Effect of ChatGPT-Supported Education on Nursing Students' Aspiration Practice Knowledge and Motivation

Overview

This study was designed to examine the effects of a Chat Generative Pre-trained Transformer (ChatGPT)-integrated lecture on nursing students' knowledge, motivation, and knowledge retention related to endotracheal suctioning. The effects of this Artificial Intelligence (AI)-supported lecture were compared with those of a traditional lecture. ChatGPT, an AI-based language model, was used to provide interactive and personalized support during the learning process.

This study was designed to investigate the effects of ChatGPT-integrated education on nursing students' knowledge, motivation, and knowledge retention related to endotracheal suctioning practice. Additionally, the study aimed to compare this innovative approach with traditional teaching methods and to explore students' feelings and perceptions regarding both learning experiences. Endotracheal suctioning is a critical nursing procedure, especially in intensive care settings, to maintain airway patency and ensure adequate oxygenation. However, existing literature indicates that nursing students often find this procedure challenging and anxiety-inducing, with generally low levels of knowledge. AI tools like ChatGPT have been reported to enhance individualized learning, critical thinking, and problem-solving skills. Therefore, integrating ChatGPT into nursing education was considered to have the potential to improve theoretical knowledge acquisition and increase students' motivation toward the lecture. The study was conducted with third- and fourth-year nursing students enrolled in the undergraduate program at Izmir University of Economics, using a randomized controlled, quasi-experimental design. Knowledge, motivation levels, and knowledge retention were compared between control and intervention groups to evaluate the effect of ChatGPT-integrated education. Additionally, students' feedback regarding the educational experience was collected and analyzed. Data collection instruments included the Student Information Form, the Suctioning Knowledge Questionnaire, the ARCS (Attention, Relevance, Confidence, and Satisfaction) Motivation Learning Scale, and the Student Feedback Form. Lectures were planned separately for the control and intervention groups. The control group received traditional instruction methods such as presentations, video demonstrations, and discussions. In contrast, the intervention group accessed information and performed critical evaluations using ChatGPT. In a classroom setting, students discussed the information obtained via ChatGPT by comparing it with the latest published clinical guidelines on suctioning practice. Knowledge tests were administered before and after the lectures in both groups, and a follow-up knowledge test was conducted six weeks later to assess knowledge retention. Data analysis was performed using SPSS version 21. Frequency analysis was conducted for categorical data, descriptive statistics for numerical data, and parametric or non-parametric tests were applied for group comparisons. The level of significance was set at 0.05. The findings aimed to evaluate the effectiveness of the educational programs and demonstrate the impact of innovative teaching approaches. Ethical approval was obtained from the Ethics Committee for Health Sciences Research at Izmir University of Economics and the Dean's Office of the Faculty of Health Sciences. Participants were informed about the study, data confidentiality, and their right to withdraw at any time. All participants provided written informed consent. Necessary permissions were obtained for the use of validated measurement tools, and all course materials were shared with participants via the Blackboard platform.