ChatGPT in nursing education. A cross-sectional descriptive study on attitude and preparedness of Undergraduate Nursing Students of SGT University

Authors

  • Nikita Badeshra
  • Riya
  • Muskan
  • Musaib
  • Banapriya Sahoo

Abstract

Background: ChatGPT is a chatbot that responds to user inputs with responses that resemble those of a human using natural language processing. This study was conducted to assess the attitude and preparedness regarding ChatGPT among undergraduate Nursing students of SGT University.
Objectives: This cross-sectional descriptive study aimed to find the correlation between attitude and preparedness regarding chatgpt among Nursing students.

METHODS: The study's instrument is a self structured questionnaire and the descriptive research design was used "to assess the perception and attitude of nursing student regarding chatGPT". The present study was conducted in SGT UNIVESITY Faculty of Nursing, Budhera in Gurugram. Non-probability purposive sampling technique was used to collect the data in present study.

RESULTS: In the present study vast majority of the samples i.e 72.40% were from the age under 18 years. Regarding the education status most of the respondents were in first year of their graduation i.e., of 54.0% and most of the samples were belongs to urban area 57.80% and 32. 90% respondents were belongs to rural area , 9.30% respondents were belongs to semi-urban area .Majority of samples are having 66.50% of previous knowledge and 33.50% are not having any previous knowledge regarding topic.

CONCLUSION: The study concluded that there is correlation between Attitude and Preparedness regarding ChatGPT among undergraduate score is -0.671 which is strong positive correlation.

 

KEYWORDS

ChatGPt , AI, Undergraduate Nursing Students.

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Published

2025-12-24

How to Cite

Nikita Badeshra, Riya, Muskan, Musaib, & Banapriya Sahoo. (2025). ChatGPT in nursing education. A cross-sectional descriptive study on attitude and preparedness of Undergraduate Nursing Students of SGT University. The Bioscan, 20(Special Issue-3), 2186–2197. Retrieved from https://thebioscan.com/index.php/pub/article/view/4661