Handbook of Educational Data Mining

Romero, Cristobal (Editor)/ Ventura, Sebastian (Editor)/ Viola, Silvia Rita (Editor)/ Pechenizkiy, Mykola (Editor)/ Baker, Ryan (Editor)

ISBN 10: 1439804575 / ISBN 13: 9781439804575

Edité par CRC Pr I Llc, 2010

A propos de cet article

1st edition. 448 pages. 10.31x7.28x1.30 inches. In Stock. N° de réf. du vendeur __1439804575

Détails bibliographiques

Titre : Handbook of Educational Data Mining

Éditeur : CRC Pr I Llc

Date d'édition : 2010

Reliure : Hardcover

Etat : Brand New

A propos de ce titre

Synopsis :

Educational data mining (EDM) is an emerging discipline concerned with developing methods for exploring the unique types of data that come from an educational context. Given the widespread use of e-learning and the vast amount of data accumulated recently, researchers in various fields have begun to investigate data mining methods to improve e-learning systems. This book presents state-of-the-art applications of data mining techniques in education. With contributions from worldwide experts, the text provides survey and tutorial chapters about key data mining techniques along with chapters exploring specific case studies on the use of EDM.

Biographie de l'auteur:

Cristóbal Romero is an associate professor in the Department of Computer Science at the University of Córdoba 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.

Sebastián Ventura is an associate professor in the Department of Computer Science at the University of Córdoba 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 International Conference on Educational Data Mining. His research is at the intersection of educational data mining, machine learning, human–computer interaction, and educational psychology.