of At-Risk Students: A New Perspective 

Some at-risk students are easily identifiable, while others show signs only in specific settings, making detection more challenging. Mr. Bailey teaches 9^th grade English language arts (ELA) and has twenty students in his first period class. Among them are Brian, Nina, and Kabree who are profiled below. Every day, Mr. Bailey records data points on each student, tracking their attendance and homework completion.  

Though the school year has only been underway for nine weeks, concerning patterns are emerging among some students. Brian is a major concern for Mr. Bailey due to various reasons. On the other hand, despite being at elevated risk, Nina and Kabree have not yet raised any red flags.  

These three students exemplify the different types of at-risk students identified by research: those who are obviously at-risk (Brian), those who are quietly at-risk (Nina), and those who are engaged but still at-risk (Kabree). 

The chart below visually summarizes the data collected on each student, with green indicating strong performance, yellow indicating borderline performance, and red indicating areas of concern. Read their stories to learn more. 

Brian: Obviously At-Risk 

The bell marking the start of class rang several minutes ago, and Brian slowly and reluctantly walks to his desk, which is directly in front Mr. Bailey’s. Mr. Bailey, who is already circulating the classroom checking for last night’s homework, expects his tardiness at this point. Still, he greets Brian and asks him to take out his homework before continuing with his rounds. Brian doesn’t have his homework today. In fact, he hasn’t completed a single assignment since school started. When Jason, who sits next to Brian asks why he was late to class, Brian shoves him causing him to fall. Brian knows that he’ll be written up again and will probably end up in in school suspension, but that might be better than sitting through another English class. 

Nina: The Quiet Achiever

As soon as she descends the bus steps, Nina rushes to her English classroom. She looks forward to chatting with Mr. Bailey, who is also the faculty advisor of her creative writing club which meets weekly after school. Sometimes, she uses the time in between bus drop off and first bell to finish her homework. Though she emigrated from Haiti four years ago, and is now a proficient English speaker, homework that is reading-heavy continues to challenge her. So, while she’s the star in Mr. Bailey’s class, subjects with lots of technical and domain-specific vocabulary, like science, challenge her beyond the point of frustration. She’s proud of the work she’s doing in English but is in danger of failing science, math, and history.  

Kabree: The Involved Student 

Kabree has been cheering since kindergarten and this year she earned a spot as a flyer on the varsity cheer team. The team practices every day after school and cheers year-round for the football and basketball teams. She refuses to miss a day of school, unless she’s too sick, because she can’t attend practice if she’s absent and loses next-day-game cheering eligibility. Her school requires student athletes to maintain a 2.0 grade point average to participate in athletics, but her coach requires a 3.0. With the support of her coach and teammates, Kabree maintains mostly A’s and B’s. A perfect storm of team and interpersonal conflict, financial stressors at home, and unrelenting social media bullying causes a series of lunchroom outbursts which led to disciplinary referrals and temporary probation from the cheer team. 

Proactive Strategies for Identifying and Supporting All Students At-Risk 

There is no mold for the at-risk student, which makes it challenging for educators to build the perfect system to identify and intervene. Any educator could guess that Brian’s behaviors are symptoms of disengagement, and if left unaddressed, his lack of connection to school may cause him to eventually dropout. However, students like Nina and Kabree who are involved, well-behaved, and engaged slip through the cracks every single day. So, what can educators do? 

By adopting these strategies, educators can more effectively monitor and support all students, ensuring that no one slips through the cracks. 

References 

1. Bowers, A. J. and Sprott, R. (2012). Why tenth graders fail to finish high school: A dropout typology and latent class analysis. Journal of Education for Students Placed at Risk, 17(3), p. 129-148. 

2. Freeman, J., Simonsen, B., McCoach, D. B., Sugai, G., Lombardi, A., Horner, R. (2015). An analysis of the relationship between implementation of school-wide positive behavior interventions and supports and high school dropout rates. The High School Journal 98(4), p. 290-315. 

3. Allensworth, E. (2013). The use of ninth-grade early warning indicators to improve Chicago schools. Journal of Education for Students Placed at Risk, 18(1), p. 68-83. 

Ellen Agnello

Ellen is a graduate assistant at the University of Connecticut. She is a former high school English language arts teacher and holds a Master’s Degree in literacy education. She is working on a dissertation toward a Ph.D. in Educational Curriculum and Instruction.