What is Data-Driven Decision Making (DDDM)

This chapter examines datafication effects on educational practices. While the use of data and technology-enabled personalized learning environments increased accountability and guided educational practices and policies, it raised concerns about privacy, data quality, and potential misuse. Therefore, the reconfiguration of data use in schools involves data quality, collection, management, analysis, interpretation, visualization, integration, and literacy. Schools should make effective decisions and support student learning and educational improvement by taking a holistic and collaborative approach, involving all stakeholders and ensuring ethical and responsible use of data. The chapter makes recommendations for improving outcomes and developing a productive learning environment, including embracing a growth mindset, emphasizing student-centered decision making, fostering a culture of improvement, involving all stakeholders, using data to support learning and well-being, utilizing real-time data and feedback, leveraging technologies, and utilizing creative analysis techniques.