[AIXRLES] Workshop on AI & XR for learning, education and serious gaming

(IEEE AIVR 2022)

December 12-14, 2022 - Virtual (with satellite events)


Sept 28, 2022
Paper submission deadline for this workshop is extended to October 16, 2022.
Sept 28, 2022
Workshop on AI & XR for learning, education and serious gaming is now online!


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.

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.
The topics of this workshop include, but are not limited to analyses and applications of the following areas:

Submission Types

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.

Technical papers 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.
Application papers should 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.

Submission Instructions

Authors are invited to submit a technical paper (4~8 pages excluding references) or Application papers (2~6 pages excluding references) in double-column IEEE format following the official IEEE Manuscript Formatting guidelines. Review will be double-blind, so please remove all author information in the submissions. Also consider the IEEE policies for publications (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 IEEE Xplore Digital Library. Submissions will undergo a thorough peer review by members for the international program committee.

Papers can be submitted via the EasyChair page for IEEE AIVR, using a specific track for this workshop.

Program Schedule

Wednesday, December 14, 2022

Times below are CET. See here for an overview of the program across different time zones.

9:00am-10:00am (Keynote 1)

Johan Jeuring
(Utrecht University, Netherlands)

The impact of AI on our teaching

Many Computer Science textbooks, tests, and assignments formulate tasks in a number of sentences, possibly with some examples. The OpenAI API Codex, GitHub Copilot and other, similar technologies provide the ability to generate code from such texts. For relatively simple tasks, these techniques already perform surprisingly well. These developments may have a revolutionary effect on programming education. One aspect is that students can now solve a task by asking Copilot for the answer. Another aspect is that this may lead to a different way of programming, in which simple pieces of code are written by AI, and the focus in programming becomes more on problems at a higher level, which have to be broken down into smaller problems which can be further handled by the AI.

In this talk I will introduce Github Copilot, and I will discuss how I think it will impact our teaching. Furthermore, I will briefly introduce some of the other activities in our projects around AI in Education.

10:00am-11:00am (Keynote 2)

Shao-Yi Chien
(National Taiwan University, Taiwan)

AI Based Eye Tracking as the Next User Interface for the Masses

Eye tracking is a technology that can know users' attention. In this talk, we will first explain why eye tracking will become the core user interface in the metaverse era and will be built-in all AR/VR devices. We will also show the achievements of Ganzin Technology, an eye tracking solution provider. The new generation eye tracking system powered by AI can remove the barrier of adopting eye tracking in compact consumer devices for broad applications, which will unblock the potential of eyes as the ultimate interface to the digital world.

Short Biography

Shao-Yi Chien received the Ph.D. degree from the Department of Electrical Engineering, National Taiwan University (NTU), Taipei, Taiwan, in 2003. In 2004, he joined the Graduate Institute of Electronics Engineering and Department of Electrical Engineering, National Taiwan University, as an Assistant Professor. Since 2012, he has been a Professor. Prof. Chien served as the Chair of IEEE Circuits and Systems Society Multimedia Systems and Applications Technical Committee in 2017-2019. Dr. Chien is an expert in AR/VR, eye tracking, computer vision, real-time image/video processing, video coding, computer graphics, and system-on-a-chip design. He has published more than 300 papers and granted more than 40 patents. Since 2018, he is the founder and CEO of Ganzin Technology, Inc., an eye tracking solution provider for AR/VR/smart-glasses, which is the most easy-to-integrate solution on the market.

11:00am-12:00pm (Paper session 1)

  • Fostering students' engineering competence by adopting augmented reality: a proposed randomized controlled trial study
  • Motivational benefits and usability of a handheld Augmented Reality game for anatomy learning

12:00pm-13:00pm (Paper session 2)

  • To evaluate the learning attention and effectiveness in three remote learning approaches using EEG, eyetracker and traditional exam
  • Table Tennis Skill Learning in VR with Step by Step Guides using Forehand Drive as a Case Study

Organization Committee

Min-Chun Hu
(National Tsing Hua University, Taiwan)
Wolfgang Hurst
(Universiteit Utrecht, Netherlands)
Heide Lukosch
(University of Canterbury, New Zealand)

Program Committee

Emanuel van Dongen
(Utrecht University, Netherlands)
Kristi Jauregi Ondarra
(Utrecht University, Netherlands)
Nina Rosa
(Utrecht University, Netherlands)
Peter Vangorp
(Utrecht University, Netherlands)

Website Chair

Calvin Ku
(National Tsing Hua University, Taiwan)
Workshop on AI & XR for learning, education and serious gaming
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