Abstract:

The aim of this study is to examine how nursing students use ChatGPT during their studies and whether they find the use meaningful.

The use of ChatGPT in the Danish healthcare system is increasing and has shown promising results in reducing nurses' administration time and supporting their clinical decision-making.

Therefore, nursing education must teach students to use ChatGPT to prepare them for the work-life that awaits them when they work in a healthcare system where ChatGPT is becoming more prevalent.

The use of ChatGPT in nursing education is increasing and is still under development and has shown both opportunities and challenges. ChatGPT is available for free to students and has the potential to support nursing students in problem-solving various tasks during their studies, increase their perceived learning, and increase their digital understanding. However, ChatGPT has some limitations, as it must be used responsibly, and there is a risk of providing incorrect information.
Despite the increased use of ChatGPT in nursing education and among nursing students, there is a lack of knowledge about how nursing students use and adopt ChatGPT during their studies and whether they experience using ChatGPT as meaningful.

The study is designed as a case study involving 60 students from the first semester of nursing education in Silkeborg, Denmark. The case study setting is lectured in microbiology, where they have two teaching sessions and group work. The first teaching session is three lectures about infection, and the second session is about the immune system. During both sessions, there will be a lecture from the teacher and group work. The group work involves the students describing how an infection develops in the body and how the immune system reacts to the infection. During group work, the students must use ChatGPT and think about how they are prompting ChatGPT.

After the two lectures, the students were asked to rate their perceived learning and experience using ChatGPT on a scale from 1 to 10.

Based on their responses, ten students were selected for group interviews to ensure diverse experiences. Two groups of five students were formed, each with different experiences from the lectures.

The interviews were transcribed, and the data were analyzed using the Kvale and Brinkmann method, focusing on condensing and interpreting the students' perceived experience using ChatGPT.

Keywords:

Artificial intelligence, ChatGPT, education, nursing, students.