Kathrin Seßler
Research Assistant, PhD student
Technical University of Munich
TUM School of Social Sciences and Technology
Chair: Human-Centered Technologies for Learning
Visiting address:
Marsstraße 20-22
80335 München
Postal address:
Arcisstraße 21
80333 München
Room: 254
Office Hours: by Appointment
Tel.: +49 89 289 24328
E-Mail: kathrin.sessler@tum.de
Career development
- 2022 – now: PhD Candidate at TU Munich, Germany
- 2019 – 2022: M.Sc. in Computer Science at University of Tübingen, Germany
- 2015 – 2019: B.Sc. in Computer Science at OTH Regensburg, Germany
Outreach Activities
- 06/2024: Presentation of the AI-Tutor PEER at the course "AI in German writing education"
- 05/2024: Workshop at the KI-Forum.Schule on the topic "ChatGPT in the classroom: AI-assisted writing in education"
- 04/2024: Radio interview at "Satz mit X - Der Mathemix" on the topic "AI - Dangerous or Genius?", Podcast available
- 12/2023: Talk as part of the lecture series of the Max-Weber-Programms, "Lerning with Generative AI"
- 12/2023: Key Note at the teaching programm "Shaping the Future" on the topic "How is AI changing society?"
- 11/2023: Workshop at the padagogical day "AI and School" in Abensberg, "AI-assisted writing: How PEER modernizes German Lessons"
- 11/2023: Workshop at the Roland-Berger-Stiftung network meeting, "Increasing educational equity through generative AI?"
- 11/2023: Panel discussion at the GesellschaftsRAUM, "The digital divide: On social inequality in the digitalized society"
- 10/2023: Panel discussion at the media days Munich, "Can AI be creative?"
- 09/2023: Implus talk at the "LunchTalk ChatGPT" of the GWMT Annual Meeting 2023
- 07/2023: Participation in the panel discussion at the event "Human - Machine- Interaction" in the school experiment KI@school.
- 07/2023: Presentation of the AI-Tutor PEER at the conference of the school experiment "Prüfungskultur innovativ".
- 06/2023: Radio interview at the children's program Kurzwelle of Radio Feierwerk on the topic "How does ChatGPT work?". Podcast available.
- 03/2023: Introduction talk at the event "Do you still write yourself? How AI is changing our education system" at the Bayrischen Akademie der Wissenschaften. Podcast available.
- 03/2023: Radio interview at the Campus Magazin of the BR in the episode "Does draft legislation endanger young researchers from Germany?". Podcast available.
Research Interests
- Machine Learning / Deep Learning
- Tabular Data Generation
- Natural Language Processing with Transformer Models
- Large Language Models in Education
Publications
- Seßler K., Kepir O., Kasneci E. (2024). Enhancing Student Motivation through LLM-Powered Learning Environments: A Comparative Study.
- Bewersdorff, A., Hartmann, C., Hornberger, M., Seßler, K., Bannert, M., Kasneci, E., ... & Nerdel, C. (2024). Taking the Next Step with Generative Artificial Intelligence: The Transformative Role of Multimodal Large Language Models in Science Education. arXiv preprint arXiv:2401.00832. https://arxiv.org/abs/2401.00832
- Bewersdorff A., Seßler K., Baur A., Kasneci E. & Nerdel C. (2023). Assessing student errors in experimentation using artificial intelligence and large language models: A comparative study with human raters, Computers and Education: Artificial Intelligence. https://doi.org/10.1016/ j.caeai.2023.100177.
- Seßler, K., Xiang, T., Bogenrieder, L., & Kasneci, E. (2023, August). PEER: Empowering Writing with Large Language Models. In European Conference on Technology Enhanced Learning (pp. 755-761). Cham: Springer Nature Switzerland. https://link.springer.com/chapter/10.1007/978-3-031-42682-7_73
- Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., ... & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://www.sciencedirect.com/science/article/pii/S1041608023000195
- Borisov, V., Seßler, K., Leemann, T., Pawelczyk, M., & Kasneci, G. (2022, September). Language Models are Realistic Tabular Data Generators. In The Eleventh International Conference on Learning Representations. https://arxiv.org/abs/2210.06280
- Borisov, V., Leemann, T., Seßler, K., Haug, J., Pawelczyk, M., & Kasneci, G. (2022). Deep neural networks and tabular data: A survey. IEEE Transactions on Neural Networks and Learning Systems. https://ieeexplore.ieee.org/abstract/document/9998482
Also, check Google Scholar for an up-to-date list.
