Computer Science Graduate Seminar: Scaling Up Learning Analytics in Blended Learning Scenarios
Friday, May 17, 2019, 10:00am
Location: Computer Science Center E3, Room 9222, Ahornstr. 55
Speaker: Vlatko Lukarov M.Sc. (i9)
Professors: Univ.-Prof. Dr.-Ing. Ulrik Schroeder, Associate Professor Katrien Verbert
This dissertation focuses on solving the practical problem of scaling up learning analytics services in blended learning scenarios in a higher education institution in Germany. This dissertation provides a solution as a set of key principles for scaling up learning analytics in blended learning scenarios in higher education. These focus on five aspects: collecting correct requirements for the different stakeholder groups, preparing the legal and technical foundations of the higher education institution, continuously develop and improve the learning analytics services, and continuously evaluate the learning analytics services. The aspects were comprehensively investigated and realized by applying design-based research methods, software engineering methods, and evaluation methods from the Human-Computer Interaction field and the behavioral and cognitive sciences. The results and contributions from this research work are a verified end-to-end process for scaling up learning analytics in a higher education institution in Germany, a comprehensive set of requirements for the stakeholder groups, a categorized and comprehensive set of learning analytics indicators from the research and practitioners community, a sustainable learning analytics infrastructure with optimized analytics engine for scalability and performance and high fidelity prototypes, and a validated method for longitudinal studies for learning analytics impact evaluation.
The computer science lecturers invite interested people to join.