A guide to data-based decision making for behavioral coaches

As schools implement multi-tiered systems of support for behavior, they often rely on behavioral coaches to support teachers in initiating new behavioral support strategies or increasing their fidelity to current practices. Data-based decision making (DBDM) holds promise as a method for behavioral coaches to identify teachers in need of support and subsequently evaluate teachers’ responses to research-based training and coaching practices. This article adapts recommendations from student-level DBDM models to propose a three-stage DBDM model for behavioral coaches interested in teacher-level data to guide their coaching activities: (1) Identify, (2) Monitor, and (3) Refine. Application of the DBDM process to behavioral coaching is described, examples of measurement tools for use across the DBDM phases are provided, and contextual factors are discussed.