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<title>AIXRLES</title>
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[AIXRLES] Workshop on AI & XR for learning, education and serious gaming
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in conjunction with the 5th IEEE Artificial Intelligence & Virtual Reality
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(IEEE AIVR 2022)
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<h3>News</h3>
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<b>Sept 28, 2022</b><br/>
Paper submission deadline for this workshop is extended to <b style="color: red">October 16, 2022</b>.
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<b>Sept 28, 2022</b><br/>
Workshop on AI & XR for learning, education and serious gaming is now online!
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Introduction
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In recent years, artificial intelligence (AI), virtual reality (VR) and augmented reality (AR) have started to become widely used in learning and education. For example, simulations and serious games help students in STEM (science, technology, engineering and mathematics) to better understand abstract concepts or observe science phenomena more easily. Immersive sports learning/training in VR allows athletes to repeatedly practice with controlled configurations just like they do on the field or court. Sensor and AI technologies can be used to monitor the behavior of learners or trainees and further infer their learning or training effectiveness. <br/>
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This workshop aims to provide an interdisciplinary platform for researchers to discuss their AI and VR/AR-related work in the context of learning, education, and serious gaming from both scientific and educational perspectives.
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The topics of this workshop includes, but are not limited to analyses and applications of the following areas:
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Simulations and serious games for learning,education and training.
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Immersive sports training and exercising.
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Intelligent tutoring systems.
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AI-based learning performance monitoring and evaluation.
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Behavior analysis in the context of training and learning.
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AI models of gaze analysis, emotion analysis, and mental states analysis.
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Learning/training data visualization and analysis in XR.
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Development of new application scenarios and new prospects utilizing AI and/or XR in the context of learning.
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Submission Types
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We invite researchers and practitioners to submit their work in the form of a scientific technical paper or an application- or use-case centered paper. <br/>
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<b>Technical papers</b> should be 4-8 pages long (excluding references) and describe original research of new ideas, analyses, or scientific studies related to AI/XR and learning. Preliminary results or prototype implementations are welcome as well.
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<b>Application papers</b> hould be 2-6 pages long (excluding references) and do not necessarily have to contain original research, but can, for example, describe best practices, new usage scenarios, and creative ideas of AI and XR usage in learning, training and education.
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Submission Instructions
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Authors are invited to submit a technical paper (4~8 pages excluding references) in double-column IEEE format following the official <a href="https://www.ieee.org/conferences/publishing/templates.html" target="_blank">IEEE Manuscript Formatting guidelines</a>. Review will be double-blind, so please remove all author information in the submissions. Also consider the <a href="https://www.ieee.org/publications/rights/index.html" target="_blank">IEEE policies for publications</a> (i.e., you must own copyright to all parts and the manuscript must be original work and not currently under review elsewhere). The conference proceedings will be published by IEEE Computer Society Press and included in the <b>IEEE Xplore Digital Library</b>. Submissions will undergo a thorough peer review by members for the international program committee.
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Papers can be submitted via the <a a href="https://easychair.org/conferences/?conf=ieeeaivr2022" target="_blank">EasyChair page for IEEE AIVR</a>, using a specific track for this workshop.
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Organization Committee
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Min-Chun Hu
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(National Tsing Hua University, Taiwan)
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<img style="vertical-align: middle; width: 250px; height: 250px; border-radius: 50%;" src="https://webspace.science.uu.nl/~hurst101/img_wh_280x280.png" alt="Avatar" class="avatar">
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Wolfgang Hurst
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(Universiteit Utrecht, Netherlands)
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<img style="vertical-align: middle; width: 250px; height: 250px; border-radius: 50%;" src="https://www.canterbury.ac.nz/hitlab/contact-us/hitlabnz-staff-profiles/1574905038267_Heide-Lukosch-low.jpg" alt="Avatar" class="avatar">
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Heide Lukosch
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(University of Canterbury, New Zealand)
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Website Chair
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<img style="vertical-align: middle; width: 250px; height: 250px; border-radius: 50%;" src="https://cjwku1209.github.io/img/calvin.jpg" alt="Avatar" class="avatar">
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Calvin Ku
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(National Tsing Hua University, Taiwan)
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Workshop on AI & XR for learning, education and serious gaming
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