Funded Research Projects
User-Centred Social Media | Graduiertenkolleg
Project Duration: October 2015 - March 2022
The DFG-funded Research Training Group (Graduate School) “User-Centred Social Media (UCSM)” aims at developing new models and methods for analyzing, designing and evaluating social media from a user perspective. The main research fields in the RTG are modelling and understanding user behavior, social media engineering, and social media analytics. The Interdisciplinary RTG brings together researchers from computer science and psychology at the Department of Computer Science and Applied Cognitive Science of the University of Duisburg-Essen.
Graduate School Scholarship Programme (GSSP)
Project Duration: February 2019 - May 2025
GSSP is a DAAD funding programm for international doctoral candidates at graduate schools. Each DAAD scholarship in this programme comprises funding for up to four years.
Open Source Projects
The goal of the transparent Recommendation and Interest Modeling Application (RIMA) is to recommend items (e.g. tweets, Twitter users, publications, researchers, conferences) and leverage explanatory visualizations to explain the recommendations (output) as well as the underlying interest models (input). RIMA follows a user-driven personalized explanation approach by providing explanations with different levels of detail and empowering users to steer the explanation process the way they see fit. Further, the application provides on-demand explanations, that is, the users can decide whether or not to see the explanation and they can also choose which level of explanation detail they want to see.
The Open Learning Analytics Platform (OpenLAP) provides a detailed technical open learning analytics (OLA) architecture with a concrete implementation of all its components, seamlessly integrated in a platform. It encompasses different stakeholders associated through a common interest in learning analytics but with diverse needs and objectives, a wide range of data coming from various learning environments and contexts, as well as multiple infrastructures and methods that enable to draw value from data in order to gain insight into learning processes.
OpenLAP follows a user-centric approach to engage end users in flexible definition and dynamic generation of indicators. To meet the requirements of diverse users, OpenLAP provides a modular and extensible architecture that allows the easy integration of new analytics modules, analytics methods, and visualization techniques.
CourseMapper is a mind map-based collaborative course annotation and analytics platform that fosters collaboration and interaction around pdf/video learning materials, supported by visual learning analytics. CourseMapper follows a learner-centered and networked learning approach, driven by the Learning as a Network (LaaN) theory.
Learners can use CourseMapper to collaboratively organize learning materials as a mind-map, share related learning resources, collaboratively discuss and annotate pdf and video learning materials. Further, CourseMapper provides different statistical and visual analytics widgets (e.g heatmaps and annotation maps) to support monitoring, awareness, self-reflection, motivation, feedback, and recommendation.