@inproceedings{maksimchuk-etal-2025-generative,
    title = "Generative {AI} in the K{--}12 Formative Assessment Process: Enhancing Feedback in the Classroom",
    author = "Maksimchuk, Michael  and
      Roeber, Edward  and
      Store, Davie",
    editor = "Wilson, Joshua  and
      Ormerod, Christopher  and
      Beiting Parrish, Magdalen",
    booktitle = "Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers",
    month = oct,
    year = "2025",
    address = "Wyndham Grand Pittsburgh, Downtown, Pittsburgh, Pennsylvania, United States",
    publisher = "National Council on Measurement in Education (NCME)",
    url = "https://preview.aclanthology.org/bulk-corrections-2025-11-25/2025.aimecon-main.12/",
    pages = "107--110",
    ISBN = "979-8-218-84228-4",
    abstract = "This paper explores how generative AI can enhance formative assessment practices in K{--}12 education. It examines emerging tools, ethical considerations, and practical applications to support student learning, while emphasizing the continued importance of teacher judgment and balanced assessment systems."
}