Work

Validation of the Data‐Driven Decision‐Making Efficacy and Anxiety Inventory ( 3D ‐ MEA ) Among Hungarian In‐Service Teachers

Year: 2025

Type: article

Abstract: ABSTRACT The essence of data‐driven decision‐making (DDDM) is high efficacy and low perceived anxiety; therefore, numerous studies have focused on exploring these characteristics in various educational contexts. This study examined structural validity, the efficacy and anxiety characteristics of the 3D‐MEA in the Hungarian context. The significance of our research lies in the fact that the questionnaire has not been examined in a non‐US context. The paper focused on Hungarian teachers ( N = 275), whose online responses led to the conclusion that the five‐factor model of the questionnaire fits well with the Hungarian language and environment. Similar to international measurements, the Anxiety and Identification subscales produced higher values than those of the Technology, Interpretation and Application subscales. The results indicated that the questionnaire originally used in the Anglo‐Saxon culture can be translated into the Hungarian language and educational environment. This research can lay the groundwork for further international comparative studies on 3D‐MEA.

Source: European Journal of Education

DOI: 10.1111/ejed.70346

Authors: Edmond Sebestyén, Edit Tóth

Institution: University of Szeged

Language: English

Topic: Educational Assessment and Improvement

Subfield: Information Systems and Management

Field: Decision Sciences

Domain: Social Sciences

SDG: Quality education

Open Access status: hybrid

Estimated APC paid: $3,350