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Updated: Jul 9, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Comparative Analysis of NCLEX-RN Questions: A Duel Between ChatGPT and Human Expertise
Background:
Artificial intelligence (AI) has the potential to revolutionize nursing education. This study compared NCLEX-RN questions generated by AI and those created by nurse educators.
Method:
Faculty of accredited baccalaureate programs were invited to participate. Likert-scale items for grammar and clarity of the item stem and distractors were compared using Mann-Whitney U, and yes/no questions about clinical relevance and complex terminology were analyzed using chi-square. A one-sample binomial test with confidence intervals evaluated participants' question preference (AI-generated or educator-written). Qualitative responses identified themes across faculty.
Results:
Item clarity, grammar, and difficulty were similar for AI and educator-created questions. Clinical relevance and use of complex terminology was similar for all question pairs. Of the four sets with preference for one item, three were generated by AI.
Conclusion:
AI can assist faculty with item generation to prepare nursing students for the NCLEX-RN examination. Faculty expertise is necessary to refine questions written using both methods. [.
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