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Artificial Intelligence in Education

24th International Conference, AIED 2023, Tokyo, Japan, July 3–7, 2023, Proceedings

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Ning Wang

    1. University of Southern California, Los Angeles, USA

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  2. Genaro Rebolledo-Mendez

    1. University of British Columbia, Vancouver, Canada

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  3. Noboru Matsuda

    1. North Carolina State University, Raleigh, USA

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  4. Olga C. Santos

    1. Despacho 3.01, UNED-Grupo de Investigación aDeNu, Madrid, Spain

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  5. Vania Dimitrova

    1. University of Leeds, Leeds, UK

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 13916)

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

Included in the following conference series:

Conference proceedings info: AIED 2023.

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Table of contents (79 papers)

  1. Front Matter

    Pages i-xxvi
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  2. Full Papers

    1. Front Matter

      Pages 1-1
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    2. Machine-Generated Questions Attract Instructors When Acquainted with Learning Objectives

      • Machi Shimmei, Norman Bier, Noboru Matsuda
      Pages 3-15

    3. SmartPhone: Exploring Keyword Mnemonic with Auto-generated Verbal and Visual Cues

      • Jaewook Lee, Andrew Lan
      Pages 16-27

    4. Implementing and Evaluating ASSISTments Online Math Homework Support At large Scale over Two Years: Findings and Lessons Learned

      • Mingyu Feng, Neil Heffernan, Kelly Collins, Cristina Heffernan, Robert F. Murphy
      Pages 28-40

    5. The Development of Multivariable Causality Strategy: Instruction or Simulation First?

      • Janan Saba, Manu Kapur, Ido Roll
      Pages 41-53

    6. Content Matters: A Computational Investigation into the Effectiveness of Retrieval Practice and Worked Examples

      • Napol Rachatasumrit, Paulo F. Carvalho, Sophie Li, Kenneth R. Koedinger
      Pages 54-65

    7. Investigating the Utility of Self-explanation Through Translation Activities with a Code-Tracing Tutor

      • Maia Caughey, Kasia Muldner
      Pages 66-77

    8. Reducing the Cost: Cross-Prompt Pre-finetuning for Short Answer Scoring

      • Hiroaki Funayama, Yuya Asazuma, Yuichiroh Matsubayashi, Tomoya Mizumoto, Kentaro Inui
      Pages 78-89

    9. Go with the Flow: Personalized Task Sequencing Improves Online Language Learning

      • Nathalie Rzepka, Katharina Simbeck, Hans-Georg Müller, Niels Pinkwart
      Pages 90-101

    10. Automated Hand-Raising Detection in Classroom Videos: A View-Invariant and Occlusion-Robust Machine Learning Approach

      • Babette Bühler, Ruikun Hou, Efe Bozkir, Patricia Goldberg, Peter Gerjets, Ulrich Trautwein et al.
      Pages 102-113

    11. Robust Educational Dialogue Act Classifiers with Low-Resource and Imbalanced Datasets

      • Jionghao Lin, Wei Tan, Ngoc Dang Nguyen, David Lang, Lan Du, Wray Buntine et al.
      Pages 114-125

    12. What and How You Explain Matters: Inquisitive Teachable Agent Scaffolds Knowledge-Building for Tutor Learning

      • Tasmia Shahriar, Noboru Matsuda
      Pages 126-138

    13. Help Seekers vs. Help Accepters: Understanding Student Engagement with a Mentor Agent

      • Elena G. van Stee, Taylor Heath, Ryan S. Baker, J. M. Alexandra L. Andres, Jaclyn Ocumpaugh
      Pages 139-150

    14. Adoption of Artificial Intelligence in Schools: Unveiling Factors Influencing Teachers’ Engagement

      • Mutlu Cukurova, Xin Miao, Richard Brooker
      Pages 151-163

    15. The Road Not Taken: Preempting Dropout in MOOCs

      • Lele Sha, Ed Fincham, Lixiang Yan, Tongguang Li, Dragan Gašević, Kobi Gal et al.
      Pages 164-175

    16. Does Informativeness Matter? Active Learning for Educational Dialogue Act Classification

      • Wei Tan, Jionghao Lin, David Lang, Guanliang Chen, Dragan Gašević, Lan Du et al.
      Pages 176-188

    17. Can Virtual Agents Scale Up Mentoring?: Insights from College Students’ Experiences Using the CareerFair.ai Platform at an American Hispanic-Serving Institution

      • Yuko Okado, Benjamin D. Nye, Angelica Aguirre, William Swartout
      Pages 189-201

    18. Real-Time AI-Driven Assessment and Scaffolding that Improves Students’ Mathematical Modeling during Science Investigations

      • Amy Adair, Michael Sao Pedro, Janice Gobert, Ellie Segan
      Pages 202-216

    19. Improving Automated Evaluation of Student Text Responses Using GPT-3.5 for Text Data Augmentation

      • Keith Cochran, Clayton Cohn, Jean Francois Rouet, Peter Hastings
      Pages 217-228
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Other volumes

  1. Artificial Intelligence in Education

  2. Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky

Keywords

About this book

This book constitutes the refereed proceedings of the 24th International Conference on Artificial Intelligence in Education, AIED 2023, held in Tokyo, Japan, during July 3-7, 2023. This event took place in hybrid mode.

The 53 full papers and 26 short papers presented in this book were carefully reviewed and selected from 311 submissions.

The papers present result in high-quality research on intelligent systems and the cognitive sciences for the improvement and advancement of education. The conference was hosted by the prestigious International Artificial Intelligence in Education Society, a global association of researchers and academics specializing in the many fields that comprise AIED, including, but not limited to, computer science, learning sciences, and education.


Editors and Affiliations

  • University of Southern California, Los Angeles, USA

    Ning Wang

  • University of British Columbia, Vancouver, Canada

    Genaro Rebolledo-Mendez

  • North Carolina State University, Raleigh, USA

    Noboru Matsuda

  • Despacho 3.01, UNED-Grupo de Investigación aDeNu, Madrid, Spain

    Olga C. Santos

  • University of Leeds, Leeds, UK

    Vania Dimitrova

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