The Learning Analytics for Innovation and Knowledge Application (LAIKA) is an interdisciplinary research group that addresses complex problems in teaching and learning contexts, mainly in higher education. This group is joined by researchers from Computer Science, Multimedia and Telecommunications and several Ph.D. students. LAIKA also collaborates regularly with other research groups from leading national and international universities.
The group exploits the competitive advantage of being in a top online University, the UOC, as a living laboratory for research in teaching and learning, where tens of thousands of users daily interact with services, resources and among them, leaving a trail that need to be tracked to analyze and better understand the learning process. Moreover, it is important that the group not only addresses problems inherent to the UOC but also develop methodologies applicable to a set of broader contexts that can be transferred to other scenarios and situations supported by virtual learning environments as well as mixed (or blended) scenarios.
The individual careers of the members of LAIKA demonstrated extensive experience in several aspects of online learning research, including commitment with the management of the institution.
Regarding the joint experience in research, the team shares the vision and a common interest to analyse a complex ecosystem within a virtual framework in which it is essential to work from various disciplines in co-operation despite the diversity of perspectives and disciplines. The fact that the group members have been involved in projects at different levels (projects, publications and thesis co-supervisions) enriches particularly the definition of common issues of interest that can be tackled from an interdisciplinary perspective, absolutely essential in the proposed framework of Learning Analytics.
As part of their activity and long experience at the UOC, the group’s members have acquired know how in the design and evaluation of online educational settings, creating instruments for data collection and analysis using statistical and data mining techniques, as well as the triangulation with data obtained through qualitative techniques (see the list of publications).
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