Amsterdam LSAC Conference & Hackathon

This week I attended the 2nd Learning and Student Analytics Conference taking place at the Universiteit van Amsterdam. The conference started to group the researchers and practitioners in Learning Analytics in The Netherlands. In practice this year it turned out attracting people from all over Europe. For this reason, in 2019 LSAC becomes a European Learning Analytics conference, which will be hosted in Nancy, France at the Loria lab.

I found the discussion quite relevant this year. Starting from the first keynote Tim McKay from University of Michigan which touched upon interesting points, one of them being unfair grading (e.g. gender performance in science/math/STEM subjects). How to improve grading at the university to reduce bias and discriminations? A solution to this problem was proposed: adapt the learning environments so that learners have different perceptions and different performances. Adaptive learning would allow students to structure their learning and being assessed differently.

Another hot topic nowadays is the privacy dilemma introduced by the GDPR. The dilemma is the following: if we need to justify every time why we collect educational data, we need to have clear research questions before-hand, this would inhibit us to explore new ways how to improve education itself. A reasonable position was expressed by Maren Scheffel: "Universities and educational institutions have the right and the obligation to improve their education, for this reason, they should not ask every time permission to use data to do this qualitative research".

The second keynote Ian Dolphin from Apereo focused on the future prospects of the data-driven society. His main message is that everyone operating in this field should carry the ethical questions along. This would prevent the dystopian future in which learning out of human control and is controlled by data.


LSAC Hackathon

As a follow-up to the conference, the LSAC Hackathon took place at the Amsterdam Business school. The Hackathon gathered experts in LA from different schools. I was asked to bring the Multimodal challenge and I prepared a tutorial concerning the analysis of the CPR multimodal datasets. I ended up in a group of very smart and motivated people which gave me quite some interesting feedback on feature extraction from multiple time-series.

The results of the LSAC Hackathon will be fed into the LAK Hackathon 2019 to take place before the LAK conference in Arizona in March 2019.

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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