ArticleCureus2026
A Psychometric Comparison of Faculty-Authored and Large Language Model-Generated Multiple-Choice Questions in Endodontics.
Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and objective Designing high-quality multiple-choice questions (MCQs) in dental education is highly resource-intensive. While generative artificial intelligence (AI) offers a rapid, scalable solution for automated item generation, there is limited student-tested psychometric evidence comparing uncurated large language model (LLM) outputs with traditional faculty-authored items in advanced dental specialties like endodontics. This study aimed to evaluate and compare the psychometric properties, specifically the difficulty index, discrimination index, distractor effectiveness, and internal consistency reliability, of faculty-authored and uncurated, LLM-generated endodontic MCQs. Materials and methods Sixty single-best-answer MCQs (30 authored by experienced endodontic faculty and 30 generated by the LLM Claude Sonnet 5 (Anthropic, San Francisco, CA) using a standardized single-prompt framework) were distributed evenly across 10 core endodontic domains. The unified 60-item examination was digitally administered to a convenience sample of 100 dental interns in a single, randomized, 60-minute session. Psychometric parameters were computed using classical test theory, and scale reliabilities were evaluated using Cronbach's alpha (
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