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Formative assessment, learning data ...

Caballe, Santi, (1967-)

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Formative assessment, learning data analytics and gamification = in ICT education /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Formative assessment, learning data analytics and gamification/ edited by Santi Caballé and Robert Clarisó
Reminder of title:	in ICT education /
other author:	Caballe, Santi,
Published:	London, UK :Academic Press is an imprint of Elsevier, : 2016.,
Description:	1 online resource.
Notes:	Includes indexes.
[NT 15003449]:	Front Cover; Formative Assessment, Learning Data Analytics and Gamification: In ICT Education; Copyright; Dedication; Contents; List of Contributors; Foreword; References; Preface; Final Words; Part 1: Formative e-Assessment; Chapter 1: Collaborative e-Assessment as a Strategy for Scaffolding Self-Regulated Learning in Higher Education; 1. Introduction; Research Questions; 2. Framework; 2.1. Self-Regulated Learning; 2.2. Alternative Assessment and Formative Feedback; 2.2.1. Self-assessment; 2.2.2. Peer assessment; 2.2.3. Co-assessment; 2.3. Self-Regulated Learning and Formative Assessment.
[NT 15003449]:	2.4. e-Assessment With Moodle3. The Study; 3.1. Context; 3.2. The Co-Assessment Activity; 4. Methodology; 5. Results and Discussion; 5.1. Students' Questionnaire; 5.2. Content Analysis of the Written Reflections; 5.3. Qualification Outcomes; 6. Conclusions; Acknowledgments; Annex 1. Instructions for the Co-Assessment Task on the Moodle Workshop; References; Chapter 2: Towards an Adaptive e-Assessment System Based on Trustworthiness; 1. Introduction; 2. State of the Art; 2.1. Fundamental Concepts; 2.2. Trust-Based Adaptability; 2.3. Adaptive e-Assessment; 3. Adaptive Trust-Based Model.
[NT 15003449]:	4. General Adaptive e-Assessment System4.1. Evidential Module; 4.2. Adaptive Module; 5. Adaptive Trust-Based e-Assessment System; 6. Simulation of a Trust-Based Adaptive Assessment System; 7. Discussion and Challenges; 8. Conclusions and Future Work; Acknowledgments; References; Chapter 3: e-Assessment for Skill Acquisition in Online Engineering Education: Challenges and Opportunities; 1. Introduction; 2. e-Assessment; 3. Formative e-Assessment; 4. e-Assessment Models, Systems, and Tools; 4.1. e-Assessment Systems; 5. Challenges and Opportunities in Online Engineering Education.
[NT 15003449]:	5.1. Skill Acquisition5.2. Feedback; 5.3. Formative Skill Assessment; 6. Conclusions; References; Chapter 4: Evaluation Model for e-Assessment; 1. Introduction; 2. The SURE Model; Step 1. Definition of key goals; Step 2. Definition of sub goals; Step 3. Confirmation of evaluation goals; Step 4. Creation of checklist; Step 5. Acceptance of checklist; Step 6. Data collection; Step 7. Data processing; Step 8. The evaluation report; 3. Theoretical Foundation for Data Processing; 4. Examples for the SURE Model; Example 3. The satisfied students; Example 4. The unsatisfied students.
[NT 15003449]:	Example 5. The gambling students5. A Tool for e-Assessment With the SURE Model; 6. Conclusion; References; Further Reading; Chapter 5: Confidence and Learning: Affective and Cognitive Aspects in Online Mathematics With Automatic Feedback; 1. Introduction; 1.1. Scenario Under Study; 1.1.1. Teaching methodology; 1.1.2. Students; 1.1.3. The teacher; 2. Theoretical Framework; 2.1. Mathematical Confidence; 2.2. Mathematical Learning; 2.3. The Relationship Between Mathematical Confidence and Mathematical Performance; 3. Research Methodology; 3.1. Participants; 3.2. Data Collection and Analysis.
Subject:	Computer-assisted instruction. -
Online resource:	https://www.sciencedirect.com/science/book/9780128036372
ISBN:	9780128036679 (electronic bk.)

Formative assessment, learning data analytics and gamification = in ICT education /
Formative assessment, learning data analytics and gamificationin ICT education /[electronic resource] :edited by Santi Caballé and Robert Clarisó - London, UK :Academic Press is an imprint of Elsevier,2016. - 1 online resource. - Intelligent data-centric systems. - Intelligent data centric systems..

Includes indexes.

Includes bibliographical references and indexes.

Front Cover; Formative Assessment, Learning Data Analytics and Gamification: In ICT Education; Copyright; Dedication; Contents; List of Contributors; Foreword; References; Preface; Final Words; Part 1: Formative e-Assessment; Chapter 1: Collaborative e-Assessment as a Strategy for Scaffolding Self-Regulated Learning in Higher Education; 1. Introduction; Research Questions; 2. Framework; 2.1. Self-Regulated Learning; 2.2. Alternative Assessment and Formative Feedback; 2.2.1. Self-assessment; 2.2.2. Peer assessment; 2.2.3. Co-assessment; 2.3. Self-Regulated Learning and Formative Assessment.

