Chair for Human-Centered Artificial Intelligence

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  3. Faculty of Applied Computer Science
  4. Institute of Computer Science
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  6. Human-Centered Artificial Intelligence
  7. Team
  8. Anan Schütt

Anan Schütt M.Sc.

Research Assistent
Chair for Human-Centered Artificial Intelligence
Phone: +49 821 598 2322
Email:
Room: 2016 ( N )
Address: Universitätsstraße 6a, 86159 Augsburg

Research Interests

  • Adaptive Education
  • Dynamic Difficulty Adjustment
  • Educational Data Mining
  • Interaction Design

Topics for Student Thesis

I'm happy to supervise Bachelor and Master theses. Following are the potential topics. I am also open to topics in the area that are particularly interesting to you!

 

  • Recommendation system for programming problems
  • Modelling difficulty levels of programming problems
  • Designing and generating explanations for chess puzzles
  • Imitating social chess games

Publications

2026 | 2024 | 2023

2026

Torben Soennecken, Anan Schütt, Björn Petrak and Elisabeth André. 2026. Adaptive generation of faded worked examples in vocational education. In Jelena Jovanovic, Bruce McLaren, Irene-Angelica Chounta, Olga Viberg, Alejandro Ortega-Arranz, Oleksandra Poquet (Eds.). Computer Supported Education: 16th International Conference, CSEDU 2024, Angers, France, May 2–4, 2024, revised selected papers. Springer, Cham, 1-18 DOI: 10.1007/978-3-032-21997-8_1
BibTeX | RIS | DOI

2024

Jean Vassoyan, Anan Schütt, Jill-Jênn Vie, Arun-Balajiee Lekshmi-Narayanan, Elisabeth André and Nicolas Vayatis. 2024. A pre-trained graph-based model for adaptive sequencing of educational documents. In NeurIPS 2024 Workshop FM-EduAssess - The First Workshop on Large Foundation Models for Educational Assessment, 15 December 2024, Vancouver, BC, Canada. CNRS, Paris, hal-04779162 DOI: 10.48550/arXiv.2411.11520
PDF | BibTeX | RIS | DOI | URL

Torben Soennecken, Anan Schütt, Björn Petrak and Elisabeth André. 2024. Bridging skills and scenarios: initial steps towards using faded worked examples as personalized exercises in vocational education. In Oleksandra Poquet, Alejandro Ortega-Arranz, Olga Viberg, Irene-Angelica Chounta, Bruce McLaren, Jelena Jovanovic (Eds.). Proceedings of the 16th International Conference on Computer Supported Education, May 2-4, 2024, in Angers, France. SciTePress, Setúbal, 43-53 DOI: 10.5220/0012565000003693
PDF | BibTeX | RIS | DOI

Anan Schütt, Tobias Huber, Jauwairia Nasir, Cristina Conati and Elisabeth André. 2024. Does difficulty even matter? Investigating difficulty adjustment and practice behavior in an open-ended learning task. In LAK '24: proceedings of the 14th Learning Analytics and Knowledge Conference, Kyoto, Japan, 18-22 March 2024. Association for Computing Machinery (ACM), New York, NY, 253-262 DOI: 10.1145/3636555.3636876
PDF | BibTeX | RIS | DOI

Anan Schütt, Tobias Huber and Elisabeth André. 2024. Estimating chess puzzle difficulty without past game records using a human problem-solving inspired neural network architecture. In Chang-Tien Lu Lu, Fusheng Wang, Bolong Zheng, Yifeng Gao (Eds.). 2024 IEEE International Conference on Big Data (BigData), 15-18 December 2024, Washington, DC, USA. Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, 8396-8402 DOI: 10.1109/bigdata62323.2024.10826087
PDF | BibTeX | RIS | DOI

2023

Anan Schütt, Tobias Huber, Ilhan Aslan and Elisabeth André. 2023. Fast dynamic difficulty adjustment for intelligent tutoring systems with small datasets. In Mingyu Feng, Tanja Käser, Partha Talukdar (Eds.). Proceedings of the 16th International Conference on Educational Data Mining, 11-14 July 2023, Bengaluru, India. International Educational Data Mining Society, 482-489
PDF | BibTeX | RIS | URL

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