At the intersection of computer science and cognitive science, we conduct applied research into human-centered explainable AI and intelligent data-intensive systems and their application in technology-enhanced learning and knowledge management domains. Headed by Prof. Dr. Mohamed Amine Chatti, we take an interdisciplinary approach in designing and developing trustworthy human-centered AI technologies and novel analytics-driven methods and visualizations for tomorrow’s smart learning and working environments. We offer lectures, seminars, and practical courses in learning technologies, web technologies, data science, visual analytics, and human-AI interaction following a technology-enhanced, student-centered learning approach.

We're part of the Department for Human-centered Computing and Cognitive Science (HCCS), Faculty of Computer Science at the University of Duisburg-Essen, one of the top universities in Germany.

News & Events

On December 1, 2023, Shoeb Joarder attended the Lehrkräftefortbildung Informatik 2023. He presented our ongoing work on Human-Centered Learning Analytics (HCLA) with Open Learning Analytics Platform (OpenLAP), our platform for self-service learning analytics. He showed a demo of OpenLAP in action, with a focus on the Indicator Specification Card (ISC) Creator and the Indicator Editor in OpenLAP.

Our paper "Interactive Explanation with Varying Level of Details in an Explainable Scientific Literature Recommender System" has been published in the International Journal of Human-Computer Interaction (IJHCI). In this work, we show how to design explanations with different levels of detail, in a systematic and theoretically-sound manner. Further, we highlight the positive impact of user-controlled, interactive explanation with varying level of details on the perception of explainable recommendation. A preprint version of the paper is available here.

Our paper "Automatic Construction of Educational Knowledge Graphs: A Word Embedding-Based Approach" has been published in the Information Journal.  In this work, we aimed at improving the concept extraction and weighting mechanisms in educational knowledge graphs (EduKGs) by leveraging state-of-the-art word and sentence embedding techniques. The paper is available as open access here.

Our paper "Semantic Interest Modeling and Content-Based Scientific Publication Recommendation Using Word Embeddings and Sentence Encoders" has been published in the Multimodal Technologies and Interaction Journal. In this work, we combine word embedding-based keyphrase extraction techniques with knowledge bases to generate semantically-enriched user interest models, and we leverage pretrained transformer sentence encoders to represent user models and papers and compute their similarities.  The paper is available as open access here.  

On August 28 & 29, 2023, Shoeb Joarder attended the 2nd Learning AID at the Ruhr-University of Bochum. The conference and workshop was organized by the state funded project KI:edu.nrw – a project to promote Didactics, Ethics and Technology of Learning Analytics and AI in Higher Education.  The event focused on the practical use of learning analytics, artificial intelligence, and data mining in higher education. Shoeb presented our ongoing research on Human-Centered Learning Analytics (HCLA) and gave a demo on the ISC Creator module in our Open Learning Analytics Platform (OpenLAP). The ISC Creator provides an intuitive user interface that allows the low-cost design of low-fidelity Learning Analytics indicators using Indicator Specification Cards. A demo can be found here.

You might be interested in understanding the difference between Transparency and Justification in explainable recommender systems. Check out our contribution "Justification vs. Transparency: Why and How Visual Explanations in a Scientific Literature Recommender System" which is published in the Information Journal  as part of the Special Issue "Information Visualization Theory and Applications". The paper is available as open access here.

Interested to learn more about visual explanation in recommender systems? Check out our paper "Visualization for Recommendation Explainability: A Survey and New Perspectives" at the following link.

Our paper "Validation of the EDUSS Framework for Self-Actualization Based on Transparent User Models: A Qualitative Study" got accepted as a full research paper at the workshop on Explainable User Models and Personalized System (ExUM 2023) in conjunction with the conference on User Modeling, Adaptation and Personalization (ACM UMAP 2023). A preprint version of the paper is available here.

On April 28^th and 29^th, 2023, Clara Siepmann attended the Human-Centered Explainable AI Workshop at the CHI'23 conference. She presented our paper "Trust and Transparency in Recommender Systems". In this work, we argue that exploration and explanation can be seen as two ends of a spectrum, with both having the potential to help the user achieve transparency and therefore trust. We referred to the combination of both approaches as exploranation.  The paper can be found here.

On March 13, 2023, we co-organized the Fourth International Workshop on Human-Centered Learning Analytics (HCLA) at the LAK’23 conference. Shoeb Joarder co-moderated the table discussion on “How can we create trustworthy LA systems?”. Furthermore, he presented our paper "Towards a Flexible User Interface for ‘Quick and Dirty’ Learning Analytics Indicator Design". In this work, we present the development details of an intuitive and theoretically-sound Indicator Specification Cards (ISC) user interface that allows the low-cost design of learning analytics indicators. The paper can be found here. A demo of the ISC user interface in OpenLAP can be found here.

Join us for the Fourth International Workshop on "Human-Centred Learning Analytics (HCLA)" that we are co-organizing at the 13th International Learning Analytics and Knowledge (LAK'23) conference in Arlington, Texas, USA (March 13-17, 2023). The workshop will be fully online.

Human-centred learning analytics (HCLA) is an emerging subcommunity of learning analytics (LA) researchers and practitioners interested in creating reliable and trustworthy LA systems that amplify and augment the abilities of educational stakeholders and which are aligned to intentions, revealed preferences, ideal preferences, interests and values.

More details and call for short papers can be found on the workshop website.

Qurat Ul Ain has been selected as the "Best Presenter" from all the presentations in the 14th International Conference on Education Technology and Computers ICETC'22 which was held hybrid (in Barcelona and online) from October 28th to 30th, 2022. She presented a paper related to our CourseMapper project, titled: "Learning Channels to Support Interaction and Collaboration in CourseMapper". A preprint version of the paper is available here.

Our team continues to grow! We warmly welcome a new research assistant and Ph.D. student to our group. Clara Siepmann holds a master’s degree in Applied Cognitive and Media Science from the University of Duisburg-Essen. Clara is especially interested in human factors in computing systems and AI/machine learning. She will strengthen our group's research on trustworthy human-AI interaction.

Our paper "What if Interactive Explanation in a Scientific Literature Recommender System" has been accepted at the ACM RecSys 22 Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2022). The paper can be found here.

On July 5th, 2022 Shoeb Joarder attended the DataCampus Conference in Essen. The event was organized by the DataCampus UDE - an interdisciplinary association to promote data skills at the UDE. During the conference, impressions of the development of the field of data literacy and data science were given, practical examples for the promotion of data skills in the subjects were presented, and perspectives for the development and expansion of data literacy and data science offered at the UDE were jointly developed. Shoeb presented the results of our Interactive Data Exploration and Analytics (IDEA) lab course and Exploratory Learning Analytics Toolkit for Students (ELAS) project - a collection of Learning Analytics applications developed by students for students.

Mouadh Guesmi attended the 30th ACM Conference on User Modeling, Adaptation, and Personalization (UMAP'22) which was held hybrid (in Barcelona and online) from July 4th to 7th, 2022. He presented two papers on our ongoing work on explainable recommender systems and explanation design choices. One in the main conference entitled: "Is More Always Better? The Effects of Personal Characteristics and Level of Detail on the Perception of Explanations in a Recommender System" (link to the paper), and the second was in the ExUM workshop entitled "Explaining User Models with Different Levels of Detail for Transparent Recommendation: A User Study" (link to the paper).

Earlier News & Events