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.

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Product Description

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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Product Details

General

Imprint

Springer Nature Switzerland AG

Country of origin

Switzerland

Series

Lecture Notes on Data Engineering and Communications Technologies, 34

Release date

October 2019

Availability

Expected to ship within 10 - 15 working days

First published

2020

Editors

, ,

Dimensions

235 x 155mm (L x W)

Format

Paperback

Pages

327

Edition

1st ed. 2020

ISBN-13

978-3-03-029325-3

Barcode

9783030293253

Categories

LSN

3-03-029325-4



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