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Engineering Data-Driven Adaptive Trust-based e-Assessment Systems: Challenges and Infrastructure Solutions: Lecture Notes on Data Engineering and Communications Technologies, cartea 34

Editat de David Baneres, M. Elena Rodríguez, Ana Elena Guerrero-Roldán
en Limba Engleză Paperback – 19 oct 2019
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.
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Specificații

ISBN-13: 9783030293253
ISBN-10: 3030293254
Pagini: 327
Ilustrații: XXIII, 327 p. 71 illus., 65 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.49 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria Lecture Notes on Data Engineering and Communications Technologies

Locul publicării:Cham, Switzerland

Cuprins

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.
 
 

Textul de pe ultima copertă

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.

Caracteristici

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