If you do research in the field of learning science there is almost certainly one point in which you realise how difficult is to model and describe a learning process. Among the human cognitive processes, learning is definitely one of the most complex and fascinating, as it encompasses several dimensions including as motivation, knowledge, emotional states.
The beautiful city of Sydney hosted the 8th international conference of Learning Analytics 2018 (LAK'18). There with my colleagues of OUNL and DIPF, we brought our contributions to the research community.
This year my main contribution constituted in the organisation of Multimodal Data Challange at the Learning Analytics Hackathon. Together with my colleagues Jan Schneider (DIPF) we brought our approach to capturing, storing, analysing, annotating and exploiting multimodal data. The challenge was introduced by the info document of the Hackathon, as well as the 3-pages submission for the LAKHackathon submission Multimodal challenge: analytics beyond user-computer interaction data.
Purpose Pyramid of Multimodal Data - (cc) Daniele Di Mitri
Originally posted in Lilab.eu
Last week the European Conference on Technology Enhanced Learning (#ECTEL2017) took place in Tallinn University with an overarching theme: "data-driven approaches in education". This year's conference focused on the role of data and learning analytics as means for deciphering and improving learning and teaching practices.
Contribute to the definition of Multimodal Data in Learning! Provide your ideas to the Multimodal Data Tree