Promoting teacher knowledge and self-efficacy for data-based decision-making: Dimensional structure, sensitivity to professional development, and relationships with teachers’ intended data use

Teachers’ knowledge and self-efficacy are key to successful data-based decision-making (DBDM). Teachers are expected to gain professional knowledge and become more self-efficacious in DBDM from various learning opportunities, including professional development (PD). However, research on DBDM often focuses on subjectively perceived knowledge, both as an indicator of (objective) professional knowledge and as an indicator of the motivational belief of self-efficacy. This raises questions on the structural validity of objective knowledge, subjective knowledge, and self-efficacy. Moreover, it is unclear whether these constructs are differentially sensitive to PD on DBDM and to what extent they predict specific proportions of variance in teachers’ intended data use. The present study reports findings from a pre-post waitlist control field trial with 116 German primary and secondary school teachers who participated in a four-week blended-learning PD on DBDM. Results indicate that objective knowledge, subjective knowledge, and self-efficacy represent empirically distinct constructs. While we observed PD effects on all three constructs in separate models, PD effects remained significant only for subjective knowledge when controlling for each other and for pretest values in a three-dimensional model. At the same time, self-efficacy of teachers in the intervention group gained from participating in the PD predicted their intention to use data in future teaching, while this was not the case for objective and subjective knowledge when controlling for each other. Our findings suggest differentiating between objective knowledge, subjective knowledge, and self-efficacy when designing and evaluating PD on DBDM and contribute to the construct validation of teacher knowledge and self-efficacy.