Validation of the Data-Driven Decision-Making Efficacy and Anxiety Inventory (3D-MEA) With U.S. Preservice Teachers

• In Event: Marriott Roundtable Session 30
  In Roundtable Session: Data Quality and Equity Implications for Data Use Practice

Abstract

Sound measurement of teacher self-efficacy for data-driven decision making is crucial in both theory-building and efficacy studies. The present study (N=457) examines the validity of inferences drawn from the Data-Driven Decision-Making Efficacy and Anxiety Inventory (3D-MEA; Dunn, Airola, Lo, & Garrison, 2013) among U.S. pre-service teachers, a population with whom the instrument has never been fully and rigorously validated. Findings indicate good fit of the hypothesized five-factor confirmatory factor model and acceptable reliability in this population. This validity and reliability evidence implies that the 3D-MEA may be used meaningfully with U.S. pre-service teachers.

Authors

• Todd Reeves, Northern Illinois University

• Yasemin Onder, Northern Illinois University

• Beheshteh Abdi, Northern Illinois University