"Learning Analytics in Higher Education provides a foundational understanding of how learning analytics is defined, what barriers and opportunities exist, and how it can be used to improve practice, including strategic planning, course development, teaching pedagogy, and student assessment. Well-known contributors provide empirical, theoretical, and practical perspectives on the current use and future potential of learning analytics for ..."
"Learning analytics (or educational big data) tools are increasingly being deployed on campuses to improve student performance, retention and completion, especially when those metrics are tied to funding. Providing personalized, real-time, actionable feedback through mining and analysis of large data sets, learning analytics can illuminate trends and predict future outcomes. While promising, there is limited and mixed empirical evidence ..."
"This SpringerBrief covers the technical material related to large scale hierarchical classification (LSHC). HC is an important machine learning problem that has been researched and explored extensively in the past few years. In this book, the authors provide a comprehensive overview of various state-of-the-art existing methods and algorithms that were developed to solve the HC problem in large scale domains. Several challenges faced by ..."