Call for papers C1: AIED/ITS

The ICCE C1 sub-conference on AIED/ITS & Adaptive Learning focuses on research and development of interactive and adaptive learning environments for learners of all ages, across all domains. The conference provides opportunities for the cross-fertilization of knowledge and ideas from researchers in many fields that make up this interdisciplinary research area, including artificial intelligence, computer science, cognitive science, education, learning sciences, educational technology, psychology, philosophy, sociology, anthropology and linguistics. It also includes many domain-specific areas for which AIED/ITS systems have been designed and built, including ITS for ill-defined domains. Possible topics in the context of AIED/ITS systems that papers may address include (but are not limited to):

• Affective Modeling
• Architectures (distributed, agent-based, web-based)
• Assessments
• Authoring Systems
• Cognitive Engineering
• Context-Aware Learning Environments
• Educational Data Mining and Learning Analytics
• Game-Based Learning Systems
• Innovative Applications
• Instructional Planning and Strategies
• Interaction Design and Novel Learning Interfaces
• Intelligent Pedagogical Agents and Learning Companions
• Knowledge Modelling and Representation
• Learner and Student Modeling
• Machine Learning in Education
• Natural Language and Dialogue
• Ontology, Metadata and Linked open data
• Semantic Web technologies, Service-oriented architectures
• Self-regulation Learning and Metacognition
• Tutoring strategies
• Web intelligence
• Virtual and Augmented Reality

We welcome contributions that report accomplished research as well as work in progress. Papers that describe innovative architectures and models (e.g. Deep-Learning-Based Models), discuss results from AIED/ITS systems in use, and present evaluations of AIED/ITS systems are strongly encouraged. The conference also welcomes research works dealing with innovative ideas (theoretical or conceptual) that have the potential for significant impact on future research in AIED/ITS field.

• Full paper (8-10 pages)
• Short paper (5-6 pages)
• Poster paper (2-3 pages)

• PC Executive Chair
  • Ryan BAKER, University of Pennsylvania, USA

• PC Co-chair
  • Sébastien LALLÉ, Sorbonne University, France

• SIG Chair
  • May Marie TALANDRON-FELIPE, University of Science and Technology, Philippines