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Engineering data-driven adaptive trust-based e-assessment systems : challenges and infrastructure solutions / David Baneres, M. Elena Rodríguez, Ana Elena Guerrero-Roldán, editors.

Baneres, David, editor.; Rodríguez, M. Elena, editor.; Guerrero-Roldán, Ana Elena, editor.
2020
LB2331.62
Available Online
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Title
Engineering data-driven adaptive trust-based e-assessment systems : challenges and infrastructure solutions / David Baneres, M. Elena Rodríguez, Ana Elena Guerrero-Roldán, editors.
ISBN
9783030293260 (electronic book)
3030293262 (electronic book)
9783030293253
DOI
https://doi.org/10.1007/978-3-030-29326-0
https://doi.org/10.1007/978-3-030-29
Published
Cham, Switzerland : Springer, 2020.
Language
English
Description
1 online resource (xxiii, 327 pages) : illustrations.
Item Number
10.1007/978-3-030-29326-0 doi
10.1007/978-3-030-29
Call Number
LB2331.62
Dewey Decimal Classification
379.1/58
Summary
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.
Note
Includes index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed October 25, 2019).
Added Author
Baneres, David, editor.
Rodríguez, M. Elena, editor.
Guerrero-Roldán, Ana Elena, editor.
Series
Lecture notes on data engineering and communications technologies ; v.34
Available in Other Form
Engineering Data-Driven Adaptive Trust-Based e-Assessment Systems : Challenges and Infrastructure Solutions
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Online Access
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Online Resources > Ebooks
All Resources
Forensic Analysis Recognition
Plagiarism Detection
Biometric Tools for Learner Identity in e-Assessment
Engineering Cloud-based Technological Infrastructure
Security and Privacy in the TeSLA Architecture
Design and Implementation of Dashboards to Support Teachers Decision-Making Process in e-Assessment Systems
Design and execution of TeSLA Pilots
Ethical, Legal and Privacy Considerations for Adaptive Systems
Underpinning Quality Assurance in Trust-based e-Assessment Procedures.

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