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 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 teachers. Reliability estimates were also high in both populations. Limitations and future directions are discussed.

教师数据驱动决策 (DDDM) 是当前 K-12 教育系统中非常突出的专业实践。此外，教师自我效能感和对 DDDM 的焦虑是研究和实践中的重要测量目标。因此，本研究检查了通过数据驱动的决策效能和焦虑 (3D-MEA) 清单在美国在职 ( N = 365) 和服役前 ( N ) 收集的数据的有效性、可靠性和不变性= 457) 教师。3D-MEA 旨在测量与 DDDM 相关的四个维度的自我效能，以及与 DDDM 相关的焦虑。多组验证性因素分析建立了结构测量不变性，支持在职和职前教师对 3D-MEA 分数的有意义且有效的可互换解释。这两个人群的可靠性估计也很高。讨论了限制和未来的方向。