Proseminar: Learning Analytics and Educational Data Mining


Christoph Greven


+49 241 80 21955




Data Mining tries to gain insights from larger amounts of data by means of various systematic analysis approaches, e.g. by uncovering patterns or correlations. This is done, for example, using statistical methods or machine learning techniques and is gaining in importance due to the increasing amount of available user and interaction data. The focus is not only on economic interests but also on educational policy with Educational Data Mining. At the same time, Learning Analytics also tries to use and interpret various data from learners to improve teaching and learning, often in the form of predictions about the behaviour or success of students.

This proseminar for computer science and related subjects gives an introduction to Educational Data Mining and Learning Analytics, their techniques, applications, potentials, risks, etc.. It follows a conference-like procedure, in which various topics are worked on throughout the semester and presented in a block at the end. The focus is on learning the scientific work process and is accompanied by weekly assignments.

Further information


The course and the meetings will be held in German.


Only register for this proseminar if you can/would like to complete it. Previous knowledge of the subject area is helpful but not necessary.