Titlebook: Learning Analytics; From Research to Pra Johann Ari Larusson,Brandon White Book 2014 Springer Science+Business Media New York 2014 Data Min

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Introduction,ide all members of an educational community with a window into what actually takes place over the trajectory of a student’s learning. This chapter provides an introduction to the volume more generally, which attempts to provide an entry point into the field by showcasing the latest results, strategi

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Designing Learning Analytics Experiencesrring in a learning experience is now a reality. Learning analytics is the discipline that uses this data to improve the overall effectiveness of the learning experience. The use of learning analytics can be divided into five stages: collect, analyze, predict, act, and refine. In this chapter an ana

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Harnessing the Currents of the Digital Oceanhat can be immediately collected, modified, moved, stored, and computed upon. This shift has already had remarkable social consequences and raises fundamental questions regarding the nature of science and knowledge. In the context of educational research, it raises key questions about the nature of

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Educational Data Mining and Learning Analytics Educational Data Mining and Learning Analytics. This article discusses the relationship between these two communities, and the key methods and approaches of educational data mining. The article discusses how these methods emerged in the early days of research in this area, which methods have seen p

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A Learning Management System-Based Early Warning System for Academic Advising in Undergraduate Enging near real-time data from a university’s learning management system, we provided academic advisors with timely and targeted data on students’ academic progress. We discuss the development of the early warning system and detail how academic advisors used it. Our findings point to the value of provid