Keynotes

Minjuan Wang
Professor and Program Head, San Diego State University; Editor-in-Chief, IEEE Transactions on Learning Technologies (TLT)

The Impact of Metaverse and Generative AI on Education

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.

The Speaker

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.

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Michalis Giannakos
Professor at Norwegian University of Science and Technology (NTNU)

Multimodal Learning Analytics to Future Learning Systems

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.

The Speaker

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).

Personal URL: https://www.ntnu.edu/employees/michailg – Lab’s URL: https://lci.idi.ntnu.no/

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Invited Speech

Stavros Demetriadis
School of Informatics, Aristotle University of Thessaloniki, Greece

"Harmonizing Minds: Navigating Human-AI Symbiosis in Learning Environments with Conversational AI"

Conversational AI software, exemplified by tools like ChatGPT, can positively impact human learning across various dimensions, including cognitive and metacognitive realms. However, the discussion on the limitations and risks associated with this technology is widespread. This underscores the necessity for a Human-AI symbiosis framework that enhances human learning and productivity, rather than displacing humans in favor of AI.

The speaker will commence by presenting research findings derived from extensive years of exploration in the "chatbots for learning" domain. This will encompass the latest results highlighting the efficacy of leveraging ChatGPT as a valuable tool for student learning. Building upon these findings, the discussion will then pivot towards examining aspects of human learning within an AI-populated world. The aim is to progress towards formulating an initial framework for Human-AI symbiosis in learning environments. The talk will delve into key perspectives from current research that underscore the significance of such considerations.

The Speaker

Stavros Demetriadis is a Full Professor with the School of Informatics, Aristotle University of Thessaloniki. After serving for 13 years as informatics teacher in Greek secondary education, Stavros joined the University doing initially research in areas such as: ICT use and acceptance by school teachers, Multimedia technology in education and Computer-supported collaborative learning. Since 2015 he started studying the impact of chatbots (and conversational AI in general) on aspects of student learning. He has since published relevant research in major journals in the area (for example, IEEE TLT, Computers and Education, and others) and has led the EU funded project with the acronym ‘ColMOOC’ (2018-2021) which explored the impact of conversational agents on collaborative learning in MOOC environments. Currently his work explores various modes of Human-AI interactions that bring value to educational settings. Overall, he has participated in 29 research/development projects, being principal investigator in 9 of them, received 3 “Best paper award” at international conferences and was supervisor of the “Cubes Coding” project that received awards at “Winners of Open Education Challenge 2014” and “NUMA Competition 2014”. He is author/co-author of more than 200 publications with Google Scholar reporting more than 4900 citations and h-index = 31.

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