@inproceedings{maksimchuk-etal-2025-generative,
    title = "Generative {AI} in the K{--}12 Formative Assessment Process: Enhancing Feedback in the Classroom",
    author = "Maksimchuk, Mike Thomas  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/ingest-emnlp/2025.aimecon-main.12/",
    pages = "107--110",
    ISBN = "979-8-218-84228-4",
    abstract = "This paper explores how generative AI can enhance K{--}12 formative assessment by improving feedback, supporting task design, fostering student metacognition, and building teacher assessment literacy. It addresses challenges of equity, ethics, and implementation, offering practical strategies and case studies to guide responsible AI integration in classroom formative assessment practices."
}