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Artificial Intelligence in Education

19th International Conference, AIED 2018, London, UK, June 27–30, 2018, Proceedings, Part I

  • Conference proceedings
  • © 2018

Overview

Editors:
  1. Carolyn Penstein Rosé

    1. Carnegie Mellon University, Pittsburgh, USA

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  2. Roberto Martínez-Maldonado

    1. University of Technology, Sydney, Australia

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  3. H. Ulrich Hoppe

    1. University of Duisburg-Essen, Duisburg, Germany

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  4. Rose Luckin

    1. UCL Institute of Education, London, UK

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  5. Manolis Mavrikis

    1. UCL Institute of Education, London, UK

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  6. Kaska Porayska-Pomsta

    1. UCL Institute of Education, London, UK

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  7. Bruce McLaren

    1. Carnegie Mellon University, Pittsburgh, USA

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  8. Benedict du Boulay

    1. University of Sussex, Brighton, UK

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10947)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: AIED 2018.

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Table of contents (45 papers)

  1. Front Matter

    Pages I-XLI
    Download chapter PDF

  2. Full Papers

    1. Front Matter

      Pages 1-1
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    2. Investigating the Impact of a Meaningful Gamification-Based Intervention on Novice Programmers’ Achievement

      • Jenilyn L. Agapito, Ma. Mercedes T. Rodrigo
      Pages 3-16

    3. Automatic Item Generation Unleashed: An Evaluation of a Large-Scale Deployment of Item Models

      • Yigal Attali
      Pages 17-29

    4. Quantifying Classroom Instructor Dynamics with Computer Vision

      • Nigel Bosch, Caitlin Mills, Jeffrey D. Wammes, Daniel Smilek
      Pages 30-42

    5. Learning Cognitive Models Using Neural Networks

      • Devendra Singh Chaplot, Christopher MacLellan, Ruslan Salakhutdinov, Kenneth Koedinger
      Pages 43-56

    6. Measuring the Quality of Assessment Using Questions Generated from the Semantic Web

      • Ricardo Conejo, Beatriz Barros, Manuel F. Bertoa
      Pages 57-69

    7. Balancing Human Efforts and Performance of Student Response Analyzer in Dialog-Based Tutors

      • Tejas I. Dhamecha, Smit Marvaniya, Swarnadeep Saha, Renuka Sindhgatta, Bikram Sengupta
      Pages 70-85

    8. An Instructional Factors Analysis of an Online Logical Fallacy Tutoring System

      • Nicholas Diana, John Stamper, Ken Koedinger
      Pages 86-97

    9. Using Physiological Synchrony as an Indicator of Collaboration Quality, Task Performance and Learning

      • Yong Dich, Joseph Reilly, Bertrand Schneider
      Pages 98-110

    10. Towards Combined Network and Text Analytics of Student Discourse in Online Discussions

      • Rafael Ferreira, Vitomir Kovanović, Dragan Gašević, Vitor Rolim
      Pages 111-126

    11. How Should Knowledge Composed of Schemas be Represented in Order to Optimize Student Model Accuracy?

      • Sachin Grover, Jon Wetzel, Kurt VanLehn
      Pages 127-139

    12. Active Learning for Improving Machine Learning of Student Explanatory Essays

      • Peter Hastings, Simon Hughes, M. Anne Britt
      Pages 140-153

    13. Student Learning Benefits of a Mixed-Reality Teacher Awareness Tool in AI-Enhanced Classrooms

      • Kenneth Holstein, Bruce M. McLaren, Vincent Aleven
      Pages 154-168

    14. Opening Up an Intelligent Tutoring System Development Environment for Extensible Student Modeling

      • Kenneth Holstein, Zac Yu, Jonathan Sewall, Octav Popescu, Bruce M. McLaren, Vincent Aleven
      Pages 169-183

    15. Better Late Than Never but Never Late Is Better: Towards Reducing the Answer Response Time to Questions in an Online Learning Community

      • Oluwabukola Mayowa (Ishola) Idowu, Gordon McCalla
      Pages 184-197

    16. Expert Feature-Engineering vs. Deep Neural Networks: Which Is Better for Sensor-Free Affect Detection?

      • Yang Jiang, Nigel Bosch, Ryan S. Baker, Luc Paquette, Jaclyn Ocumpaugh, Juliana Ma. Alexandra L. Andres et al.
      Pages 198-211

    17. A Comparison of Tutoring Strategies for Recovering from a Failed Attempt During Faded Support

      • Pamela Jordan, Patricia Albacete, Sandra Katz
      Pages 212-224

    18. Validating Revised Bloom’s Taxonomy Using Deep Knowledge Tracing

      • Amar Lalwani, Sweety Agrawal
      Pages 225-238

    19. Communication at Scale in a MOOC Using Predictive Engagement Analytics

      • Christopher V. Le, Zachary A. Pardos, Samuel D. Meyer, Rachel Thorp
      Pages 239-252
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Other volumes

  1. Artificial Intelligence in Education

  2. Artificial Intelligence in Education

Keywords

About this book

This two volume set LNAI 10947 and LNAI 10948 constitutes the proceedings of the 19th International Conference on Artificial Intelligence in Education, AIED 2018, held in London, UK, in June 2018.
The 45 full papers presented in this book together with 76 poster papers, 11 young researchers tracks, 14 industry papers and 10 workshop papers were carefully reviewed and selected from 192 submissions. The conference provides opportunities  for the cross-fertilization of approaches, techniques and ideas from the  many fields that comprise AIED, including computer science, cognitive and learning sciences, education, game design, psychology, sociology, linguistics as well as many domain-specific areas.

Editors and Affiliations

  • Carnegie Mellon University, Pittsburgh, USA

    Carolyn Penstein Rosé, Bruce McLaren

  • University of Technology, Sydney, Australia

    Roberto Martínez-Maldonado

  • University of Duisburg-Essen, Duisburg, Germany

    H. Ulrich Hoppe

  • UCL Institute of Education, London, UK

    Rose Luckin, Manolis Mavrikis, Kaska Porayska-Pomsta

  • University of Sussex, Brighton, UK

    Benedict du Boulay

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