Generative AI in the K–12 Formative Assessment Process: Enhancing Feedback in the Classroom

Mike Thomas Maksimchuk, Edward Roeber, Davie Store


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.
Anthology ID:
2025.aimecon-main.12
Volume:
Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers
Month:
October
Year:
2025
Address:
Wyndham Grand Pittsburgh, Downtown, Pittsburgh, Pennsylvania, United States
Editors:
Joshua Wilson, Christopher Ormerod, Magdalen Beiting Parrish
Venue:
AIME-Con
SIG:
Publisher:
National Council on Measurement in Education (NCME)
Note:
Pages:
107–110
Language:
URL:
https://aclanthology.org/2025.aimecon-main.12/
DOI:
Bibkey:
Cite (ACL):
Mike Thomas Maksimchuk, Edward Roeber, and Davie Store. 2025. Generative AI in the K–12 Formative Assessment Process: Enhancing Feedback in the Classroom. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers, pages 107–110, Wyndham Grand Pittsburgh, Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).
Cite (Informal):
Generative AI in the K–12 Formative Assessment Process: Enhancing Feedback in the Classroom (Maksimchuk et al., AIME-Con 2025)
Copy Citation:
PDF:
https://aclanthology.org/2025.aimecon-main.12.pdf