Pitch session: Learning with Machines

On the 14th December 2017, during the (y)OUr day organised by the Open Universiteit I was invited to prepare a pitch of 3 minutes about my research. Here is what I said.

My name is Daniele Di Mitri and I am PhD candidate at the TELI department of the Welten institute. My field of research is learning analytics. The Open Universiteit is a distance university that provides its education online. With Learning Analytics it is possible to collect the user-interaction events, analyse these data and provide more personalisation opportunities to the students.

My research uses the same approach to study learning moments happening in the physical space, such as co-located learning experiences in the classroom or at the workplace. With latest wearable sensor technologies it is possible to track motoric movements and physiological information (such as EEG, heart-rate or skin temperature). With these data, we can trace the offline learning behaviour as well as collect data about the context and activity.

In the near future, this could lead to improved Learning with Machines. I know that many of you will freak out thinking about having a Robot teacher. However, we all already use some kind of algorithmic support for our everyday life: look for example Google search, Siri and other conversational bots etc. In my research, I investigate how to make these technologies more "empathic" to their users so that they can have a better understanding of learner's emotions and psychological information and guide better learning.

These Intelligent Tutors can provide personalised feedback at any time in any place, provide you with easily accessible feedback and push you into the uncomfortable zone where the learning happens (the zone of proximal development).

If you are interested in this research, please feel free to get in contact with me!


Published by Daniele Di Mitri

Daniele Di Mitri is a research group leader at the DIPF - Leibniz Institute for Research and Information in Education and a lecturer at the Goethe University of Frankfurt, Germany. Daniele received his PhD entitled "The Multimodal Tutor" at the Open University of The Netherlands (2020) in Learning Analytics and wearable sensor support. His research focuses on collecting and analysing multimodal data during physical interactions for automatic feedback and human behaviour analysis. Daniele's current research focuses on designing responsible Artificial Intelligence applications for education and human support. He is a "Johanna Quandt Young Academy" fellow and was elected "AI Newcomer 2021" at the KI Camp by the German Informatics Society. He is a member of the editorial board of Frontiers in Artificial Intelligence journal, a member of the CrossMMLA, a special interest group of the Society of Learning Analytics Research, and chair of the Learning Analytics Hackathon (LAKathon) series.

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