Human-centred technology is widely regarded as an approach to design systems that respond to our needs and desires. Whether it takes the form of an app, device, or website, it enhances our ability to achieve our goals, by prioritizing the human needs over the technical requirements. When it comes to learning technology, human-centredness is established by taking into consideration the end-users needs utilizing evidence coming from sources such as questionnaires, interviews, observation and user logs. However, contemporary work indicates that insights extracted from multimodal data enable us to investigate and understand learners’ behaviour in ways that would not be possible with mainstream data sources. 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). In this talk, I will present methods and studies and our initial results on how multimodal data contributes to human-centered learning technology. Moreover, I will discuss the inherent connection of multimodal data with the third wave of AI, and potential implications for learning technologies and analytics.
Michail (Michalis) Giannakos is a professor of interaction design and learning technologies in the Department of CS 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 learning systems. Giannakos has co-authored more than 200 manuscripts published in prestigious peer-reviewed journals and conferences. He is the Editor-in-Chief of the International Journal of Child-Computer Interaction (Elsevier) and associate/guest editor of IEEE TLT, IEEE ToE, Behaviour & Information Technology, BJET, and CHB. He has worked at several research projects funded by diverse sources like the European Commission (EC), Microsoft Research, The Research Council of Norway (RCN), US-NSF, and served as an evaluator for funding agencies such as the EC and the US-NSF. Giannakos 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).