CALL FOR PAPERS 

ITS 2024 - 20th International Conference on Intelligent Tutoring Systems 

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ITS2024 is the upcoming Conference of the series of Intelligent Tutoring Systems Conferences on Computer and Cognitive Sciences, Artificial Intelligence, and Deep Learning in Tutoring and Education. ITS2024 will be held in Thessaloniki, Greece, from June 10 to June 13, 2024. The conference will be hybrid and it will allow participants to attend it online too. 

The ITS2024 Conference is about “Generative Intelligence and ITS”. ITS2024 presents academic and research achievements in Computer and Cognitive Sciences, AI, and Deep Learning vis-a-vis the advances of Intelligent Tutoring Systems.

ITS is evolving to a new concept of Artificial Intelligence which can be found in various disciplines and can serve human education and well-being. This new concept is named: GENERATIVE INTELLIGENCE. Generative Intelligence concerns various AI systems, techniques, architectures, methods, or tools based on deep and machine learning which can be used to generate texts, images, solutions, and environments, able to enhance HUMAN intelligence, cognitive capacities, memory, and learning. Instead of trying to reproduce human behavior or recognize human traits using artificial intelligence techniques or learning analytics, Generative Intelligence provides a means to increase human cognitive potential.

T1: Generative Intelligence  and Tutoring Systems 

T2:  Generative Intelligence and Healthcare Informatics.                                         

T3: Games, Serious Games and Virtual Reality 

T4: Neural Networks and Data Mining 

T5: Generative Intelligence and Metaverse 

T6: Security, Privacy and Ethics in Generative Intelligence 

T7:Generative Intelligence for Applied Natural Language Processing 

T8: Generative Intelligence for Autonomous Robots and Learning 

Topics of Interest include, but are not limited to: 

• Intelligent Tutoring 

• Generative Intelligence

• Learning Environments for Underrepresented Communities 

• Artificial Intelligence in Education 

• Human in the Loop, Understanding Human Learning on the Web in a Virtual (Digital) World 

• Machine Behaviour (MB), Explainable AI, Bias in AI in Learning Environments 

• Emotions, Modeling of Motivation, Metacognition and Affect Aspects of Learning, Affective Computing and ITS 

• Extended Reality (XR), Virtual Reality (VR), Augmented Reality (AR), Mixed Reality (MR) in Learning Technologies 

• Augmented Intelligence and Metaverse 

• Informal Learning Environments, Learning as a Side Effect of Interactions 

• Collaborative and Group Learning, Communities of Practice and Social Networks 

• Analytics and Deep Learning in Learning Systems, Educational Datamining, Educational

Exploitation of Data Mining and Machine Learning Techniques 

• Sentiment Analysis in Learning Environments 

• Data Visualisation in Learning Environments 

• Privacy, Security and Ethics in Learning Environments 

• Gamification, Educational games, Simulation-based Learning and serious games 

• Brain-Computer Interface applications in Intelligent Tutoring Systems 

• Healthcare Informatics 

• Dialogue and Discourse During Learning Interactions 

• Ubiquitous, Mobile and Cloud Learning Environments 

• Virtual Pedagogical Agents and Learning Companions 

• Multi-Agent and Service-Oriented Architectures for Learning and Tutoring Environments 

• Single and GroupWise Action Modelling in Learning Environments 

• Ontological Modeling, Semantic Web Technologies and Standards for Learning 

• Empirical Studies of Learning with Technologies 

• 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 

• Personalized and Adaptive Learning Environments 

• Adaptive Support for Learning, Models of Learners, Diagnosis and Feedback 

• Recommender Systems for Learning 

• Causal Modelling and Constraints-based Modelling in Intelligent Tutoring 

The ITS2024 Conference invites submissions to be presented and discussed during the Conference. All papers must be original and not simultaneously submitted to or published in any other journal or conference. Papers should be submitted referring to a precise conference track.

The following categories are welcome: Full papers – twelve (12) pages, Short papers – eight (8) pages, and Posters – six (6) pages. All paper submissions should be made through the Easychair platform. Paper submissions should be in PDF and in English.

In order to increase high-quality papers and independent merit, the evaluation process of papers is double-blind. All papers submitted for review MUST not contain the authors’ names, affiliations, or any information that may disclose the author’s identity (this information is to be restored in the camera-ready version upon acceptance). Authors should replace names and affiliations with Xs on submitted papers. In particular, in the version submitted for review, they should avoid explicit auto-references, such as “in [1] we show” — consider “in [1] it is shown“; i.e. they may cite previous works, provided that they are not deducible from the text that the cited works belong to the authors. When citing their previous work, they should keep the names with Xs.