Tutorial, Learning Analytics Summer Institute, Ann Arbor, June 2017 As algorithms pervade societal life, they’re moving from an arcane topic reserved for computer scientists and mathematicians, to the object of far wider academic and mainstream media attention
Current ethical debates about the consequences of automation focus on the rights of individuals. But algorithmic processes exhibit a collective dimension. In our working paper, we therefore suggest ways to better take this dimension into account.
Regulation is a key word when the Nordic countries discuss the platform economy. The challenge is to secure good working conditions for the individual, a level playing field for businesses and tax revenues for the state. New technology is good, but the platforms must be developed in line with the labour market as a whole.
Not all learning analytics are the same. Discover how proactive learning analytics help you influence and improve ongoing learning processes by predicting the future and creating recommendations for action. Identify the 4 key elements that will determine the success of your analytics journey.
K. Fleszar, M. Mnich, and J. Spoerhase. 24th Europ. Symp. Algorithms (ESA'16), volume 57 of Leibniz International Proceedings in Informatics (LIPIcs), page 42:1--42:17. Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, (2016)