Students with persistent behavior problems, including those with or at risk for emotional or behavioral disorders, often struggle to be self-regulated learners. To improve self-regulation skills, numerous strategies have been suggested, including goal setting. Whereas goal setting has focused mostly on academic and life skills, behavioral goal setting has received less attention, particularly in terms of determining best practices for effective goal setting in school-based interventions. Thus, the purpose of this review was to examine the existing literature on interventions using behavioral goal setting alone and behavioral goal setting as part of a multicomponent intervention for students with persistent behavior problems. Findings from 40 studies are discussed in terms of participants, setting, design, measures, intervention components, and outcomes with a specific focus on directions for future research and implications for practice.▪ The term "self-determination" has been used to describe a multitude of behaviors and beliefs that help people live independent, self-directed lives (Wehmeyer & Field, 2007). Carter, Lane, Crnobori, Bruhn, and Oakes (2011) reviewed the literature on self-determination interventions aimed at improving this broad group of metacognitive skills for students with and at risk for emotional or behavioral disorders (EBD). Interventions in their review focused on a range of skills, including making choices and decisions, problem-solving activities, goal setting, promoting self-advocacy skills, self-awareness, self-knowledge, self-assessment, and self-regulation. The most commonly studied self-determination strategy, according to their review, was self-regulation.
Technology in schools is abundant as is the call for evidence-based interventions for students who need additional support to be successful. One promising use of technology is for self-monitoring interventions aimed at improving classroom behavior. In this study, two middle school students with disabilities used a multicomponent, self-monitoring app on an iPad during their reading classes. Using a data-based individualization approach, teachers worked with the primary investigator to monitor students' response to the intervention and adapt the intervention accordingly. A single-subject design was used to test the effects of the intervention, and a functional relation was established for both participants who improved their academic engagement and decreased their disruptive behavior. Additionally, participants indicated the intervention was socially valid. Limitations, implications, and future directions are discussed.
Self-monitoring has a well-established literature base for improving the behavior of students with a range of ages and abilities. Whereas self-monitoring often involves technology for prompting self-monitoring procedures, to date, only a few studies have examined the use of technology for recording self-monitored behavior. To extend the literature in this area, the effects of technology-based self-monitoring were examined using an iPad application called SCORE IT in which students and teachers rate students' behavior and view automated graphs of progress toward goals. Using a baseline and intervention (ABAB) design to measure outcomes, improvements in behavior were established for both middle school participants-one with attention deficit hyperactivity disorder and another receiving noncategorical special education services for reading, math, and behavioral deficits. Findings, limitations, and recommendations for future research are discussed.
Self-monitoring is one of the most widely used and widely researched strategies for improving student behavior. However, specific research-based guidance about how to design effective self-monitoring interventions and to whom they should be delivered does not yet exist. To this end, we examined how various treatment components and participant characteristics moderated response to self-monitoring interventions. We included 66 single-case studies on academic engagement and 21 single-case studies on disruptive behavior. These studies included 290 participants with challenging behavior, 183 of whom had a disability. After extracting raw data from original studies, we analyzed data using multilevel modeling for each dependent variable (i.e., academic engagement, disruptive behavior). Across both dependent variables, student age and educational setting impacted treatment effects, as did the inclusion of goal-setting, feedback, and reinforcement. Based on our findings, we describe implications related to designing self-monitoring interventions. We also discuss limitations and future directions.
Multitiered frameworks like Positive Behavior Interventions and Supports (PBIS) have been recommended for preventing and remediating behavior problems. In this study, technology-based self-monitoring was used as a Tier 2 intervention to improve the academic engagement and disruptive behavior of three middle school students who were identified as at risk for failure and needing immediate intervention. Results of the multiple baseline design across settings indicated the intervention was highly effective for one student and moderately effective for another. The third student required more intense support than offered in Tier 2. Issues of matching students to Tier 2 intervention based on multiple data sources, the alignment of technology-based self-monitoring with key features of Tier 2, limitations of the study, recommendations for future research, and implications for practice are discussed.
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