Dr.-Ing Tim Steuer

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Tim Steuer

Research Interests

  • Knowledge & Educational Technologies
  • Applications of Natural Language Processing in Education
    • Natural Language Generation in Education
    • Automatic Question Generation in Education
    • HCI and AI in Education


I am always looking for motivated students interested in writing a thesis in the field of educational technologies. If you are interested, have a look at open theses or contact me with your own idea.

Supervised Theses

  • Automatic Detection of Information Inconsistencies in Automatic Summaries (Master Thesis, 2021)
  • Investigating Cause and Effect Extraction as Content Selection Method for Automatic Question Generation (Bachelor Thesis, 2021)
  • An Empirical Comparison of German Neural Language Models through NLU Tasks (Master Thesis, 2021)
  • Investigating Automatic Answer Extraction Methods for Automatic Question Generation on the SQuAD Dataset and in Education (Master Thesis, 2021)
  • Design und Implementierung einer Evaluationsplattform für Fragegeneratoren im Bildungsbereich (Bachelor Thesis, 2020)
  • Generation of Multi-Language Domain-Specific Vocabulary from Unstructured Data (Master Thesis, 2020)
  • Detecting Question-Worthy Sentences with Extractive Summarization Methods (Master Thesis, 2020)
  • Text Simplification for the German Language via Neural Networks (Bachelor Thesis,2020)
  • Application of the Lottery Ticket Hypothesis in NLP and Early Pruning (Bachelor Thesis, 2020)
  • Automatically Generating Questions for Self-assessment of Reading Comprehension (Master Thesis, 2019)

Supervised Labs & Seminars

  • SLURM Rest API Task Scheduling (Lab, WS2021/22)
  • Index Extraction From Textbooks (Lab, SS2021)
  • Improving Language Tools Simple German Capabilities (Lab, WS2020/21)
  • Automatic Question Generation with Minified Language Models (Lab, WS2020/21)
  • Automatic Question Generation via Neural Machine Translation (Lab, WS2020/21)
  • Index Extraction From Textbooks (Lab, SS2020)
  • Handwritten Equation Solver: Supporting Teachers during Math Correction (Lab, WS2019/20)
  • Visualization of Knowledge Graphs of Book Contents (Lab, SS2019)
  • Quizbots in Education - (Seminar, SS2022)
  • Neural Question Generation Models - Focus on Usage in Education - (Seminar, WS2021/22)
  • Learning Analytics Tools in Higher Education (Seminar, WS2021)
  • Usability and AI (Seminar, WS2021)
  • Knowledge Representation in Intelligent Tutoring Systems (Seminar, SS2019)
  • Relation Extraction using Distant Supervision (Seminar, SS2019)
  • Neural Question Generation Methods (Seminar, SS2019)
  • Evidence in Learning Analytics (Seminar, SS2019)
  • Applications of Intelligent Tutoring Systems (Seminar, SS2019)


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