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Item Difficulty and Response Time Prediction with Large Language Models: An Empirical Analysis of USMLE Items
Download2024-06-20
Bulut, O., Gorgun, G., Tan, B.
This paper summarizes our methodology and results for the BEA 2024 Shared Task. This competition focused on predicting item difficulty and response time for retired multiple-choice items from the United States Medical Licensing Examination® (USMLE®). We extracted linguistic features from the item...
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Understanding response processes in noncognitive measures with explanatory item response modeling
Download2019-04-01
A common criticism of noncognitive measures is the potential for cultural influences in response processes. This study employs explanatory item response modeling to understand the effects of various demographic variables on response processes, using a measure of social support. Results support...