An analysis of an item-response strategy based on knowledge retrieval
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Updated: Feb 8, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Minjeong Jeon1, Paul De Boeck2
1Department of Education, University of California, Los Angeles, 3141 Moore Hall, 457 Portola Avenue, Los Angeles, CA, 90024, USA. mjjeon@ucla.edu.
Abstract:
In this paper, we hypothesize a type of item-response strategy based on knowledge retrieval. Knowledge retrieval-based item-solving strategy may emerge when: (1) one's regular ability is not utilized, (2) fast response time is not necessarily applied, and (3) the accuracy rate may be higher than the expected level due to chance. We propose to utilize item-response time with a finite-mixture IRT modeling approach to illustrate a potentially knowledge retrieval-based item-solving strategy. The described strategy is illustrated through the utilization of a low-stakes assessment data administered under no time constraint. A simulation study is provided to evaluate the accuracy of the empirical results.
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