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Edmond Sebestyén: Pedagogical Data-Driven Decision-Making: Theoretical Approaches and Measures The study reviews current theories and the most important investigations of data-driven decision making (DDDM). DDDM is an approach which helps to make better decisions relating to educational actions for better teaching and learning. The theories of DDDM as well as the related concepts, data usage, data literacy and data culture are synthetized in the paper. It seems that more investigations are needed to clarify what DDDM encompasses. Both policymakers and teachers realize the need to focus on data and evidence to inform practice. DDDM helps to identify students’ knowledge gaps, make better instructional actions and to improve the quality of instruction at schools. That is why it has relevance both for educational research and practice. The paper also describes different types of measures for assessing DDDM and its related dimensions such as data literacy or affective factors of DDDM usage (like 3D-MEA). In the international literature, DDDM has been receiving more and more attention, and it is time to start a discussion about it in Hungary as well. MAGYAR PEDAGÓGIA 119. Number 4. 287-312. (2019) Levelezési cím / Address for correspondence: Sebestyén Edmond, Szegedi Tudományegyetem Neveléstudományi Doktori Iskola. H–6722 Szeged, Petőfi Sándor sgt. 30–34. |
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