Natalie Hutchins


Fixing paper assignments

  1. Please select all papers that belong to the same person.
  2. Indicate below which author they should be assigned to.
Provide a valid ORCID iD here. This will be used to match future papers to this author.
Provide the name of the school or the university where the author has received or will receive their highest degree (e.g., Ph.D. institution for researchers, or current affiliation for students). This will be used to form the new author page ID, if needed.

TODO: "submit" and "cancel" buttons here


2025

pdf bib
Talking to Learn: A SoTL Study of Generative AI-Facilitated Feynman Reviews
Madeline Rose Mattox | Natalie Hutchins | Jamie J Jirout
Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress

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.