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© 2020

Engineering Data-Driven Adaptive Trust-based e-Assessment Systems

Challenges and Infrastructure Solutions

  • David Baneres
  • M. Elena Rodríguez
  • Ana Elena Guerrero-Roldán
Book

Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 34)

Table of contents

  1. Front Matter
    Pages i-xxiii
  2. A. Pastor López-Monroy, Hugo Jair Escalante, Manuel Montes-y-Gómez, Xavier Baró
    Pages 1-18
  3. David Gañan
    Pages 19-40
  4. Xavier Baró, Roger Muñoz Bernaus, David Baneres, Ana Elena Guerrero-Roldán
    Pages 41-65
  5. Josep Prieto-Blazquez, David Gañan
    Pages 67-83
  6. Christophe Kiennert, Malinka Ivanova, Anna Rozeva, Joaquin Garcia-Alfaro
    Pages 85-108
  7. Isabel Guitart Hormigo, M. Elena Rodríguez, Xavier Baró
    Pages 109-132
  8. Roumiana Peytcheva-Forsyth, Harvey Mellar
    Pages 159-188
  9. Harvey Mellar, Roumiana Peytcheva-Forsyth
    Pages 189-211
  10. Manon Knockaert, Nathan De Vos
    Pages 267-296
  11. Paula Ranne, Esther Huertas Hidalgo, Roger Roca, Anaïs Gourdin, Martin Foerster
    Pages 297-316
  12. Back Matter
    Pages 317-327

About this book

Introduction

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.

Keywords

Trust-based Assessment Systems Learner Biometric Profile Modelling Management Information Systems Authentication and Authorship Systems Engineering Learning Analytics and Services Awareness Services for Learners and Teachers Modelling Knowledge Domains, Learner Modelling Scalable Data Mining for Analytics Auditing Tools for Reliable Cloud Services Services for Large-scale Data Analysis and Mining Description and Composition of Learning Services Services for Metadata Management and Trust Emerging Trends in e-Assessment Services Performance Metrics, Benchmarks and Data Sets Evaluation Methodologies Case Studies and Applications Ethical, Legal and Privacy Considerations for Data Analysis

Editors and affiliations

  • David Baneres
    • 1
  • M. Elena Rodríguez
    • 2
  • Ana Elena Guerrero-Roldán
    • 3
  1. 1.Faculty of Computer Science, Multimedia and TelecommunicationsUniversitat Oberta de CatalunyaBarcelonaSpain
  2. 2.Faculty of Computer Science, Multimedia and TelecommunicationsUniversitat Oberta de CatalunyaBarcelonaSpain
  3. 3.Faculty of Computer Science, Multimedia and TelecommunicationsUniversitat Oberta de CatalunyaBarcelonaSpain

Bibliographic information

  • Book Title Engineering Data-Driven Adaptive Trust-based e-Assessment Systems
  • Book Subtitle Challenges and Infrastructure Solutions
  • Editors David Baneres
    M. Elena Rodríguez
    Ana Elena Guerrero-Roldán
  • Series Title Lecture Notes on Data Engineering and Communications Technologies
  • Series Abbreviated Title Lecture Notes on Data Engineering and Communications Technologies
  • DOI https://doi.org/10.1007/978-3-030-29326-0
  • Copyright Information Springer Nature Switzerland AG 2020
  • Publisher Name Springer, Cham
  • eBook Packages Intelligent Technologies and Robotics Intelligent Technologies and Robotics (R0)
  • Softcover ISBN 978-3-030-29325-3
  • eBook ISBN 978-3-030-29326-0
  • Series ISSN 2367-4512
  • Series E-ISSN 2367-4520
  • Edition Number 1
  • Number of Pages XXIII, 327
  • Number of Illustrations 6 b/w illustrations, 65 illustrations in colour
  • Topics Computational Intelligence
    Artificial Intelligence
  • Buy this book on publisher's site
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