The implementation of prereferral models was being discussed in educational literature as early as 1979. Over the past decade, schools in the United States have begun to adopt prereferral models to meet multiple goals, such as reducing inappropriate referrals to special education, supporting students who face academic and behavioral challenges,…

Early warning systems (EWS) using analytical tools that have been trained against prior years' data, can reliably predict dropout risk in individual students so that educators may intervene early to help avert this from happening. Risk profiles for dropouts aren't always useful since students often do not conform to the profiles. Researchers with…

Colleges are increasingly turning to predictive analytics to identify "at-risk" students in order to target additional supports. While recent research demonstrates that the types of prediction models in use are reasonably accurate at identifying students who will eventually succeed or not, there are several other considerations for the…

Recent data from statewide assessments, scores on the National Assessment of Educational Progress (NAEP), and college remediation needs show that an increasing number of K-12 students are not performing at grade level. As schools look to support these students' learning, some districts are turning to a proven strategy for identifying the students…

Recent advocacy efforts and state policies have recognized the identification of and support for students with dyslexia as a critical issue for schools. Current issues related to dyslexia identification include the lack of a universal definition for dyslexia and the possible confusion created by state legislation related to dyslexia. Tackling…

Twice-exceptional (2e) students are a unique group at risk for social/emotional difficulties and disenfranchisement in schools. These students' profiles combine giftedness with areas of struggle such as learning disabilities, social impairments, emotional and mental health issues, or behavioural problems. Supporting 2e students requires developing…

Inefficient targeting of students at risk of dropping out might explain why dropout-reducing efforts often have no or mixed effects. In this study, we present a new method which uses a series of machine learning algorithms to efficiently identify students at risk and makes the sensitivity/precision trade-off inherent in targeting students for…

Students with both academic and behavioral risk factors can benefit from participation in self-regulated strategy development (SRSD) instruction. Educators can use systematic screening procedures as part of effective data-informed decision making for identifying students who could benefit from SRSD. In this manuscript we detail screening…

The collection of student data through screening and progress monitoring of social and emotional learning (SEL) skills is just as important as the implementation of curriculum and practices. Monitoring skill acquisition allows teachers to identify effective practices, provide intervention, and intensify support for students who need it. In this…

There have been substantial advances in the development of states' education data systems over the past 20 years, supported by large investments from the federal government. However, the availability of modern data systems has not translated into meaningful improvements in how consequential state policies, such as funding and accountability…

Considerable attention and legislation are currently focused on developmental dyslexia. A major challenge to these efforts is how to define and operationalize dyslexia. In this article, we argue that rather than defining dyslexia on the basis of an underlying condition, dyslexia is best viewed as a label for an unexpected reading disability. This…

Classification accuracy is a key characteristic of screening tools. A goal in classification accuracy is to correctly identify issues that result in a later problem and situations in which the scores identify issues that do not result in a later problem.

The science of reading should be informed by an evolving evidence base built upon the scientific method. Decades of basic research and randomized controlled trials of interventions and instructional routines have formed a substantial evidence base to guide best practices in reading instruction, reading intervention, and the early identification of…

Schools have an important role to play in adolescent suicide prevention. This article describes universal screenings for depression and suicidality as one component of the Signs of Suicide (SOS) program in middle and high schools following the suicide death of a student in the past few years. Of the students screened (N = 7,429), 11.0 percent of…

There is growing evidence of an escalation of depression in young people. In light of this, schools are increasingly being confronted with the challenge of how to best manage students with depressive disorders. Such management includes consideration of the academic, behavioural, social and emotional implications of the disorder. This article…