Ideas in Testing Research Seminar Schedule, November 14, 2025

Coffee & Networking (9:00 — 9:50)

Welcome and Introductions (9:50 — 10:00)

DIF, fit, and bias (10:00 — 11:00)

An Open Discussion on Fuzzy Logic and Differential Item Functioning — Walton Ferguson & Ying Cheng (University of Notre Dame) abstract

Psychometric Modeling of Help Requests and the Role of Person-Item Interactions — Daniel Bolt, Lionel Meng, Leonard Tetzlaff, & Frank Goldhammer (University of Wisconsin–Madison) abstract

Modeling of Assessment Reports: Uncovering Gender Bias in Police Officer Screening — Jung-Shan Liang, Anushka Patil, Hudson Pfister, Tony H. Lam, Maxwel G. Porter, & Scott B. Morris (Illinois Institute of Technology) abstract

Break (11:00 — 11:15)

Predicting and understanding item performance (11:15 — 12:15)

Targeted Fine-Tuning of Transformer Encoders for Content-Based Item Parameter Prediction — Yuxiao Zhang, Yanyan Fu, & Kyung (Chris) T. Han (Purdue University) abstract

Data, theory, and methods for understanding item difficulty — Kirk Becker & Paul Jones (Pearson) abstract

Automating item difficulty strata classifications — Alan Mead (Certiverse) & Chenxuan Zhou (Talent Algorithms) abstract slides

Lunch (12:15 — 1:00)

Applications of AI (1:00 — 2:00)

Item review using LLMs — Reese Butterfuss (Certiverse) abstract

Template Based Automated Item Generation with Large Language Model Assistance — Guanchao (Samuel) Huang & Cheng Liu, (University of Notre Dame) abstract

Evaluating the Reliability of Generative AI in Scoring Constructed Responses in Physics — Xiuxiu Tang, G. Alex Ambrose, & Ying Cheng (University of Notre Dame) abstract

Break (2:00 — 2:10)

Psychometric methods (2:10 — 2:50)

Impact of informed starting value on longitudinal computer adaptive tests in PROMIS assessments — Michael Bass, Scott Morris, & Tony Lam (Illinois Institute of Technology) abstract

Mixture Item Response Model as Unsupervised Classifier: Preknowledge Detection — Tai Sun Jeong & James A. Wollack abstract

Open Discussion: How will AI affect psychomeric theory and practice in the next three years? (2:50 — 3:10)

Cognitive Diagnostic Models (3:10 — 4:10)

Adaptive CUSUM Charts for Real-Time Detection of Item Parameter Drift in CD-CAT — Jing Huang & Hua-Hua Chang, (Purdue University) abstract

Estimation of High-Dimensional Higher-Order Cognitive Diagnosis Model: A Composite Marginal Likelihood Approach — Minho Lee & Yon Soo Suh, (University of Notre Dame) abstract

Detecting Aberrant Responses in CDM: Comparing Person-Fit Statistics With Empirical and Fixed Critical Values — Audrey Filonczuk & Ying Cheng, (University of Notre Dame) abstract

Closing comments (4:10)

Questions about the seminar may be directed to Alan Mead (), Scott Morris (), or Kirk Becker (). We hope you will join us.

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