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Engineering Data-Driven Adaptive Trust-based e-Assessment Systems = Challenges and Infrastructure Solutions /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Engineering Data-Driven Adaptive Trust-based e-Assessment Systems/ edited by David Baneres, M. Elena Rodríguez, Ana Elena Guerrero-Roldán.
其他題名:	Challenges and Infrastructure Solutions /
其他作者:	Baneres, David.
面頁冊數:	XXIII, 327 p. 71 illus., 65 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Computational intelligence. -
電子資源:	https://doi.org/10.1007/978-3-030-29326-0
ISBN:	9783030293260

Engineering Data-Driven Adaptive Trust-based e-Assessment Systems = Challenges and Infrastructure Solutions /
Engineering Data-Driven Adaptive Trust-based e-Assessment SystemsChallenges and Infrastructure Solutions /[electronic resource] :edited by David Baneres, M. Elena Rodríguez, Ana Elena Guerrero-Roldán. - 1st ed. 2020. - XXIII, 327 p. 71 illus., 65 illus. in color.online resource. - Lecture Notes on Data Engineering and Communications Technologies,342367-4512 ;. - Lecture Notes on Data Engineering and Communications Technologies,3.

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. .

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.

ISBN: 9783030293260

Standard No.: 10.1007/978-3-030-29326-0doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Engineering Data-Driven Adaptive Trust-based e-Assessment Systems = Challenges and Infrastructure Solutions /
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