![]() While it is reasonable that these two problems attracted a lot of attention, learning analytics are far more powerful. Historically, some of the most common uses of learning analytics is prediction of student academic success, and more specifically, the identification of students who are at risk of failing a course or dropping out of their studies. Learning Analytics builds on these well established disciplines, but seeks to exploit the new opportunities once we capture new forms of digital data from students’ learning activity, and use computational analysis techniques from data science and AI. ![]() SO WHAT’S ALL THE FUSS ABOUT? People have been researching learning and teaching, tracking student progress, analysing school or university data, designing assessments and using evidence to improve teaching and learning for a long time. usability, participatory design, sociotechnical systems thinking). ![]() ![]() statistics, visualization, computer/data sciences, artificial intelligence), and Human-Centered Design (e.g. educational research, learning and assessment sciences, educational technology), Analytics (e.g. As a research and teaching field, Learning Analytics sits at the convergence of Learning (e.g. Learning analytics is both an academic field and commercial marketplace which have taken rapid shape over the last decade. LEARNING ANALYTICS is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs, as defined back in 2011 for the first LAK, this general definition still holds true even as the field has grown.
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