This course explores how AI is transforming the collection, analysis, and use of educational data to understand and improve learning. As digital platforms and sensor-based systems generate increasingly rich data, educators and researchers use machine learning and large language models to uncover patterns, generate insights, and support decision-making at scale. The course introduces AI methods for data analysis through three lenses: conceptual foundations for interpreting evidence, hands-on experience with AI-augmented analysis and visualization, and critical examination of ethical, institutional, and societal implications. Students work with real educational datasets to study data preparation, exploratory, predictive analysis, dashboards, and analytic sense-making, while addressing validity, bias, data rights, and responsible AI use. No prior technical background is required.
Graduate Course