@inproceedings{hamalainen-leiviska-2025-nlg,
    title = "From {NLG} Evaluation to Modern Student Assessment in the Era of {C}hat{GPT}: The Great Misalignment Problem and Pedagogical Multi-Factor Assessment ({P}-{MFA})",
    author = {H{\"a}m{\"a}l{\"a}inen, Mika  and
      Leivisk{\"a}, Kimmo},
    editor = {H{\"a}m{\"a}l{\"a}inen, Mika  and
      Rie{\ss}ler, Michael  and
      Morooka, Eiaki V.  and
      Kharlashkin, Lev},
    booktitle = "Proceedings of the 10th International Workshop on Computational Linguistics for Uralic Languages",
    month = dec,
    year = "2025",
    address = "Joensuu, Finland",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/acl-awards-reasoning/2025.iwclul-1.1/",
    pages = "1--5",
    ISBN = "979-8-89176-360-9",
    abstract = "This paper explores the growing epistemic parallel between NLG evaluation and grading of students in a Finnish University. We argue that both domains are experiencing a Great Misalignment Problem. As students increasingly use tools like ChatGPT to produce sophisticated outputs, traditional assessment methods that focus on final products rather than learning processes have lost their validity. To address this, we introduce the Pedagogical Multi-Factor Assessment (P-MFA) model, a process-based, multi-evidence framework inspired by the logic of multi-factor authentication."
}