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Data-driven decision making as a model to improve in primary education

Author

Listed:
  • Athanatou Maria
  • Prendes Espinosa Maria Paz
  • Gutierrez Porlan Isabel

Abstract

The digital evaluation field is a new area that arises in the core of education and studies highlight the importance of editing data as well as using ICT to drive internal school improvement. Data- Driven Decision Making (DDDM in advance) executes relatively simple models on carefully targeted data extracted through target questionnaires. This article contributes to the creation of a DDDM plan that considers the evaluation of a primary school in Greece. The research design is based on the DigCompOrg model and uses a quantitative technique through a questionnaire. The results presented include the analysis of the teaching team. Extracted data enabled the researchers to identify the requirements that the specific school must meet in order to proceed with self-evaluation in its digitalization process. The percentage results for teachers’ self-perception of ICT use in lessons, teachers’ digital competence, digital content use, pedagogical evaluation, digital communication with parents and digital support of school leadership indicated that significant changes in ICT integration continue to occur in the specific primary school, ICT culture and most of its components. For these reasons, this article presents a proposal for a DDDM theoretical model plan for primary school improvement presented at the end.

Suggested Citation

  • Athanatou Maria & Prendes Espinosa Maria Paz & Gutierrez Porlan Isabel, 2023. "Data-driven decision making as a model to improve in primary education," Journal of Education and e-Learning Research, Asian Online Journal Publishing Group, vol. 10(1), pages 36-42.
  • Handle: RePEc:aoj:jeelre:v:10:y:2023:i:1:p:36-42:id:4337
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