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Technology Enhanced Assessment

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Cover of 'Technology Enhanced Assessment'

Table of Contents

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    Book Overview
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    Chapter 1 Dynamic Generation of Assessment Items Using Wikidata
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    Chapter 2 Students’ Attitudes Towards Personal Data Sharing in the Context of e-Assessment: Informed Consent or Privacy Paradox?
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    Chapter 3 Students’ and Teachers’ Perceptions of the Usability and Usefulness of the First Viewbrics-Prototype: A Methodology and Online Tool to Formatively Assess Complex Generic Skills with Video-Enhanced Rubrics (VER) in Dutch Secondary Education
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    Chapter 4 Assessing Learning in MOOCs Through Interactions Between Learners
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    Chapter 5 Corrective Feedback and Its Implications on Students’ Confidence-Based Assessment
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    Chapter 6 Automated Feedback for Workplace Learning in Higher Education
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    Chapter 7 Formative Assessment of Inquiry Skills for Responsible Research and Innovation Using 3D Virtual Reality Glasses and Face Recognition
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    Chapter 8 Quizbot: Exploring Formative Feedback with Conversational Interfaces
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    Chapter 9 Best of Two Worlds: Using Two Assessment Tools in One Course
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    Chapter 10 Digital Exams in Engineering Education
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    Chapter 11 A Cost–Benefit Analysis for Developing Item Banks in Higher Education
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    Chapter 12 Advantages of Using Automatic Formative Assessment for Learning Mathematics
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    Chapter 13 Getting to Grips with Exam Fraud: A Qualitative Study Towards Developing an Evidence Based Educational Data Forensics Protocol
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    Chapter 14 Assessment of Collaboration and Feedback on Gesture Performance
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Title
Technology Enhanced Assessment
Published by
Springer International Publishing, October 2019
DOI 10.1007/978-3-030-25264-9
ISBNs
978-3-03-025263-2, 978-3-03-025264-9
Editors

Draaijer, Silvester, Joosten-ten Brinke, Desirée, Ras, Eric

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 2 67%
Student > Bachelor 1 33%
Readers by discipline Count As %
Computer Science 2 67%
Social Sciences 1 33%