Introduction to Learning Analytics: Data-Driven Education

Educational institutions and online learning platforms generate massive amounts of data every day. Understanding how to interpret this data is key to improving student engagement, personalizing instruction, and designing effective learning environments. This course provides a clear, step-by-step introduction to the field of learning analytics, showing you how to turn raw educational data into actionable insights. Through structured text lessons, you will transition from understanding basic data collection to exploring modern predictive modeling and student support strategies. You will gain the confidence to analyze learning behaviors and make informed, data-driven decisions that directly benefit students. What you'll learn: - Understand the core definitions, frameworks, and cycles of learning analytics - Identify and collect relevant data from modern Learning Management Systems (LMS) - Apply basic analytical methods to track student progress and engagement - Explore the fundamentals of predictive modeling to identify at-risk learners - Navigate critical ethical considerations, data privacy, and student consent - Design actionable intervention strategies based on educational data insights The course begins with foundational terminology and the historical context of learning analytics, then progresses systematically through data collection, analysis techniques, and real-world intervention design. It is specifically designed for beginners, including educators, instructional designers, and academic administrators, with no prior data science background required. Start reading today to unlock the power of educational data and transform the learning experience.