@inproceedings{mattox-etal-2025-talking,
    title = "Talking to Learn: A {S}o{TL} Study of Generative {AI}-Facilitated Feynman Reviews",
    author = "Mattox, Madeline Rose  and
      Hutchins, Natalie  and
      Jirout, Jamie J",
    editor = "Wilson, Joshua  and
      Ormerod, Christopher  and
      Beiting Parrish, Magdalen",
    booktitle = "Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress",
    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-wip.14/",
    pages = "117--124",
    ISBN = "979-8-218-84229-1",
    abstract = "Structured Generative AI interactions have potential for scaffolding learning. This Scholarship of Teaching and Learning study analyzes 16 undergraduate students' Feynman-style AI interactions (N=157) across a semester-long child-development course. Qualitative coding of the interactions explores engagement patterns, metacognitive support, and response consistency, informing ethical AI integration in higher education."
}