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ITS2019 – Challenges in Artificial Intelligence – Pushing the boundaries of ITS

The Intelligent Tutoring Systems (ITS) 2019 conference was the 15th of a series of top-flight international conferences on the use of advanced computer technologies and interdisciplinary research for enabling, supporting and enhancing human learning.

ITS 2019 Conference focused on the role of Artificial Intelligence in the developments of Intelligent Tutoring Systems. It took place in Jamaica (Caribbean) from 3-7 June, 2019.

Theme of the Conference
The title of ITS 2019 Conference was “Challenges in Artificial Intelligence – Pushing the boundaries of ITS”. The Conference explored the academic and research achievements in the field of Artificial Intelligence vis-a-vis the advances in the context of Intelligent Tutoring Systems. The main focus was on the multifaceted challenges of AI and their impact on Intelligent Tutoring Systems. It aimed to present and promote high-quality research and trigger an exchange of ideas in the field, as well as to reinforce and expand the existing ITS network of researchers, academics, and market representatives.

Topics of Interest
Topics of interest to the conference include, but was not limited to:

    • Intelligent Tutoring
    • Artificial Intelligence in Education
    • Educational Datamining
    • Machine Learning in Intelligent Tutoring Systems
    • Deep Learning and Intelligent Tutoring Systems
    • Informal Learning Environments, Learning as a Side Effect of Interactions
    • Collaborative and Group Learning, Communities of Practice and Social Networks
    • Simulation-based Learning and Serious Games
    • Dialogue and Discourse During Learning Interactions
    • Ubiquitous, Mobile and Cloud Learning Environments
    • Empirical Studies of Learning with Technologies
    • Understanding Human Learning on the Web
    • Adaptive Support for Learning, Models of Learners, Diagnosis and Feedback
    • Modeling of Motivation, Metacognition and Affect Aspects of Learning
    • Recommender Systems for Learning
    • Virtual Pedagogical Agents and Learning Companions
    • Ontological Modeling, Semantic Web Technologies and Standards for Learning
    • Multi-Agent and Service Oriented Architectures for Learning and Tutoring Environments
    • Educational Exploitation of Data Mining and Machine Learning Techniques
    • Instructional Design Principles or Design Patterns for Educational Environments
    • Authoring Tools and Development Methodologies for Advanced Learning Technologies
    • Domain-Specific Learning Technologies, e.g. Language, Mathematics, Reading, Science, Medicine, Military and Industry
    • Non Conventional Interactions Between Artificial Intelligence and Human Learning
    • Privacy and Security in e-Learning Environments.

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