5 papers
Distilling Black-Box Machine Learning into a Small, Self-Explaining Language Model for Learning Analytics
Chenguang Pan, Airui Meng, Youmi Suk
Learning analytics increasingly relies on flexible machine learning (ML), but the model opacity and the burden of deployment prevent these tools from reaching educational practice.…
Equality, Equity, and Causality in Fairness Research: A Commentary on Cheng (2026)
Youmi Suk
This is an invited commentary on the Psychometrika focus article "Fairness Issues and Evaluation in Psychometrics and AI/ML: What Can We Learn from Each Field?" by Ying Cheng (2026…
Separable Effects in Four-Arm and Two-Arm Designs
Chan Park, Youmi Suk
Robins and Richardson (2010) reformulated mediation analysis by decomposing treatments into multiple components and examining separable effects of each component. While this approa…
Generative AI-Based Monte Carlo Simulation for Method Evaluation Using Synthetic Multilevel Data
Youmi Suk, Chenguang Pan, Weixuan Xiao
The role of AI-generated synthetic data has recently been expanded to support realistic Monte Carlo simulations. However, guidance is limited on generating data with multilevel str…
Identifying Causes of Test Unfairness: Manipulability and Separability
Youmi Suk, Weicong Lyu
Differential item functioning (DIF) is a widely used statistical notion for identifying items that may disadvantage specific groups of test-takers. These groups are often defined b…