ITS2022 -18th International Conference on Intelligent Tutoring Systems (June 27-July 1, 2022)

Bulletin of the Technical Committee on Learning Technology (ISSN: 2306-0212)
Volume 21, Number 4, pp (2021)
Received December 23, 2021
Accepted December 27, 2021
Published online mmm dd, 2021
This work is under Creative Commons CC-BY-NC 3.0 license. For more information, see Creative Commons License

Authors: Stefan Trausan-Matuemail, Mihai Dascaluemail

University Politehnica of Bucharest


I. Introduction

ITS2022 ( is the upcoming Conference of the series of Intelligent Tutoring Systems (ITS) Conferences on Computer and Cognitive Sciences, Artificial Intelligence and Deep Learning in Tutoring the Education. It will be held in Bucharest, Romania, in June/July 2022 and will be hosted by University Politehnica of Bucharest. The theme of the conference is “NEW CHALLENGES FOR ITS DURING AND AFTER COVID”.

The Intelligent Tutoring Systems conference attracts researchers and academics, the industry and the end-users since 1988. It started out as an enthusiastic project by Professor Claude Frasson and in 2018 it celebrated its 30th anniversary at its birthplace in Montreal.

The ITS conference series enables, supports and enhances human learning, through an interdisciplinary research approach on Intelligent Systems. By linking together the study of the use of advanced computer technologies and various other themes, such as education, tutoring and etc, the ITS conference series builds the foundation for the evaluation of the use of Intelligent Systems in education, modeling innovative applications of technologies and the adaptation of systems to specific groups of learners.

We want to emphasize the strong link we have established with another prestigious conference, the 22th IEEE International Conference on Advanced Learning Technologies (ICALT2022; organized in the same venue, with one overlapping day (July 1, 2022).

II. Topics of Interest

The topics of interest of the ITS2022 Conference include, but are not limited to:

  • Intelligent Tutoring
  • 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
  • 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
  • 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 proceedings of the conferences are published with Springer’s Lecture Notes in Computer Science.

III. Important Dates

  • January 15, 2022: Submission deadline for all papers (Full paper, Short paper, Posters, Doctoral Consortium, Workshop Proposals, Tutorial Proposals, Industry Track Proposals)
  • February 28, 2022: Acceptance notification
  • March 31, 2022: Final version submission
  • June 27-28, 2022: Workshops and Tutorials
  • June 29 – July 1, 2022: ITS 2022 Conference