Engineering Data-Driven Adaptive Trust-based e-Assessment Systems - Challenges and Infrastructure Solutions (Paperback, 1st ed. 2020)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Lecture Notes on Data Engineering and Communications Technologies, 34
Release date:	October 2019
First published:	2020
Editors:	David Baneres • M. Elena Rodriguez • Ana Elena Guerrero Roldan
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	327
Edition:	1st ed. 2020
ISBN-13:	978-3-03-029325-3
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-03-029325-4
Barcode:	9783030293253

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