Intelligent Tutoring Systems

13th International Conference, ITS 2016, Zagreb, Croatia, June 7-10, 2016. Proceedings

  • Alessandro Micarelli
  • John Stamper
  • Kitty Panourgia
Conference proceedings ITS 2016

DOI: 10.1007/978-3-319-39583-8

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9684)

Table of contents (52 papers)

  1. Front Matter
    Pages I-XXI
  2. Full Papers

    1. Front Matter
      Pages 1-1
    2. Understanding Procedural Knowledge for Solving Arithmetic Task by Externalization
      Kazuhisa Miwa, Hitoshi Terai, Kazuya Shibayama
      Pages 3-12
    3. Do Erroneous Examples Improve Learning in Addition to Problem Solving and Worked Examples?
      Xingliang Chen, Antonija Mitrovic, Moffat Mathews
      Pages 13-22
    4. Automatic Question Generation: From NLU to NLG
      Karen Mazidi, Paul Tarau
      Pages 23-33
    5. Timing Game-Based Practice in a Reading Comprehension Strategy Tutor
      Matthew E. Jacovina, G. Tanner Jackson, Erica L. Snow, Danielle S. McNamara
      Pages 59-68
    6. Evaluation of the Formal Models for the Socratic Method
      Nguyen-Thinh Le, Nico Huse
      Pages 69-78
    7. Stealth Assessment in ITS - A Study for Developmental Dyscalculia
      Severin Klingler, Tanja Käser, Alberto-Giovanni Busetto, Barbara Solenthaler, Juliane Kohn, Michael von Aster et al.
      Pages 79-89
    8. Tell Me How to Teach, I’ll Learn How to Solve Problems
      Noboru Matsuda, Nikolaos Barbalios, Zhengzheng Zhao, Anya Ramamurthy, Gabriel J. Stylianides, Kenneth R. Koedinger
      Pages 111-121
    9. Scale-Driven Automatic Hint Generation for Coding Style
      Rohan Roy Choudhury, Hezheng Yin, Armando Fox
      Pages 122-132
    10. Estimating Individual Differences for Student Modeling in Intelligent Tutors from Reading and Pretest Data
      Michael Eagle, Albert Corbett, John Stamper, Bruce M. McLaren, Angela Wagner, Benjamin MacLaren et al.
      Pages 133-143
    11. Building Pedagogical Models by Formal Concept Analysis
      Giuseppe Fenza, Francesco Orciuoli
      Pages 144-153
    12. Predicting Learning from Student Affective Response to Tutor Questions
      Alexandria K. Vail, Joseph F. Grafsgaard, Kristy Elizabeth Boyer, Eric N. Wiebe, James C. Lester
      Pages 154-164
    13. Integrating Real-Time Drawing and Writing Diagnostic Models: An Evidence-Centered Design Framework for Multimodal Science Assessment
      Andy Smith, Osman Aksit, Wookhee Min, Eric Wiebe, Bradford W. Mott, James C. Lester
      Pages 165-175
    14. The Bright and Dark Sides of Gamification
      Fernando R. H. Andrade, Riichiro Mizoguchi, Seiji Isotani
      Pages 176-186

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 13th International Conference on Intelligent Tutoring Systems, ITS 2016, held in Zagreb, Croatia, in June 2016.

The 20 revised full papers, 32 short papers, 35 posters, and 7 young researchers’ track papers presented in this volume were carefully reviewed and selected from 147 submissions. The specific theme of the ITS 2016 conference is "Adaptive Learning in Real World Contexts".

ITS 2016 covers a wide range of topics such as: intelligent tutoring; informal learning environments, learning as a side effect of interactions; collaborative and group learning, communities of practice and social networks; simulation-based learning and serious games; dialogue and discourse during learning interactions; co-adaptation between technologies and human learning; ubiquitous and mobile learning environments; empirical studies of learning with technologies, understanding human learning on the web; adaptive support for learning, models of learners, diagnosis and feedback; modeling of motivation, metacognition, and affect aspects of learning; recommender systems for learning; virtual pedagogical agents and learning companions; ontological modeling, semantic web technologies and standards for learning; multi-agent and service oriented architectures for learning and tutoring environments; educational exploitation of data mining and machine learning techniques; instructional design principles or design patterns for educational environments; authoring tools and development methodologies for advanced learning technologies; domain-specific learning technologies, e.g. language, mathematics, reading, science, medicine, military, and industry; non conventional interactions between artificial intelligence and human learning; and privacy and security in e-learning environments.

Keywords

artificial intelligence in education collaborative learning e-learning interactive learning environments social interaction active learning bayesian networks brain computer interface cognitive models computer-assisted instruction data mining data structures distance learning genetic algorithm learning management systems machine learning natural language processing ontology personalized education semantic analysis

Editors and affiliations

  • Alessandro Micarelli
    • 1
  • John Stamper
    • 2
  • Kitty Panourgia
    • 3
  1. 1.Roma Tre University RomeItaly
  2. 2.Carnegie Mellon University PittsburghUSA
  3. 3.Neoanalysis Ltd AthensGreece

Bibliographic information

  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-39582-1
  • Online ISBN 978-3-319-39583-8
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349