A Systematic Review of Data-Based Decision-Making Training for Pre-service Teachers

• In Event: Understanding Educational Practitioner Data Use

Abstract

With barriers to effective data use among teachers in making educational decisions, it is imperative to understand how data-based decision-making (DBDM) is taught during teacher preparation. Following the 2011 call by stakeholders to strengthen research on preservice training in DBDM, there has been a growing number of interventions targeting teacher candidates. This systematic review synthesized 50 studies, examining course contexts, delivery methods, data types, DBDM components, and outcomes. Results revealed wide variation in implementation, with increased emphasis on formative and process data and most interventions covering at least three of five core DBDM components. However, few studies assessed K–12 student outcomes. Findings underscore the need to align preservice DBDM training with evidence-based frameworks that foster authentic classroom data use.

Authors

• Eunji Kong, University of Oregon

• Yitong Jiang

• Wenjing Bao, University of Oregon

• Stephanie Shire, University of Oregon