Showing 1 - 2 of 2 Research Library Publications
Posted: | Daniel Jurich, Chunyan Liu

Applied Measurement Education: Volume 36, Issue 4, Pages 326-339

 

This study examines strategies for detecting parameter drift in small-sample equating, crucial for maintaining score comparability in high-stakes exams. Results suggest that methods like mINFIT, mOUTFIT, and Robust-z effectively mitigate drifting anchor items' effects, while caution is advised with the Logit Difference approach. Recommendations are provided for practitioners to manage item parameter drift in small-sample settings.
 

Posted: | Martin G. Tolsgaard, Martin V. Pusic, Stefanie S. Sebok-Syer, Brian Gin, Morten Bo Svendsen, Mark D. Syer, Ryan Brydges, Monica M. Cuddy, Christy K. Boscardin

Medical Teacher: Volume 45 - Issue 6, Pages 565-573

 

This guide aims aim to describe practical considerations involved in reading and conducting studies in medical education using Artificial Intelligence (AI), define basic terminology and identify which medical education problems and data are ideally-suited for using AI.