2025 : 4 : 21

Mohammad Ahmadi Safa

Academic rank: Professor
ORCID:
Education: PhD.
ScopusId: 57190976760
HIndex:
Faculty: Faculty of Humanities
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Phone:

Research

Title
Data use in language schools: The case of EFL teachers’ data‑driven decision making
Type
JournalPaper
Keywords
Data use · Data-driven decision making · EFL teachers
Year
2023
Journal Journal of Educational Change
DOI
Researchers ، Mohammad Ahmadi Safa

Abstract

Powered by educational policy recommendations around the world, studies on different aspects of data-driven decision making have soared both in number and scope in different educational contexts. However, despite the availability of diverse data, second or foreign language research has been quite tardy in the study of language teachers’ application of data-driven decision making. On this basis and with the aim of exploring the conditions that can lead to the teachers’ optimum use of data, this qualitative study investigated English as a Foreign Language (EFL) teachers’ data use for instructional decision making purposes. Hence, different forms of data, purposes, challenges, enablers, and barriers of data use were studied from EFL teachers’ perspective. To collect the required data, semi-structured interviews were run with 30 EFL teachers and the collected data were analyzed following the groundedtheory approach and qualitative content analysis procedure. The findings indicated that EFL teachers mainly use both formative and summative assessment results type of data. In addition, they use data for accountability and instructional purposes. Furthermore, integrating data use across the curriculum was mentioned the most among the challenges faced by EFL teachers in data-driven decision making. Considering promoting and inhibiting factors, data use for instructional purposes appears to be affected by language school organizational characteristics, EFL teachers’ characteristics, and data characteristics. The findings underscore the significance of the provision of the conditions that support data-driven decision making for second or foreign language teachers. Moreover, teacher education programs are recommended to include in-service data-driven decision making courses in their curricula.