Publicado por Mathieu Daquin
14/09/2016
When dealing with Data Science, “learning” tends to be an ambiguous term: With the ubiquity of machine learning, we sometimes forget that humans learn too. Sure, that’s not entirely true, but considering how evidently omnipresent the process of learning is for humans, it seems strange how much the two worlds of Data Science and Education have been struggling to collide. The most obvious way in which they do is the emerging field of learning analytics. The basic idea here is, through data analytics, to try to understand how we learn and to improve how we teach. Right now, most approaches remain technically straightforward as they focus essentially on the organisational, policy and pedagogical implications. For example, the
Publicado por Mathieu Daquin
07/04/2016
The Book “Open Data for Education Linked, Shared, and Reusable Data for Teaching and Learning” just got published by Springer. Edited by Dmitry Mouromtsev and Mathieu d’Aquin (the coordinator of AFEL), this book gives an overview of the practices in the area, including concrete examples of applications of open data for learning and teaching, from various authors, including AFEL members such as Stefan Dietze and Besnik Fetahu.
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Publicado por Susana López Sola @ Equipo GNOSS
27/01/2016
Wikipedia article about Learning analytics. There is no universally agreed definition of 'learning analytics'; the definition presented in this article is the one that appeared in the "Call for Papers of the 1st International Conference on Learning Analytics & Knowledge (LAK 2011)": Learning Analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs.
Contents
1 What is Learning Analytics?
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