Do Data-Driven Decision-Making Efficacy and Anxiety (3D-MEA) Inventory Scores Mean the Same Thing for Preservice and In-Service Teachers?

• In Event: New Pathways: Breaking Ground on Pioneering Data Use Practices for Education

Abstract

Teacher data-driven decision making (DDDM) is a professional practice of great prominence in the current K-12 education system. Moreover, teacher self-efficacy and anxiety around DDDM represent important measurement targets in both research and practice. This study consequently examined the validity, reliability, and measurement invariance of data collected via the Data-Driven Decision-Making Efficacy and Anxiety (3D-MEA) Inventory among U.S. in-service (N=365) and pre-service (N=457) teachers. The 3D-MEA is intended to measure four dimensions of self-efficacy related to DDDM, as well as anxiety related to DDDM. Multi-group confirmatory factor analyses established structural measurement invariance, which supports meaningful and effectively interchangeable interpretation of 3D-MEA scores with both in-service and pre-service teacher populations. Reliability estimates were also high in both populations.

Authors

• Valerie Hamilton, Eastern University

• Yasemin Onder, Northern Illinois University

• Natalie Andzik, Northern Illinois University

• Todd Reeves, Northern Illinois University