Resumen de Data-based decision-making in schools: Examining the process and effects of teacher support
Karin Hebbecker, Natalie Foster, Boris Forthmann, Elmar Souvignier
The idea of data-based decision-making (DBDM) at the classroom level is that teachers use assessment data to adapt their instruction to students’ individual needs and thus improve students’ learning progress. In this study, we first investigate this theoretically assumed DBDM process, and second, we evaluate the effectiveness of teacher support on the different steps of this process. Using longitudinal data of N = 120 teachers and their N = 2458 students, we analyzed the relations between teachers’ log-file-based data analysis activities, teachers’ self-reported frequency of instructional decision-making, and students’ learning progress in reading by means of latent mediation analyses. Moreover, we analyzed whether additional teacher support in the form of instructional recommendations, teacher training, and prepared teaching material can promote the implementation of different steps of DBDM. Results of latent mediation analyses revealed positive associations of teachers’ data analysis with their instructional decision-making and students’ learning progress. Teacher support was positively associated with data analysis and students’ learning progress (mediated by data analysis). Results are discussed regarding the theoretically assumed steps in the DBDM process and the potential of teacher support with a focus on teachers’ instructional decision-making. (PsycInfo Database Record (c) 2022 APA, all rights reserved)
