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

Challenges and Infrastructure Solutions

  • Shares original innovations, research, and lessons learned regarding teaching and technological perspectives on trust-based learning systems
  • Describes current trends, privacy, ethical issues, technological solutions, and adaptive educational models
  • Presents a global view on the state of the art, challenges, and solutions in e-Assessment
  • Offers a valuable reference guide for industry, educational institutions, researchers, developers, and practitioners
  • Discusses original research contributions on innovative learning methodologies and systems

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

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Table of contents (13 chapters)

  1. Front Matter

    Pages i-xxiii
  2. Forensic Analysis Recognition

    • A. Pastor López-Monroy, Hugo Jair Escalante, Manuel Montes-y-Gómez, Xavier Baró
    Pages 1-18
  3. Plagiarism Detection

    • David Gañan
    Pages 19-40
  4. Biometric Tools for Learner Identity in e-Assessment

    • Xavier Baró, Roger Muñoz Bernaus, David Baneres, Ana Elena Guerrero-Roldán
    Pages 41-65
  5. Engineering Cloud-Based Technological Infrastructure

    • Josep Prieto-Blazquez, David Gañan
    Pages 67-83
  6. Security and Privacy in the TeSLA Architecture

    • Christophe Kiennert, Malinka Ivanova, Anna Rozeva, Joaquin Garcia-Alfaro
    Pages 85-108
  7. Design and Implementation of Dashboards to Support Teachers Decision-Making Process in e-Assessment Systems

    • Isabel Guitart Hormigo, M. Elena Rodríguez, Xavier Baró
    Pages 109-132
  8. Design and Execution of Large-Scale Pilots

    • Roumiana Peytcheva-Forsyth, Harvey Mellar
    Pages 159-188
  9. Integration of TeSLA in Assessment Activities

    • Harvey Mellar, Roumiana Peytcheva-Forsyth
    Pages 189-211
  10. Ethical, Legal and Privacy Considerations for Adaptive Systems

    • Manon Knockaert, Nathan De Vos
    Pages 267-296
  11. Underpinning Quality Assurance in Trust-Based e-Assessment Procedures

    • Paula Ranne, Esther Huertas Hidalgo, Roger Roca, Anaïs Gourdin, Martin Foerster
    Pages 297-316
  12. Back Matter

    Pages 317-327

About this book

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.

Editors and Affiliations

  • Faculty of Computer Science, Multimedia and Telecommunications, Universitat Oberta de Catalunya, Barcelona, Spain

    David Baneres, M. Elena Rodríguez, Ana Elena Guerrero-Roldán

Bibliographic Information

Buy it now

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access