In the UMAP poster/demo session on Thursday, June 24, 2021, 15:30-16:15 CEST, we will present the Semantic Interest Modeling Toolkit (SIMT) and show how it has been leveraged in the transparent Recommendation and Interest Modeling Application (RIMA) to infer interest models of researchers based on their publications extracted from Semantic Scholar and use the inferred interest models to provide personalized recommendations of tweets. Here are links to the paper and the video presentation of the demo.

We are happy to welcome a new research associate and Ph.D. student to our group. Shoeb Joarder holds a master’s degree in Computer Engineering from the University of Duisburg-Essen. Shoeb is especially interested in the application of HCI, big data analytics, and visual analytics in education and social media. He will strengthen our group's research on scalable human-centered learning analytics.

Our paper "On-demand Personalized Explanation for Transparent Recommendation" got accepted as a full research paper at the workshop on Explainable User Models and Personalized System (ExUM 2021) in conjunction with the conference on User Modeling, Adaptation and Personalization (ACM UMAP 2021). The paper can be found here.

Our paper "SIMT: A Semantic Interest Modeling Toolkit" got accepted as a demo paper at the conference on User Modeling, Adaptation and Personalization (ACM UMAP 2021). The paper can be found here.

Starting summer semester 2021, we are offering a new lab course on Interactive Data Exploration and Analytics (IDEA) for Bachelor students in Applied Computer Science and Komedia. The aim of this semester's IDEA lab is to provide the foundation for an Exploratory Learning Analytics Toolkit for Students (ELAS) to support UDE students in their learning activities.

Our paper "Open, Scrutable and Explainable Interest Models for Transparent Recommendation" got accepted at the workshop on Transparency and Explanations in Smart Systems (TExSS ) in conjunction with the conference on Intelligent User Interfaces (ACM IUI 2021). The paper can be found here.

Mouadh Guesmi presented our paper "How to Design Effective Learning Analytics Indicators? A Human-Centered Design Approach" at the European Conference on Technology Enhanced Learning (ECTEL 2020). We propose in this work Human-Centered Indicator Design (HCID) as a transparent learning analytics approach that targets learners and teachers as end-users by involving them in the systematic design of learning analytics indicators that fit their needs, based on well-established design practices from the HCI and information visualization fields. A preprint version of the paper is available here.

Our chapter entitled "The LAVA Model: Learning Analytics Meets Visual Analytics" has been published in the book "Adoption of Data Analytics in Higher Education Learning and Teaching" by Springer. A preprint version of the chapter can be found here.

Our chapter entitled "Open Learning Analytics: A Systematic Literature Review and Future Perspectives" has been published in the book "Artificial Intelligence Supported Educational Technologies" by Springer. A preprint version of the chapter can be found here.

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