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). A preprint version of 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.

To support our online teaching in the summer semester 2020, we will use CourseMapper; 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.

We're co-organizing two workshops in conjunction with the 10th International Learning Analytics and Knowledge (LAK) Conference. The workshop on Explainable Learning Analytics (XLA) aims at advancing research and practices around transparent insights, decisions, and actions in LA to improve the trustworthiness, impact, and adoption of LA systems at scale. The aim of the workshop on Addressing Drop-out Rates in Higher Education (ADORE) is to discuss challenges, issues, and best practices related to institutional LA and supporting student success. The paper submission deadline for both workshops is December 15, 2019.

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