CategoriesCall for Proposals

Multimodal and Immersive Systems for Skills Development and Education (BJET)

Call for Papers: Multimodal and Immersive Systems for Skills Development and Education

Guest editor(s): 

  • Daniele Di Mitri, DIPF, Germany
  • Bibeg Limbu, TU Delft, The Netherlands
  • Jan Schneider, DIPF, Germany
  • Deniz Iren, Open University, The Netherlands
  • Michail Giannakos, NTNU, Norway
  • Daniel Spikol, University of Copenhagen, Denmark
  • Roland Klemke, Open University, The Netherlands

Rationale for publications

During the last decade, we have seen an enormous penetration of multimodal and immersive systems such as virtual, augmented reality and motion-based systems. Such systems, along with rapidly evolving technological affordances (e.g., multimodal interaction, tactile feedback) powered by Artificial Intelligence (AI) and sensors, are attempting to redefine how we interact and learn with technology. This attempt has long-term implications for human-computer interaction and technology-enhanced learning, enabling new forms of personalised, contextual, and deliberate practice of skills in authentic settings. This can facilitate more holistic learning that considers the interplay of different domains, such as the cognitive, affective and psychomotor domains. Capabilities arising from the interplay of sensor data and advanced computational approaches can provide insights into the complex learning phenomena unfolding during real-world practice, allowing seamless learning interventions to be deployed in authentic learning settings. In this context, multimodal and immersive systems can support learning approaches such as embodied learning, considering often ignored aspects such as context, psychomotor, affective, and physiological aspects. However, the potential of multimodality is an ongoing research endeavour, as some remaining challenges must be addressed.

Critical challenges of multimodal and immersive systems in education comprise:

  • how to combine multimodal data to deliver meaningful information on human performance?
  • What are good practices to represent real-time data actionable by AI systems?
  • How to use multimodal data to compare the difference in performance between a learner and an expert and across multiple learners to detect and classify indicators of performance or training mistakes?
  • How can theory-informed meaningful guidance and feedback be designed in Multimodal and immersive environments with multiple modalities to provide desirable learning experiences?

This Special Section will build upon the seminal empirical and conceptual work conducted during the last years in the series of workshops (e.g., Cross-MMLA, MAIED, MILeS) during major conferences (e.g., LAK, EC-TEL, AIED) to produce a unique collection of articles that will critically highlight the challenges and opportunities in the confluence of AI and multimodal learning analytics to support learning.

Topics of interest include, but are not limited to, the following aspects:

The potential scope for interest should aim at supporting the development of complex skills through the use of multimodal and/or immersive technologies that might include but are not limited to:

  • Affordances of multimodal immersive learning systems
  • User and learner experience in multimodal immersive learning systems
  • Pedagogical concepts for multimodal immersive learning systems
  • User acceptance of multimodal immersive learning systems
  • Application fields for multimodal immersive learning systems
  • Evaluation approaches for multimodal immersive learning systems
  • Authentic practice through multimodal technologies
  • Sensor-based analytics for learning
  • Multimodal AI tutors/Intelligent Tutoring Systems


Submission and Inquiries

We, therefore, invite submissions concerning the above topics. Abstracts should demonstrate that the paper fits the special section focus, has a rigorous methodology, is innovative, makes a significant contribution to the field, is relevant to an international audience, and takes a critical approach.  Full papers will undergo the standard reviewing process.  Therefore, if based on your abstract, you are invited to submit a full paper, this invitation is just that and should not be taken as an indication that the final paper will be accepted.

Abstracts should be around 250 words, clearly and concisely written, and generally include the following:

  • An introduction of one or two sentences stating the research aims and educational context; e.g. undergraduate; high school; pre-school, all levels etc.
  • For empirical reports, a brief summary of the data collection methodology.
  • A summary of the outcomes
  • Concise conclusions and implications in two or three sentences. What new insights does this research provide? What is its unique and significant contribution to the field? How is it relevant for a diverse international audience?

Important Dates:

Abstract submission emailed to the guest editors: February 1st, 2023

Full paper submission: May 15th, 2023

Last Article Acceptances: September 1st, 2023

Articles published online as soon as copyediting is completed.

Issue Publication: January 2024


Guest editors:  

Daniele Di Mitri, DIPF, Germany, (corresponding guest editor)

Bibeg Limbu, TU Delft, The Netherlands,

Jan Schneider, DIPF, Germany,

Deniz Iren, Open University, The Netherlands,

Michail Giannakos, NTNU, Norway,

Daniel Spikol, University of Copenhagen, Denmark,

Roland Klemke, Open University, The Netherlands

Published by Daniele Di Mitri

Daniele Di Mitri is a research group leader at the DIPF - Leibniz Institute for Research and Information in Education and a lecturer at the Goethe University of Frankfurt, Germany. Daniele received his PhD entitled "The Multimodal Tutor" at the Open University of The Netherlands (2020) in Learning Analytics and wearable sensor support. His research focuses on collecting and analysing multimodal data during physical interactions for automatic feedback and human behaviour analysis. Daniele's current research focuses on designing responsible Artificial Intelligence applications for education and human support. He is a "Johanna Quandt Young Academy" fellow and was elected "AI Newcomer 2021" at the KI Camp by the German Informatics Society. He is a member of the editorial board of Frontiers in Artificial Intelligence journal, a member of the CrossMMLA, a special interest group of the Society of Learning Analytics Research, and chair of the Learning Analytics Hackathon (LAKathon) series.

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