While behavioral data are important, they are useless if teachers do not know how to interpret the data and make subsequent intervention decisions. In other words, without support or training in the data-based decision-making process, the teacher may be left "data rich, but information poor" (Wayman, 2005). To improve the decision-making process for general and special education teachers implementing technology-based self-monitoring interventions for students with challenging behaviors, we trained teachers to use data collected within a mobile intervention app to make decisions about student responsiveness. In this presentation, we will present a framework for guiding data-based decision making in behavioral interventions, ways technology can improve this framework, and findings from a professional development series on this data-based framework. Findings will focus on outcomes for students with challenging behavior and teachers' perceptions of usability and feasibility.