collaborators

7 papers

cs.CL2026

Multimodal Item Parameter Estimation using Simulated Response Probabilitie

Christopher Ormerod, YoungKoung Kim

We present results from reconstructing multiple-choice model (MCM) and three-parameter logistic (3PL) model curves using a fine-tuned multimodal large language model (LLM) based on…

cs.CL2026

Detecting Alarming Student Verbal Responses using Text and Audio Classifier

Christopher Ormerod, Gitit Kehat

This paper addresses a critical safety gap in the use Automated Verbal Response Scoring (AVRS). We present a novel hybrid framework for troubled student detection that combines a t…

cs.CL2026

Reconstructing Item Characteristic Curves using Fine-Tuned Large Language Models

Christopher Ormerod

Traditional methods for determining assessment item parameters, such as difficulty and discrimination, rely heavily on expensive field testing to collect student performance data f…

cs.CL2025

SMART: Simulated Students Aligned with Item Response Theory for Question Difficulty Prediction

Alexander Scarlatos, Nigel Fernandez, Christopher Ormerod +2

Item (question) difficulties play a crucial role in educational assessments, enabling accurate and efficient assessment of student abilities and personalization to maximize learnin…

cs.CL2025

Long Context Automated Essay Scoring with Language Models

Christopher Ormerod, Gitit Kehat

Transformer-based language models are architecturally constrained to process text of a fixed maximum length. Essays written by higher-grade students frequently exceed the maximum a…

cs.CL2025

Automated Essay Scoring Incorporating Annotations from Automated Feedback Systems

Christopher Ormerod

This study illustrates how incorporating feedback-oriented annotations into the scoring pipeline can enhance the accuracy of automated essay scoring (AES). This approach is demonst…