Welcome to the Website of the Social Computing Group
At the intersection of computer science and social science, we conduct applied research into intelligent data-intensive systems and their application in social media, technology-enhanced learning, and knowledge management domains. Headed by Prof. Dr. Mohamed Amine Chatti, we design, implement, and evaluate new analytics-driven theories, methods and systems for tomorrow’s smart learning and working environments. We offer lectures, seminars, and practical courses in learning technologies, web technologies, data science and visual analytics, following a technology-enhanced, student-centered learning approach.
We're part of the Department of Computer Science and Applied Cognitive Science, Faculty of Engineering at the University of Duisburg-Essen, one of the top universities worldwide younger than 50 years.
News & Events
March 2021New Lab Course IDEA
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.
February 2021New Publication in TExSS@IUI 2021
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.
September 2020New Publication at ECTEL 2020
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.
April 2020CourseMapper in SS20
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.
November 2019XLA and ADORE Workshops at LAK2020
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.
Where to find us
We are located in the 4th floor of building LE - Campus Duisburg
Fakultät für Ingenieurwissenschaften
Fachgebiet Social Computing