News & Events

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).

We currently have one open position for a Research Assistant and PhD Student in trustworthy data science. Please send your application as one PDF file to Prof. Mohamed Chatti. Application deadline is July 7th 2022.

You might be interested in our Explore - Develop - Understand - Scrutinize - Socialize (EDUSS) framework for self-actualization goals of transparent user modeling. Check out our contribution "Interactive Visualizations of Transparent User Models for Self-Actualization: A Human-Centered Design Approach" which is published in the Multimodal Technologies and Interaction Journal  as part of the Special Issue "Explainable User Models". The paper is available as open access here.  

Our paper "Explaining User Models with Different Levels of Detail for Transparent Recommendation: A User Study" got accepted as a full research paper at the workshop on Explainable User Models and Personalized System (ExUM 2022) in conjunction with the conference on User Modeling, Adaptation and Personalization (ACM UMAP 2022). A preprint version of the paper is available here.

Our team is growing. We are happy to welcome a new research assistant and Ph.D. student to our group! Rawaa Alatrash holds a master's degree in Computer Science and Engineering from India with a scholarship. Rawaa is interested in Human-Centered AI and NLP. She will support our group's research on knowledge graphs for recommendation and explanation.

Our paper "Is More Always Better? The Effects of Personal Characteristics and Level of Detail on the Perception of Explanations in a Recommender System" got accepted as a full research paper at the conference on User Modeling, Adaptation and Personalization (ACM UMAP 2022). A preprint version of the paper is available here.

The results of the student projects developed in the Human-Computer Interaction (HCI) and Learning Analytics lecture course in the winter semester of 2021/22 are now available, including open-source codes, demos, and advertisement videos.

Teams of students in HCI participated in a two-months project to design and build a prototype around a set of user needs. The teams are tasked with milestones to move them towards a high-fidelity prototype as 
proof-of-concept that is presented in slides and demos at the end of the course. We were impressed with the quality of their projects.

Earlier News & Events