I was invited to present his research on the 8th September 2021 for the Falling Walls Lab Rhineland organised in Bonn. The title of the presentation was "Breaking the Walls of the Digital Classroom".
Falling Walls Lab Rhineland is jointly hosted by RWTH Aachen, University of Bonn, University of Cologne, Heinrich-Heine-Universität Düsseldorf and Forschungszentrum Jülich. The event is hosted on a rotating basis by the participating institutions. Next year's Falling Walls Lab Rhineland will take place in Düsseldorf.
The Falling Walls Foundation is a non-profit organisation in Berlin, dedicated to the support of science and the humanities. It is a unique international platform for leaders from the worlds of science, business and politics, the arts and society. Falling Walls fosters discussion on research and innovation and promotes the latest scientific findings among a broad audience from all parts of society.
March is the month of the Learning Analytics & Knowledge conference, in 2019 has taken place in Tempe, Phoenix, Arizona. Coming back from a very long journey (extended by some days off) in the United States, I decided to wrap up all my conference highlights in a blog post.
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.Continue reading
Visual Learning Pulse: Flow Prediction and Feedback in Self-regulated Learning
Visual Learning Pulse is a Master thesis research project developed in cooperation with the Welten
Institute, the Research Centre for Learning, Teaching and Technology at the Open University of the Netherlands, and partially financed by the European project Learning Analytics Community Exchange (LACE). Visual Learning Pulse explores whether physiological and physical data such as heart rate, step count and weather data if correlated with learning activity data can be used to predict learning success in self-regulated learning settings.