Datainformed Leadership A Guide to AIEnabled Data Science Across Education Systems

Data can transform education, but only when it is interpreted responsibly and turned into meaningful action. This work demystifies analytics for anyone seeking to improve teaching, learning, leadership, and institutional performance while safeguarding professional judgement, fairness, privacy, and the interests of every individual learner. The book guides teachers, school leaders, researchers, and decision-makers through the complete journey from data collection and governance to visualisation, interpretation, communication, and sustained improvement. Accessible chapters introduce data literacy, quality, ethics, regression, clustering, classification, forecasting, spatial analysis, and educational data mining. Practical examples, case studies, decision frameworks, and visual models demonstrate applications in instructional design, student support, assessment, institutional planning, and school leadership. Dedicated coverage of generative and agentic artificial intelligence explores emerging opportunities alongside concerns about assessment integrity, surveillance, bias, transparency, and accountability, enabling readers to evaluate both established analytical methods and rapidly developing technologies confidently and responsibly. Distinctively human-centred, this book treats analytics not as a substitute for educators’ expertise, but as a disciplined companion to contextual knowledge and stakeholder voice. It equips readers to ask better questions, challenge misleading claims, communicate uncertainty honestly, and transform evidence into ethical, equitable, and sustainable educational action for every learner.