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Linguistics to LLMs: Teaching with and about Chatbots

Paper · 2026 · Ulrike Pado and Barbara Pampel

Summary

LLM-based methods are rapidly displacing older NLP techniques, so existing courses must be revised. The authors use this as a chance to add a chatbot as a learning aid. They describe how they rebuilt a three-week dialogue unit within a mandatory, German-taught AI course for Business Informatics bachelor students at Hochschule für Technik Stuttgart. The unit previously covered rule-based digital assistants. It now treats LLM-based chatbots and covers:

  • human dialogue theory (adjacency pairs, Gricean Maxims)
  • neural networks and the Transformer
  • embeddings
  • energy consumption and bias

They also deployed a tutorbot built with Retrieval-Augmented Generation (RAG) in Flowise on open-source LLMs. It is restricted to the course materials and also serves as a case study analysed in class. Questionnaires before and after instruction showed that students felt more confident about the technical basics. They also judged LLMs more realistically, attributing less objectivity and intelligence to them while recognising their human-like conversational behaviour. The paper offers a practical template for instructors making similar curriculum changes.

Key points

  • Setting: a 14-week mandatory AI class in the second year of a seven-semester Business Informatics program, taught with the Computer-based Learning (CBL) approach (self-paced videos, self-tests, exercises during in-person sessions).
  • The tutorbot "SKIT" uses RAG over the class slides. Its system prompt forbids answering beyond the retrieved context and supplies a fixed fallback reply when the slides contain no relevant information.
  • The authors' earlier work found the bot answered as intended in 95% of 328 user-bot interactions.
  • Usage: 280 interactions occurred during the LLM/chatbot weeks, and roughly 110 more were spread over the rest of the course, peaking before formative tests. Use was anonymous, and no student opted out of research analysis.
  • Stated limitations: the small number of students and classes limits generalisability, and fast-moving tools may quickly date the findings.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🎓University of KonstanzKonstanz · Germany17 works · 232 citations🎓Stuttgart Technical University of Applied SciencesStuttgart · Germany2 works · 1 citation

 Fields, topics and concepts

📚 Shelves 3The field of science this work belongs to (OpenAlex fields).Computer Science · 16,667 worksArtificial Intelligence · 16,194 worksInformation Systems · 1,437 works

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 3,320 worksDialogue systems · 624 works

Cite

Cite as Ulrike Pado and Barbara Pampel. 2026. Linguistics to LLMs: Teaching with and about Chatbots. Proceedings of the Seventh Workshop on Teaching Natural Language Processing (TeachNLP 2026).

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.18653/v1/2026.teachingnlp-1.4

@inproceedings{pado2026linguistics,
  title = {{Linguistics to LLMs: Teaching with and about Chatbots}},
  author = {Ulrike Pado and Barbara Pampel},
  booktitle = {Proceedings of the Seventh Workshop on Teaching Natural Language Processing (TeachNLP 2026)},
  year = {2026},
  doi = {10.18653/v1/2026.teachingnlp-1.4},
  url = {https://doi.org/10.18653/v1/2026.teachingnlp-1.4}
}

References

12 references, 4 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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