Educational Data Mining: Applications and Trends - Couverture souple

Couverture souple

ISBN 10 : 3319344994 ISBN 13 : 9783319344997

Editeur : Springer, 2016

Synopsis

This book is devoted to the Educational Data Mining arena. It highlights works that show relevant proposals, developments, and achievements that shape trends and inspire future research. After a rigorous revision process sixteen manuscripts were accepted and organized into four parts as follows:

· Profile: The first part embraces three chapters oriented to: 1) describe the nature of educational data mining (EDM); 2) describe how to pre-process raw data to facilitate data mining (DM); 3) explain how EDM supports government policies to enhance education.

· Student modeling: The second part contains five chapters concerned with: 4) explore the factors having an impact on the student's academic success; 5) detect student's personality and behaviors in an educational game; 6) predict students performance to adjust content and strategies; 7) identify students who will most benefit from tutor support; 8) hypothesize the student answer correctness based on eye metrics and mouse click.

· Assessment: The third part has four chapters related to: 9) analyze the coherence of student research proposals; 10) automatically generate tests based on competences; 11) recognize students activities and visualize these activities for being presented to teachers; 12) find the most dependent test items in students response data.

· Trends: The fourth part encompasses four chapters about how to: 13) mine text for assessing students productions and supporting teachers; 14) scan student comments by statistical and text mining techniques; 15) sketch a social network analysis (SNA) to discover student behavior profiles and depict models about their collaboration; 16) evaluate the structure of interactions between the students in social networks.

This volume will be a source of interest to researchers, practitioners, professors, and postgraduate students aimed at updating their knowledgeand find targets for future work in the field of educational data mining.

A propos du livre

Présentation de l'éditeur

This book offers 16 papers highlighting relevant proposals, new research, and results that will shape trends and inspire future research in Educational Data Mining. The papers are grouped into four areas: Profile; Student modeling; Assessment and Trends.

Détails de l'édition

• Éditeur: Springer
• Date d'édition: 2016
• Langue: anglais
• ISBN 10: 3319344994
• ISBN 13: 9783319344997
• Reliure: Broché
• Nombre de pages: 488
• Éditeur: Peña-Ayala Alejandro
• Coordonnées du fabricant: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3; Heidelberg; 69115; Allemagne