國立高雄大學圖資館 |

Language: English

Back

Engineering data-driven adaptive tru...

Baneres, David.

Engineering data-driven adaptive trust-based e-assessment systemschallenges and infrastructure solutions /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Engineering data-driven adaptive trust-based e-assessment systemsedited by David Baneres, M. Elena Rodriguez, Ana Elena Guerrero-Roldan.
Reminder of title:	challenges and infrastructure solutions /
other author:	Baneres, David.
Published:	Cham :Springer International Publishing :2020.
Description:	xxiii, 327 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Education, HigherEvaluation
Online resource:	https://doi.org/10.1007/978-3-030-29326-0
ISBN:	9783030293260$q(electronic bk.)

Engineering data-driven adaptive trust-based e-assessment systemschallenges and infrastructure solutions /
Engineering data-driven adaptive trust-based e-assessment systemschallenges and infrastructure solutions /[electronic resource] :edited by David Baneres, M. Elena Rodriguez, Ana Elena Guerrero-Roldan. - Cham :Springer International Publishing :2020. - xxiii, 327 p. :ill. (some col.), digital ;24 cm. - Lecture notes on data engineering and communications technologies,v.342367-4512 ;. - Lecture notes on data engineering and communications technologies ;v.2..

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$q(electronic bk.)

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

864951
Education, Higher
--Evaluation

LC Class. No.: LB2331.62

Dewey Class. No.: 379.158

Engineering data-driven adaptive trust-based e-assessment systemschallenges and infrastructure solutions /
LDR:02534nmm a2200337 a 4500 001 576808
003 DE-He213
005 20200303140751.0
006 m d
007 cr nn 008maaau
008 201120s2020 sz s 0 eng d
020 $a 9783030293260$q(electronic bk.)
020 $a 9783030293253$q(paper)
024 7 $a 10.1007/978-3-030-29326-0 $2 doi
035 $a 978-3-030-29326-0
040 $a GP $c GP
041 0 $a eng
050 4 $a LB2331.62
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 379.158 $2 23
090 $a LB2331.62 $b .E57 2020
245 0 0 $a Engineering data-driven adaptive trust-based e-assessment systems $h [electronic resource] : $b challenges and infrastructure solutions / $c edited by David Baneres, M. Elena Rodriguez, Ana Elena Guerrero-Roldan.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xxiii, 327 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Lecture notes on data engineering and communications technologies, $x 2367-4512 ; $v v.34
505 0 $a 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.
520 $a 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.
650 0 $a Education, Higher $x Evaluation $x Technological innovations. $3 864951
650 0 $a Education, Higher $x Effect of technological innovations on. $3 231419
650 1 4 $a Computational Intelligence. $3 338479
650 2 4 $a Artificial Intelligence. $3 212515
700 1 $a Baneres, David. $3 864948
700 1 $a Rodriguez, M. Elena. $3 864949
700 1 $a Guerrero-Roldan, Ana Elena. $3 864950
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Lecture notes on data engineering and communications technologies ; $v v.2. $3 770548
856 4 0 $u https://doi.org/10.1007/978-3-030-29326-0
950 $a Intelligent Technologies and Robotics (Springer-42732)