AIMA4Edu: AIMA4Edu Workshop at IJCAI 2020 Pacifico Convention Plaza Yokohama Yokohama, Japan, July 11-17, 2020 |
Conference website | https://www.aima4edu.com/ |
Abstract registration deadline | May 25, 2020 |
Submission deadline | July 3, 2020 |
AIMA4Edu: AI-based Multimodal Analytics for Understanding Human Learning in Real-World Educational Contexts
Format: One day workshop. Program includes invited talks, presentations, discussion, final panel discussion, and future plans.
Proposed Schedule:
08:30 - 08:40 Welcome remarks
08:40 - 09:00 Overview of the shared dataset
09:00 - 09:30 Invited talk (1)
09:30 - 10:00 Contributed talks (2)
10:00 - 10:30 Coffee break
10:30 - 11:30 Invited talks (2)
11:30 - 12:00 Contributed talks (2)
12:00 - 14:00 Lunch break
14:00 - 15:00 Invited talks (2)
15:00 - 16:00 Contributed talks (2)
16:00 - 17:00 Panel Discussion
17:00 Closing remarks
Scope and Objectives
Human learning is a complex interactive and iterative process that takes place at a very fine grained level. However, our ability to understand and support this fascinating latent learning process is often limited by what we can perceive and how we can measure. Recent advances of sensing technology and accompanying techniques for processing multimodal data, which manifest the psychological as well physiological processes during the human learning process, give us a new opportunity to look at this classical problem with a new pair of lens. The emerging new type of data includes, but not limited to, student’s physiological signals such as EKG or EEG waveforms, students’ speech, facial expressions and postures, within the context of particular learning activities. We are particularly interested in those data gathered from the real world educational activities versus those from the controlled lab environment.
In this 2nd annual convening of the AIMA4EDU workshop, we expand topic areas to include nascent methodological areas and work beginning to apply multimodal data and AI to support learners. A multimodal dataset collected by Squirrel AI Learning is published on the workshop’s website (https://www.aima4edu.com/), and we also encourage attendants to share more data to the community for research purposes only.
Relevant topic areas include (but not limited to):
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Predicting learning and/or affect from multimodal data streams
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Visualizing and representing multimodal data for human inference
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Constructing models of learning interactions
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Evaluating learning designs and/or learning components
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New analytic tools and techniques for connecting learning with multimodal data, especially on model interpretability and fairness
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Using multimodal data to inform data-driven interventions for better learning and engagement
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Frameworks and models for better applicability and generalizability of multimodal learning analytics
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Challenges associated with multimodal integrated behavioral and affective analyses
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The engineering and modeling around multi-modal sensor synchronization
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Comprehensive user state interpretation and forecast
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Interface and HCI design around data collection and feedback mechanism
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Standardization for data format and processed around MIBA
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Collaboration of students with coaches and collaboration between students in a group within the AI supported classroom environment
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Implication of multimodal data for recommendation
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Multimodal data sharing best practices, incentives and mechanisms, including data protection, ethical use of data, and governance.
This conference format will be:
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Presentations of peer-reviewed papers, including discussions
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Final panel discussion on needs and challenges for the future
Related Workshop at IJCAI: None
This workshop is a follow-up to our IJCAI ‘19 workshop by the same name. It focuses on exploiting AI-based multimodal data processing methods to understand how to leverage big data, collected from multiple modalities, in an education context and advance new educational applications fuelled by AI.
Paper Submission and Publication
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Authors should submit papers in IJCAI-2020’s format as PDF (Springer Format) on easychair, or send to guodong.long@uts.edu.au (primary contact)
Important Dates
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Paper submission ultimate deadline: May 25th, 2020
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Notification of acceptance/rejection: June 4th, 2020
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Camera-ready version deadline: July 3rd, 2020
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Conference July 12, 2020? (exact day will be communicated after acceptance)
Organizing Committee
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Guodong Long (University of Technology Sydney, guodong.long@uts.edu.au)
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Zachary Pardos (UC Berkeley, pardos@berkeley.edu)
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Edgar Kalns (SRI International, edgar.kalns@sri.com)
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Richard Tong (Yixue Squirrel AI and IEEE, richard.tong@ieee.org)
Members of program committee (tentative):
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Lingfei Teddy Wu (IBM Watson)
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Artur Dubrawski (Carnegie Mellon University)
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Tom Mitchell (Carnegie Mellon University)
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Jonathan Rowe (North Carolina State University)
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Jing Jiang (University of Technology Sydney)
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Shirui Pan (Monash University)
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Marcelo Worsley (Northwestern University )
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Dor Abrahamson (University of California, Berkeley)
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Paulo Blikstein (Columbia Teacher’s College)
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Bertrand Schneider (Harvard University)
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Shuchi Grover (SRI International)
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Mike Tissenbaum (University of Wisconsin, Madison)
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Joseph Grafsgaard (North Carolina State University)
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James Lester (North Carolina State University)
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Sen Wang (University of Queensland)
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Lina Yao (University of New South Wales)
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Lujie Karen Chen (Carnegie Mellon University)
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Fangli Xu (Squirrel AI Learning)