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Relationships between Course Taking and Teacher Self-Efficacy and Anxiety for Data-Driven Decision Making

Abstract Data-driven decision making (DDDM) involves using information gathered from and about students to make ongoing decisions about their instruction. Many teachers struggle with implementation of DDDM practices to optimize instruction, underscoring the importance of teacher education vis-à-vis DDDM. The present study secondarily analyzed existing data (N = 784) to examine both: the extent to which teachers take formal coursework related to DDDM; and the relationship between participation in such coursework and teacher self-efficacy and anxiety surrounding DDDM. Descriptive statistics suggest that most teachers are taking courses that may build their capacity for DDDM, although courses in DDDM or data use per se are among the least common. Moreover, multiple linear regression analyses indicated that participation in only stand-alone coursework in DDDM or data use is consistently associated with teacher self-efficacy for DDDM.