There is a growing number of universities and other educational institutions that are using different kinds of virtual learning environments (VLEs) or online learning platforms (such as Moodle, Blackboard, Sakai) to deliver their educational content, especially through online courses. These online courses can be very diverse (according to the teachers' lessons plans, subjects of the courses, learning objectives, etc.) therefore no general characterization of “typical course” can most likely be made. But there is at least one aspect of online courses that for sure plays an important role in learning of students. This crucial aspect of students' online learning is interpersonal communication and participation in discussion forums.

Even though there exists plenty of research studies focused on the interactions between the participants of the online forums, these studies use predominantly traditional research methods such as surveys, questionnaires, interviews, observations, etc. (De Laat, 2007; Rabbany, 2013) Of course traditional methods are very important for our current understanding of this topic, but often these methods are not able to answer questions concerning the structure of interactions in courses as a whole and the relationships between the participants of discussions. In order to fully understand the role of discussions and interpersonal interactions in students' online learning, we need to answer questions like: What kinds of structural patterns of interactions can be found in online courses? Can we identify the basic “types” of person-to-person interactions in online courses? What kind of differences are there between forum participants? What is the role of the teacher or the tutor in online discussions and how they choose to participate in forums?

To answer the above mentioned questions we turn our attention to a newly emerged field of Learning Analytics (LA). It is a new research area that is concerned with “the measurement, collection, analysis, and reporting of data about learners and their contexts, for the purposes of understanding and optimizing learning and the environments in which it occurs” (Siemens, 2013).

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