A Single-Case Study of a Self-Monitoring Intervention for High School Students

Students with high incidence disabilities who display elevated levels of externalizing behaviors are more likely to obtain lower grades, less likely to pass classes, and less likely to have positive peer and adult relationships compared to their peers with and without disabilities (Lane, Barton-Arwood, Nelson, & Wehby, 2008; Maggin, Wehby, & Gilmour, 2016). Furthermore, students who display elevated levels of externalizing behaviors are likely to display actions that negatively affect both their academic and behavioral outcomes in the classroom (Maggin et al., 2016). Teachers are expected to deliver evidence-based interventions in their classrooms to improve these outcomes (Every Student Succeeds Act, 2015), but teachers cite high-frequency, low-intensity disruptive behavior as an ongoing challenge, and they can struggle to deliver evidence-based behavioral interventions in their classrooms (Barrett, Eber, & Weist, 2013; Busacca, Anderson, & Moore, 2015; Wehby & Kern, 2014). Self-monitoring is an evidence-based intervention that has over 40 years of research demonstrating effectiveness at improving on-task behavior and decreasing disruptive behavior for students with high incidence disabilities who also display elevated levels of externalizing behaviors (e.g., Dooley, 2018; Vogelgesang, Bruhn, Coghill-Behrends, Kern, & Troughton, 2016). At its core, self-monitoring involves students observing and recording their behavior at regular intervals, and self-monitoring interventions often include additional components, such as adult feedback, graphing, technology, and contingent reinforcement (Bruhn, McDaniel, & Kreigh, 2015). Although there is sufficient research to identify self-monitoring as an evidence-based intervention (Busacca et al., 2015; Maggin, Briesch, & Chafouleas, 2013), researchers have most often implemented self-monitoring interventions with students in grades K-8, and there is a paucity of research on the efficacy of self-monitoring for high school students with high incidence disabilities. The purpose of this study was to examine whether an electronic (MoBeGo) self-monitoring intervention was effective for high school students with high incidence disabilities who also displayed elevated levels of externalizing behavior. In this study, I recruited two general education high school teachers who taught students with individualized education programs for high incidence disabilities who also displayed elevated levels of externalizing behaviors at school. To identify students who met the inclusion criteria, the two teachers nominated students and then completed the Strengths and Difficulties Questionnaire (SDQ; Goodman, 1997) to assess whether the students displayed the externalizing behavior in class. I then conducted two direct observations to confirm that the nominated students displayed the behaviors in class. A total of four high school students with high incidence disabilities met the inclusion criteria and participated in this study, and I implemented a single-case withdrawal (ABAB) research design with each student to assess the functional relation between the electronic (MoBeGo) self-monitoring intervention, and the dependent variables of academic engagement and respectful behavior. To collect data on the dependent variables, I conducted direct observations utilizing momentary time sampling at 15-second intervals for the duration of a class period. In the baseline and withdrawal phases (A), the student participants received the same classroom management strategies the teacher had used throughout the school year. In the intervention (B) phases, the students used the electronic (MoBeGo) self-monitoring application. MoBeGo was chosen to deliver the self-monitoring intervention because it has demonstrated positive effects in elementary and middle schools, and automatically incorporated goal setting and graphing in a digital format that did not require additional work from the teacher or students. Teachers met briefly with each student at the end of each class to review the results and discuss the student’s performance. I conducted a formative visual analysis within the phases of the study to monitor the students’ performance and inform my decisions related to changing phases. The goal of the intervention was for students to improve the frequency with which they displayed academic engagement and respectful behavior by 10% from the baseline phase, and the participants were not eligible change phases until they had achieved goal and data were stable. I conducted summative visual analysis at the conclusion of the study to determine whether there was a functional relation between the electronic (MoBeGo) self-monitoring intervention and the dependent variables, and I also calculated effect sizes to analyze the degree of the change in the dependent variables. The visual analysis indicated that there was a functional relation between the intervention and the dependent variables of academic engagement and respectful behavior for three participants. A functional relation could not be determined for the fourth participant due to insufficient data in the final intervention phase. The results of the effect size analysis suggested that the intervention had a large effect on both dependent variables. Furthermore, the teachers and students were able to implement the intervention with fidelity and identified it as a socially valid intervention.