Overview
- Explores the state of the art in software tools and innovative learning strategies for providing effective and efficient solutions to the various problems and challenges currently facing eLearning from a software data engineering perspective
- Highlights stimulating practical research from leading international experts
- Provides useful references for educational institutions, industry, academic researchers, professionals, developers, and practitioners
Part of the book series: Lecture Notes on Data Engineering and Communications Technologies (LNDECT, volume 11)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (10 chapters)
Keywords
About this book
This book presents original research on analytics and context awareness with regard to providing sophisticated learning services for all stakeholders in the eLearning context. It offers essential information on the definition, modeling, development and deployment of services for these stakeholders.
Data analysis has long-since been a cornerstone of eLearning, supplying learners, teachers, researchers, managers and policymakers with valuable information on learning activities and design. With the rapid development of Internet technologies and sophisticated online learning environments, increasing volumes and varieties of data are being generated, and data analysis has moved on to more complex analysis techniques, such as educational data mining and learning analytics. Now powered by cloud technologies, online learning environments are capable of gathering and storing massive amounts of data in various formats, of tracking user-system and user-user interactions, and of delivering rich contextual information.
Editors and Affiliations
Bibliographic Information
Book Title: Software Data Engineering for Network eLearning Environments
Book Subtitle: Analytics and Awareness Learning Services
Editors: Santi Caballé, Jordi Conesa
Series Title: Lecture Notes on Data Engineering and Communications Technologies
DOI: https://doi.org/10.1007/978-3-319-68318-8
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing AG 2018
Softcover ISBN: 978-3-319-68317-1Published: 10 February 2018
eBook ISBN: 978-3-319-68318-8Published: 09 February 2018
Series ISSN: 2367-4512
Series E-ISSN: 2367-4520
Edition Number: 1
Number of Pages: XVII, 228
Number of Illustrations: 8 b/w illustrations, 49 illustrations in colour
Topics: Computational Intelligence, Data Mining and Knowledge Discovery