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Data Analytics Approaches in Educational Games and Gamification Systems

  • Ahmed Tlili
  • Maiga Chang
Book

Part of the Smart Computing and Intelligence book series (SMCOMINT)

Table of contents

  1. Front Matter
    Pages i-xx
  2. Introduction

    1. Front Matter
      Pages 1-1
  3. Learning Analytics in Educational Games and Gamification Systems

    1. Front Matter
      Pages 25-25
    2. Dirk Ifenthaler, David Gibson
      Pages 55-68
    3. Valerie Shute, Seyedahmad Rahimi, Ginny Smith
      Pages 69-93
    4. Juan Montaño, Cristian Mondragón, Hendrys Tobar-Muñoz, Laura Orozco
      Pages 95-109
  4. Academic Analytics and Learning Assessment in Educational Games and Gamification Systems

    1. Front Matter
      Pages 111-111
    2. Mouna Denden, Ahmed Tlili, Fathi Essalmi, Mohamed Jemni, Maiga Chang, Kinshuk et al.
      Pages 113-126
    3. J. X. Seaton, Maiga Chang, Sabine Graf
      Pages 127-138
    4. Yu-Jie Zheng, I-Ling Cheng, Sie Wai Chew, Nian-Shing Chen
      Pages 165-184
  5. Modeling Learners and Finding Individual Differences by Educational Games and Gamification Systems

    1. Front Matter
      Pages 185-185
    2. Sven Manske, Sören Werneburg, H. Ulrich Hoppe
      Pages 187-212
    3. Rafael Luis Flores, Robelle Silverio, Rommel Feria, Ada Angeli Cariaga
      Pages 213-226
    4. Ana Carolina Tomé Klock, Isabela Gasparini, Marcelo Soares Pimenta
      Pages 227-246
  6. Conclusion

About this book

Introduction

Game-based learning environments and learning analytics are attracting increasing attention from researchers and educators, since they both can enhance learning outcomes. This book focuses on the application of data analytics approaches and research on human behaviour analysis in game-based learning environments, namely educational games and gamification systems, to provide smart learning. Specifically, it discusses the purposes, advantages and limitations of applying such approaches in these environments. Additionally, the various smart game-based learning environments presented help readers integrate learning analytics in their educational games and gamification systems to, for instance, assess and model students (e.g. their computational thinking) or enhance the learning process for better outcomes. Moreover, the book presents general guidelines on various aspects, such as collecting data for analysis, game-based learning environment design, system architecture and applied algorithms, which facilitate incorporating learning analytics into educational games and gamification systems.

After a general introduction to help readers become familiar with the subject area, the individual chapters each discuss a different aim of applying data analytics approaches in educational games and gamification systems. Lastly, the conclusion provides a summary and presents general guidelines and frameworks to consider when designing smart game-based learning environments with learning analytics.

Keywords

Learning Analytics Academic Analytics Data Analytics Educational Games Educational Gamification Systems Smart Learning Systems Stealth Assessment Learner Modeling Learning Improvement Educational Data Mining Computer-Based Learning

Editors and affiliations

  • Ahmed Tlili
    • 1
  • Maiga Chang
    • 2
  1. 1.Smart Learning InstituteBeijing Normal UniversityBeijingChina
  2. 2.School of Computing and Information SystemsAthabasca UniversityEdmontonCanada

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-32-9335-9
  • Copyright Information Springer Nature Singapore Pte Ltd. 2019
  • Publisher Name Springer, Singapore
  • eBook Packages Computer Science
  • Print ISBN 978-981-32-9334-2
  • Online ISBN 978-981-32-9335-9
  • Series Print ISSN 2522-0888
  • Series Online ISSN 2522-0896
  • Buy this book on publisher's site