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

• Published in: The Journal of nursing education Vol. 62; no. 12; pp. 679 - 687
• Main Authors: Cox, Rachel L., Hunt, Karen L., Hill, Rebecca R.
• Format: Journal Article
• Language: English
• Published: Thorofare SLACK INCORPORATED 01-12-2023
• Subjects: Artificial intelligence; Blooms taxonomy; Case Studies; Chatbots; Critical thinking; Data Analysis; Educational Resources; Feedback; Learning; Learning Processes; Licensing examinations; Nurses; Nursing care; Nursing education; Students; Teachers; Teaching Methods; Thinking Skills; United States > US
• ISSN: 0148-4834; 1938-2421
• DOI: 10.3928/01484834-20231006-07

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.]