Next Skill Evaluation & Targeting via Map-Based Analytics

Jeff Hoover, Amy Clark


Abstract
This study integrates assessment data with learning maps, using a neural network to recommend individualized next skills for instruction and assessment. Results indicate high-certainty, expert-validated recommendations, with empirical support for foundational assumptions. This demonstrates the potential for AI to support more personalized learning-maps-based instruction and assessment.
Anthology ID:
2026.aimecon-sessions.33
Volume:
Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Coordinated Session Papers
Month:
October
Year:
2026
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:
306–311
Language:
URL:
https://aclanthology.org/2026.aimecon-sessions.33/
DOI:
Bibkey:
Cite (ACL):
Jeff Hoover and Amy Clark. 2026. Next Skill Evaluation & Targeting via Map-Based Analytics. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Coordinated Session Papers, pages 306–311, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).
Cite (Informal):
Next Skill Evaluation & Targeting via Map-Based Analytics (Hoover & Clark, AIME-Con 2026)
Copy Citation:
PDF:
https://aclanthology.org/2026.aimecon-sessions.33.pdf