@inproceedings{farhana-etal-2026-theory,
    title = "Theory of Mind and Application in Educational Context",
    author = "Farhana, Effat  and
      Zainab, Maha  and
      Wang, Qiaosi  and
      Mireshghallah, Niloofar  and
      van der Meulen, Ramira  and
      van Duijn, Max",
    editor = "Kochmar, Ekaterina  and
      Alhafni, Bashar  and
      Bann{\`o}, Stefano  and
      Bexte, Marie  and
      Burstein, Jill  and
      Horbach, Andrea  and
      Laarmann-Quante, Ronja  and
      Tack, Anais  and
      Yaneva, Victoria  and
      Yuan, Zheng",
    booktitle = "Proceedings of the 21st Workshop on Innovative Use of {NLP} for Building Educational Applications ({BEA} 2026)",
    month = jul,
    year = "2026",
    address = "San Diego, California, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.bea-1.1/",
    pages = "1--6",
    ISBN = "979-8-89176-409-5",
    abstract = "This tutorial examines the integration of Theory of Mind (ToM) into AI-driven tutoring systems, with a focus on how large language models (LLMs) can represent learners' cognitive and emotional states to enable adaptive, personalized feedback. Participants will learn foundational ToM concepts from cognitive science and psychology and how these ideas can be operationalized in AI systems. We discuss mutual ToM, in which both tutors and learners model each other{'}s mental states, and address challenges including misconception detection, metacognitive modeling, and privacy in data-driven tutoring. The tutorial also includes hands-on demonstrations of machine ToM in programming education using benchmark datasets such as CS1QA and CodeQA. By combining theoretical foundations, empirical insights, and practical exercises, this tutorial will provide an overview of designing human-centered, ethically aware, and cognitively informed AI tutoring systems."
}