Metaverse has been the trendy topics in global education since 2022. The Metaverse is considered the third wave of the Internet revolution, able to support persistent interconnected online 3D virtual environments (3DVE), and promising to bring new levels of social connection and collaboration. How to effectively design and use Metaverse in teaching and learning remains crucial for the development of effective learning experiences. Meanwhile, Generative AI such as ChatGPT entered the spotlight in 2023 and stirred conversations around the world on its usage and “threats” to teaching, learning and training.
In this presentation, Dr. Wang will first showcase exemplary Metaverse technologies and learning platform, then share an Edu-Metaverse Ecosystem she published with her students and international collaborators. She will continue discussing the impact and implications of Generative AI on education. For example, how to effectively use Generative AI in various disciplines? In addition, she will also explore the ethical considerations of using AI in different educational settings.
Dr. Minjuan Wang is Professor and Program Head of Learning Design and Technology (LDT) in the School of Journalism and Media Studies at San Diego State University and Editor-in-Chief of the IEEE Transactions on Learning Technologies (TLT).
Dr. Wang teaches Methods of Inquiry, Designing and Developing Learning for the Global Audience, and Mobile Learning Design. Her research specialties are multidisciplinary, focusing on learning across the Metaverse, Cross-Reality (XR) and Immersive Learning, AI in education, and the sociocultural aspects of learning design and the use of technology.
She has been collaborating with scholars worldwide on research and development projects. She is a high-impact author, an internationally recognized scholar and has keynoted more than 30 international conferences. In addition to serving as the EiC for IEEE-TLT, she co-chairs the Education Society’s newly established Technical Committee on Immersive Learning (TC-ILE) and co-organizes several IEEE’s flagship conferences.
The intersection of multimodal data and advanced computational analyses has the ability to improve our understanding on how humans learn and provide novel affordances that enhance our learning, such as affective and embodied learning. Multimodal data coming from learners’ mobile devices, wearables and other ubiquitous devices not only offer new ways to detect human’s learning experience, but also enable powerful learning technologies and interfaces (via AI and ML algorithms). In this talk, I will present methods and studies and our initial results on how multimodal learning analytics (MMLA) contributes to rich measurements with respect to human learning, to the interaction affordances of learning systems, and to the design and development of learning systems. Moreover, I will discuss the inherent connection of MMLA learning technologies with AI, the potential implications of putting MMLA learning technologies to practice and potential challenges connected with ethical and methodological aspects.
Bio: Michail (Michalis) Giannakos is a professor of interaction design and learning technologies in the Department of Computer Science of the Norwegian University of Science and Technology (NTNU). He is the head of the Learner-Computer Interaction lab (https://lci.idi.ntnu. no/), and his research focuses on the design and study of emerging technologies in online and hybrid education settings and on developing new ways for humans to interact with interactive learning systems.
Giannakos has co-authored more than 200 manuscripts published in prestigious peer-reviewed journals and conferences (including Computers & Education, Computers in Human Behavior, IEEE Pervasive Computing, IEEE TLT, BJET, ACM TOCE, ACM IDC, CSCL). Giannakos the Editor-in-Chief of the International Journal of Child-Computer Interaction (Elsevier). He is also in the Editorial Board of IEEE Transactions on Learning Technology, IEEE Transactions on Education, Behaviour & Information Technology, and the International Journal of Information Management, and has served as a guest editor on highly recognized journals such as BJET, Computers in Human Behavior, and ACM TOCE. He has served as an evaluator for the European Commission (EC) and the US-NSF, and he has co-edited The Multimodal Learning Analytics Handbook (Springer) and co-authored a textbook on Educational Data Analytics for Teachers and School Leaders (Springer). Giannakos has worked at several research projects funded by diverse sources like the EC, Microsoft Research, The Research Council of Norway (RCN), US-NSF, the German Agency for International Cooperation, and Cheng Endowment. Giannakos is one of the experts in the Norwegian task force (formed by the ministry of education and research) for introducing learning analytics to Norwegian K-12 schools and universities. He is also a recipient of a Marie Curie/ ERCIM Fellowship, the Norwegian Young Research Talent Award, and he is one of the outstanding academic fellows of NTNU (2017–2022).
|29 May 2023||Submission of Special Session proposals|
|15 Jun 2023||EXTENDED|
Submission of: (i) structured abstracts (for full papers, short papers) for the main conference
|19 Jun 2023||Notification of acceptance for abstracts for the main conference.|
|01 Aug 2023||EXTENDED|
(i) complete papers for all submission types
(ii) proposals for round tables, workshops, tutorials
|24 Aug 2023||Notification of acceptance|
|07 Sep 2023||Late Paper and Doctoral Consortium submission|
|11 Sep 2023||Late Paper and Doctoral Consortium notification of acceptance|
|20 Sep 2023||Camera-ready due & author registration deadline|
|16 Oct 2023||Submission for the 1st round of the competition|
|23 Oct 2023||Notification of acceptance for the 2nd round of the competition|
|30 Oct 2023||Team members registration for participation in the 2nd round of the competition|
|09 Nov 2023||IMCL2023 Conference Opening|