AI-Generated Formative Practice and Feedback: Performance Benchmarks and Applications in Higher Education

Rachel van Campenhout, Michelle Weaver Clark, Jeffrey S. Dittel, Bill Jerome, Nick Brown, Benny Johnson


Abstract
Millions of AI-generated formative practice questions across thousands of publisher etextbooks are available for student use in higher education. We review the research to address both performance metrics for questions and feedback calculated from student data, and discuss the importance of successful applications in the classroom to maximize learning potential.
Anthology ID:
2025.aimecon-main.36
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:
337–344
Language:
URL:
https://aclanthology.org/2025.aimecon-main.36/
DOI:
Bibkey:
Cite (ACL):
Rachel van Campenhout, Michelle Weaver Clark, Jeffrey S. Dittel, Bill Jerome, Nick Brown, and Benny Johnson. 2025. AI-Generated Formative Practice and Feedback: Performance Benchmarks and Applications in Higher Education. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers, pages 337–344, Wyndham Grand Pittsburgh, Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).
Cite (Informal):
AI-Generated Formative Practice and Feedback: Performance Benchmarks and Applications in Higher Education (van Campenhout et al., AIME-Con 2025)
Copy Citation:
PDF:
https://aclanthology.org/2025.aimecon-main.36.pdf