Discussing the challenges associated with assessing student progress given the explosion of e-learning environments, this book shows educators how to effectively garner intelligent data from online educational environments that combine assessment and gamification. --

ISBN: 9780128036679 (electronic bk.)Subjects--Topical Terms:

519664
Computer-assisted instruction.
Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: LB1028.5

Dewey Class. No.: 371.33

Formative assessment, learning data analytics and gamification = in ICT education /
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245 0 0 $a Formative assessment, learning data analytics and gamification $h [electronic resource] : $b in ICT education / $c edited by Santi Caballé and Robert Clarisó
260 $a London, UK : $b Academic Press is an imprint of Elsevier, $c 2016.
300 $a 1 online resource.
490 1 $a Intelligent data-centric systems
500 $a Includes indexes.
504 $a Includes bibliographical references and indexes.
505 0 $a Front Cover; Formative Assessment, Learning Data Analytics and Gamification: In ICT Education; Copyright; Dedication; Contents; List of Contributors; Foreword; References; Preface; Final Words; Part 1: Formative e-Assessment; Chapter 1: Collaborative e-Assessment as a Strategy for Scaffolding Self-Regulated Learning in Higher Education; 1. Introduction; Research Questions; 2. Framework; 2.1. Self-Regulated Learning; 2.2. Alternative Assessment and Formative Feedback; 2.2.1. Self-assessment; 2.2.2. Peer assessment; 2.2.3. Co-assessment; 2.3. Self-Regulated Learning and Formative Assessment.
505 8 $a 2.4. e-Assessment With Moodle3. The Study; 3.1. Context; 3.2. The Co-Assessment Activity; 4. Methodology; 5. Results and Discussion; 5.1. Students' Questionnaire; 5.2. Content Analysis of the Written Reflections; 5.3. Qualification Outcomes; 6. Conclusions; Acknowledgments; Annex 1. Instructions for the Co-Assessment Task on the Moodle Workshop; References; Chapter 2: Towards an Adaptive e-Assessment System Based on Trustworthiness; 1. Introduction; 2. State of the Art; 2.1. Fundamental Concepts; 2.2. Trust-Based Adaptability; 2.3. Adaptive e-Assessment; 3. Adaptive Trust-Based Model.
505 8 $a 4. General Adaptive e-Assessment System4.1. Evidential Module; 4.2. Adaptive Module; 5. Adaptive Trust-Based e-Assessment System; 6. Simulation of a Trust-Based Adaptive Assessment System; 7. Discussion and Challenges; 8. Conclusions and Future Work; Acknowledgments; References; Chapter 3: e-Assessment for Skill Acquisition in Online Engineering Education: Challenges and Opportunities; 1. Introduction; 2. e-Assessment; 3. Formative e-Assessment; 4. e-Assessment Models, Systems, and Tools; 4.1. e-Assessment Systems; 5. Challenges and Opportunities in Online Engineering Education.
505 8 $a 5.1. Skill Acquisition5.2. Feedback; 5.3. Formative Skill Assessment; 6. Conclusions; References; Chapter 4: Evaluation Model for e-Assessment; 1. Introduction; 2. The SURE Model; Step 1. Definition of key goals; Step 2. Definition of sub goals; Step 3. Confirmation of evaluation goals; Step 4. Creation of checklist; Step 5. Acceptance of checklist; Step 6. Data collection; Step 7. Data processing; Step 8. The evaluation report; 3. Theoretical Foundation for Data Processing; 4. Examples for the SURE Model; Example 3. The satisfied students; Example 4. The unsatisfied students.
505 8 $a Example 5. The gambling students5. A Tool for e-Assessment With the SURE Model; 6. Conclusion; References; Further Reading; Chapter 5: Confidence and Learning: Affective and Cognitive Aspects in Online Mathematics With Automatic Feedback; 1. Introduction; 1.1. Scenario Under Study; 1.1.1. Teaching methodology; 1.1.2. Students; 1.1.3. The teacher; 2. Theoretical Framework; 2.1. Mathematical Confidence; 2.2. Mathematical Learning; 2.3. The Relationship Between Mathematical Confidence and Mathematical Performance; 3. Research Methodology; 3.1. Participants; 3.2. Data Collection and Analysis.
520 $a Discussing the challenges associated with assessing student progress given the explosion of e-learning environments, this book shows educators how to effectively garner intelligent data from online educational environments that combine assessment and gamification. -- $c Edited summary from book.
650 0 $a Computer-assisted instruction. $3 519664
650 0 $a Intelligent tutoring systems. $3 567576
650 7 $a EDUCATION / Administration / General $2 bisacsh $3 1599784
650 7 $a EDUCATION / Organizations & Institutions $2 bisacsh $3 1600226
655 0 $a Electronic books. $2 lcsh $3 542853
700 1 $a Caballe, Santi, $d 1967- $e editor. $3 3509191
700 1 $a Clarisó, Robert, $e editor. $3 3509192
830 0 $a Intelligent data centric systems. $3 3235783
856 4 0 $u https://www.sciencedirect.com/science/book/9780128036372