Handbook of Educational Data Mining

This handbook provides a thorough overview of the current state of knowledge in this area. The first part of the book includes nine surveys and tutorials on the principal data mining techniques that have been applied in education. The second part presents a set of 25 case studies that give a rich overview of the problems that EDM has addressed. With contributions by well-known researchers from a variety of fields, the book reflects the multidisciplinary nature of the EDM community. It helps education experts understand what types of questions EDM can address and helps data miners understand what types of questions are important to educational design and educational decision making.

Cristobal Romero is an associate professor in the Department of Computer Science at the University of Cordoba in Spain. Dr. Romero is a member of the International Working Group on Educational Data Mining and was conference co-chair of the Second International Conference on Educational Data Mining. His research interests include the application of artificial intelligence and data mining techniques to education and e-learning systems. Sebastian Ventura is an associate professor in the Department of Computer Science at the University of Cordoba in Spain. Dr. Ventura has been a reviewer for User Modelling and User Adapted Interaction, Information Sciences, and Soft Computing and was conference co-chair of the Second International Conference on Educational Data Mining. His research interests encompass machine learning, data mining, and their applications as well as the application of KDD techniques to e-learning. Mykola Pechenizkiy is an assistant professor in the Department of Computer Science at Eindhoven University of Technology in the Netherlands. Dr. Pechenizkiy has been involved in the organization of workshops, special tracks, and conferences on applications of data mining in medicine, industry, and education. He is conference co-chair of the Fourth International Conference on Educational Data Mining. His research is focused on knowledge discovery, data mining, machine learning, and their applications. Ryan Baker is an assistant professor of psychology and the learning sciences in the Department of Social Science and Policy Studies, with a collaborative appointment in computer science, at Worcester Polytechnic Institute in Massachusetts. An associate editor of the Journal of Educational Data Mining, Dr. Baker was program co-chair of the First International Conference on Educational Data Mining and conference chair of the Third Interna

Preface. Introduction. Basic Techniques, Surveys, and Tutorials. Case Studies. Index.

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