Comparative Analysis of NCLEX-RN Questions: A Duel Between ChatGPT and Human Expertise

J Nurs Educ. 2023 Dec;62(12):679-687. doi: 10.3928/01484834-20231006-07. Epub 2023 Dec 1.

Abstract

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. [J Nurs Educ. 2023;62(12):679-687.].

MeSH terms

  • Artificial Intelligence
  • Education, Nursing*
  • Education, Nursing, Baccalaureate* / methods
  • Educational Measurement / methods
  • Humans
  • Licensure, Nursing
  • Students, Nursing*