IJCAI2021 Artificial Intelligence for Education

Updates

• [August 19, 2021] Workshop Day is approaching. See you all tomorrow!

• [August 15, 2021] Workshop schedule is now updated. More information about topics and titles of each talk is displayed in Workshop Schedule.

• [August 1, 2021] Workshop schedule for AI4EDU @ IJCAI2021 is decided! Please check Workshop Schedule for more details. More information about invited talks will be released soon.

• [June 22, 2021] AI4EDU @ IJCAI2021 accepted paper list is released, details can be found in Accepted Papers section. Congratulations!

• [June 22, 2021] Deadline of the camera-ready final paper submission is set at July 6, 2021. Please submit your FINAL paper through the “update file” button on your paper submission page: https://easychair.org/conferences/?conf=ai4eduijcai2021.

Important Dates

• May 10, 2021 May 30, 2021 June 5, 2021: Workshop paper submission due AOE
• May 25, 2021 June 15, 2021 June 22, 2021 (Sorry for the late notification): Notifications of acceptance
• July 6, 2021: Deadline of the camera-ready final paper submission
• August 21, 2021 August 20, 2021: Workshop Date

Workshop Schedule

We outline the tentative schedule for the proposed workshop. All the time slots are in Montreal Time (UTC-4).

• 10:00 - 10:10 Opening Remarks
• 10:10 - 12:10 Invited Talk Session 1
  • 10:10 - 10:40 Automated Content Creation (Automated Authoring of ITS)
    Speaker: Andrew Olney, University of Memphis
  • 10:40 - 11:10 Intelligent tutoring system
    Speaker: James Lester, North Carolina State University
  • 11:10 - 11:40 An automated teaching assistant for middle school math classrooms
    Speaker: Kurt VanLehn, Arizona State University
  • 11:40 - 12:10 Course Recommendation
    Speaker: Zachary A. Pardos, UC Berkeley
• 12:10 - 12:50 Paper Presentation Session 1
  • 12:10 - 12:20 RLTutor: Reinforcement Learning Based Adaptive Tutoring System by Modeling Virtual Student with Fewer Interactions
    Authors: Yoshiki Kubotani, Yoshihiro Fukuhara and Shigeo Morishima
  • 12:20 - 12:30 EQ-Net: A Geometric Deep Model to Assist Educational Questionnaire Analysis
    Authors: Yaqing Wang, Min Lu and Quanming Yao
  • 12:30 - 12:40 Supporting Self-Regulation Learning Using a Bayesian Approach. Some Preliminary Insights.
    Authors: Fahima Djelil, Jean-Marie Gilliot, Serge Garlatti and Philippe Leray
  • 12:40 - 12:50 Deep Knowledge Tracing using Temporal Convolutional Networks
    Authors: Nisrine Ait Khai, Vasile Rus and Lasang Tamang
• 12:50 - 14:50 Invited Talk Session 2
  • 12:50 - 13:20 Reading Comprehension
    Speaker: Danielle McNamara, Arizona State University
  • 13:20 - 13:50 Reinforcement Learning in Education
    Speaker: Vasile Rus, University of Memphis
  • 13:50 - 14:20 Computational Thinking
    Speaker: Gautam Biswas, Vanderbilt University
  • 14:20 - 14:50 The impact of Pedagogical Policy on Student Learning: An Reinforcement Learning Approach
    Speaker: Min Chi, North Carolina State University
• 14:50 - 15:20 Paper Presentation Session 2
  • 14:50 - 15:00 Competency Model Approach to AI Literacy: Research-based Path from Initial Framework to Model
    Authors: Farhana Faruqe, Larry Medsker and Ryan Watkins
  • 15:00 - 15:10 Neural Prerequisite Prediction
    Authors: Fatima Al-Raisi, Rayyan Al Khadhuri, Khoula Al Kharusi, Istabraq Al Rahaili and Sara Al Hosni
  • 15:10 - 15:20 ADAPQUEST: A Software for Web-Based Adaptive Questionnaires based on Bayesian Networks
    Authors: Claudio Bonesana, Francesca Mangili and Alessandro Antonucci
• 15:20 - 18:20 Invited Talk Session 3
  • 15:20 - 15:50 Identify learning in real time
    Speaker: Charles Lang, Columbia University
  • 15:50 - 16:20 Human system evaluations on Educational Technologies
    Speaker: Scotty Craig, Arizona State University
  • 16:20 - 16:50 Anticipate, Notice, Respond: A Framework for Learner Variability
    Speaker: David Dockterman, Harvard University
  • 16:50 - 17:20 Explainable question answering for education
    Speaker: Dapeng Wu, University of Florida
  • 17:20 - 17:50 Analogy and Reasoning
    Speaker: Ken Forbus, Northwestern University
• 17:50 - 18:00 Final Remarks

Accepted Papers

• Supporting Self-Regulation Learning Using a Bayesian Approach. Some Preliminary Insights.
  Fahima Djelil, Jean-Marie Gilliot, Philippe Leray and Serge Garlatti

• ADAPQUEST: A Software for Web-Based Adaptive Questionnaires based on Bayesian Networks
  Claudio Bonesana, Francesca Mangili and Alessandro Antonucci

• RLTutor: Reinforcement Learning Based Adaptive Tutoring System by Modeling Virtual Student with Fewer Interactions
  Yoshiki Kubotani, Yoshihiro Fukuhara and Shigeo Morishima

• Competency Model Approach to AI Literacy: Research-based Path from Initial Framework to Model
  Farhana Faruqe, Larry Medsker and Ryan Watkins

• EQ-Net: A Geometric Deep Model to Assist Educational Questionnaire Analysis
  Yaqing Wang, Min Lu and Quanming Yao

• Neural Prerequisite Prediction
  Fatima Al-Raisi, Rayyan Al Khadhuri, Khoula Al Kharusi, Istabraq Al Rahaili and Sara Al Hosni

• Deep Knowledge Tracing using Temporal Convolutional Networks
  Nisrine Ait Khai, Vasile Rus and Lasang Tamang

Organizers

• Zitao Liu TAL Education Group, China
• Richard Tong Squirrel AI Learning, USA
• Xiangen Hu University of Memphis, USA
• Jiliang Tang Michigan State University, USA
• Hang Li TAL Education Group, China