M. Sc. Mouadh Guesmi

M. Sc. Mouadh Guesmi

Office location: LE 409

Office hours: By appointment only

Phone : +49 (0) 203 379-1333

E-Mail: mouadh.guesmi@stud.uni-due.de

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Short CV

Since we are living in the era of advanced technologies and digitalization, I decided to study computer science in the higher institute of computer science and management in Kairouan, Tunisia. After obtaining my bachelor's degree in computer science, I opted for a research master in intelligent information systems at the same institute where I covered several subjects in depth like Learning Technologies, Game-Based Learning, Personalization, User Modeling, Educational Data Mining, and Learning Theories. Since February 2019, I'm a research assistant and PhD student in the Social Computing Group, Department of Computer Science and Applied Cognitive Science (INKO), Faculty of Engineering at the University of Duisburg-Essen, Germany.

Research Interests

  • Human-Centred Interface
  • User Modeling and Personalization
  • Explainable Recommender Systems
  • Information Visualization

Academic Qualifications

Sep 2014 - Apr 2018
Master in Intelligent Information Systems
University of Kairouan, Higher Institute of Computer Science and Management, Tunisia

Sep 2011 - May 2014
Bachelor in Fundamental Computer Science
University of Kairouan, Higher Institute of Computer Science and Management, Tunisia

Work Experience

since Feb 2019
Research assistant and PhD student in the Social Computing Group at the University of Duisburg-Essen, Germany

Publications

  • Mouadh Guesmi, Mohamed Amine Chatti, Laura Vorgerd, Shoeb Joarder, Qurat Ul Ain, Thao Ngo, Shadi Zumor, Yiqi Sun, Fangzheng Ji, Arham Muslim
    Input or Output: Effects of Explanation Focus on the Perception of Explainable Recommendation with Varying Level of Details  Inproceedings In Proceedings of the 8th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS ’21)
      
  • Mohamed Amine Chatti, Volkan Yücepur, Arham Muslim, Mouadh Guesmi, Shoeb Joarder
    Designing Theory-Driven Analytics-Enhanced Self-Regulated Learning Applications  Book Chapter  Forthcoming
    In M. Sahin & D. Ifenthaler (Eds.), Visualizations and Dashboards for Learning Analytics. Cham: Springer.
  • Mouadh Guesmi, Mohamed Amine Chatti, Laura Vorgerd, Shoeb Joarder, Shadi Zumor, Yiqi Sun, Fangzheng Ji, Arham Muslim
    On-demand Personalized Explanation for Transparent Recommendation  Inproceedings
    In Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization (UMAP ’21 Adjunct).
      
  • Mohamed Amine Chatti, Fangzheng Ji, Mouadh Guesmi, Arham Muslim, Ravi Kumar Singh, and Shoeb Ahmed Joarder
    SIMT: A Semantic Interest Modeling Toolkit  Inproceedings
    In Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization (UMAP ’21 Adjunct).
      
  • Mouadh Guesmi, Mohamed Amine Chatti, Yiqi Sun, Shadi Zumor,Fangzheng Ji, Arham Muslim, Laura Vorgerd, and Shoeb Ahmed Joarder
    Open, Scrutable and Explainable Interest Models for Transparent Recommendation  Inproceedings
    In Companion Proceedings of the 26th International Conference on Intelligent User Interfaces (IUI'21).
      
  • Mohamed Amine Chatti, Arham Muslim, Mouadh Guesmi, Florian Richtscheid, Dawood Nasimi, Amin Shahin, and Ritesh Damera
    How to Design Effective Learning Analytics Indicators? A Human-Centered Design Approach  Inproceedings
    In Proceedings of the Fifteenth European Conference on Technology Enhanced Learning (ECTEL'20), pp. 303-317, 2020.
      
  • Mohamed Amine Chatti, Arham Muslim, Manpriya Guliani, Mouadh Guesmi
    The LAVA Model: Learning Analytics Meets Visual Analytics  Book Chapter  
    In D. Ifenthaler & D. Gibson (Eds.), Adoption of Data Analytics in Higher Education Learning and Teaching (pp. 71-93). Cham: Springer.
      
  • Arham Muslim, Mohamed Amine Chatti, Mouadh Guesmi
    Open Learning Analytics: A Systematic Literature Review and Future Perspectives  Book Chapter 
    In N. Pinkwart & S. Liu (Eds.), Artificial Intelligence Supported Educational Technologies (pp. 3-29). Cham: Springer.
      
  • Mouadh Guesmi, Mohamed Amine Chatti, Arham Muslim
    A Review of Explanatory Visualizations in Recommender Systems  Inproceedings
    In Companion Proceedings of the 10th International Conference on Learning Analytics & Knowledge (LAK'20), pp. 480-491, 2020