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 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.

Data-based individualization (DBI) is a systematic process used to guide teachers in making decisions related to students’ responsiveness to intervention. Whereas this process has been used extensively with academic interventions, far less is known about DBI used within the context of behavioral interventions. In this study, elementary general and special education teachers (a) implemented a technology-based, self-monitoring intervention with students exhibiting challenging behavior; and (b) used DBI to evaluate student progress and make intervention adaptations accordingly. Results of multilevel modeling indicated students improved their positive behavior significantly (p < .001) from baseline to intervention. For most students, once they began intervention, positive behaviors either maintained or increased gradually when teachers made adaptations to the self-monitoring intervention. In addition to these results, an analysis of the effects of different intervention adaptations (e.g., raising or lowering goals, increasing or decreasing interval length) and visual analysis of individual students’ response 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.