Overview
- Shares original innovations, research, and lessons learned regarding teaching and technological perspectives on trust-based learning systems
- Describes current trends, privacy, ethical issues, technological solutions, and adaptive educational models
- Presents a global view on the state of the art, challenges, and solutions in e-Assessment
- Offers a valuable reference guide for industry, educational institutions, researchers, developers, and practitioners
- Discusses original research contributions on innovative learning methodologies and systems
Part of the book series: Lecture Notes on Data Engineering and Communications Technologies (LNDECT, volume 34)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (13 chapters)
-
Front Matter
-
Back Matter
Keywords
- Trust-based Assessment Systems
- Learner Biometric Profile Modelling
- Management Information Systems
- Authentication and Authorship Systems
- Engineering Learning Analytics and Services
- Awareness Services for Learners and Teachers
- Modelling Knowledge Domains, Learner Modelling
- Scalable Data Mining for Analytics
- Auditing Tools for Reliable Cloud Services
- Services for Large-scale Data Analysis and Mining
- Description and Composition of Learning Services
- Services for Metadata Management and Trust
- Emerging Trends in e-Assessment Services
- Performance Metrics, Benchmarks and Data Sets
- Evaluation Methodologies
- Case Studies and Applications
- Ethical, Legal and Privacy Considerations for Data Analysis
About this book
This book shares original innovations, research, and lessons learned regarding teaching and technological perspectives on trust-based learning systems. Both perspectives are crucial to enhancing the e-Assessment process.
In the course of the book, diverse areas of the computer sciences (machine learning, biometric recognition, cloud computing, and learning analytics, amongst others) are addressed. In addition, current trends, privacy, ethical issues, technological solutions, and adaptive educational models are described to provide readers with a global view on the state of the art, the latest challenges, and potential solutions in e-Assessment. As such, the book offers a valuable reference guide for industry, educational institutions, researchers, developers, and practitioners seeking to promote e-Assessment processes.
Editors and Affiliations
Bibliographic Information
Book Title: Engineering Data-Driven Adaptive Trust-based e-Assessment Systems
Book Subtitle: Challenges and Infrastructure Solutions
Editors: David Baneres, M. Elena Rodríguez, Ana Elena Guerrero-Roldán
Series Title: Lecture Notes on Data Engineering and Communications Technologies
DOI: https://doi.org/10.1007/978-3-030-29326-0
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020
Softcover ISBN: 978-3-030-29325-3Published: 19 October 2019
eBook ISBN: 978-3-030-29326-0Published: 18 October 2019
Series ISSN: 2367-4512
Series E-ISSN: 2367-4520
Edition Number: 1
Number of Pages: XXIII, 327
Number of Illustrations: 6 b/w illustrations, 65 illustrations in colour