Practical Learning Analytics for Higher Education

Educational institutions generate vast amounts of data, but turning that information into actionable insights to support student success requires a structured approach. This text-only course guides you from the absolute basics of learning analytics to analyzing student engagement, predicting academic performance, and applying ethical data practices. You will learn to: • Understand the core concepts, terminology, and metrics of learning analytics in higher education. • Analyze student engagement patterns and learning behaviors using realistic educational datasets. • Apply modern data analysis techniques to identify students who may need academic support. • Explore ethical guidelines, data privacy standards, and student consent frameworks. • Design basic predictive models to forecast learning outcomes and course completion rates. • Interpret analytics reports to make informed decisions that improve instructional design. You will start with foundational definitions and privacy regulations before moving into reading code-based data analysis examples and interpreting real-world educational scenarios. This course is designed for educators, academic advisors, institutional researchers, and beginners interested in educational data science, with no prior data science experience required. Start exploring your educational data to drive student success today.