Nursing Students' Attitudes Towards Artificial Intelligence and Exam Anxiety Levels

Overview

This study was planned to determine nursing students' attitudes towards artificial intelligence and test anxiety levels after using ChatGPT and Google Bard in their education. The study will be carried out in accordance with the research feature of quasi-experimental, pretest-posttest, with 3rd and 4th year nursing students studying at Sinop University Faculty of Health Sciences in the 2023-2024 fall academic year. The research groups are named as follows; Experimental Group: The group that will receive ChatGPT and Google Bard training, Control Group: The group that will not receive ChatGPT and Google Bard training, in other words, the 3rd year students of the nursing department will be referred to as the control group, and the 4th year students will be the experimental group. Educational content; ChatGPT and Google Bard training for senior students of the Faculty of Health Sciences who volunteered to participate in the study was provided by Dr. Lecturer It will be given by member Yasemin Özyer Güvener. After the training is completed, students will be asked to use generative artificial intelligence for educational purposes. During the posttest implementation of the study (one week before the final exams), data collection tools will be applied again to students who continue to volunteer to participate in the research. Key words: nursing students, test anxiety, generative artificial intelligence, ChatGPT, Google Bard

In health sciences education, generative artificial intelligence programs, namely ChatGPT and Google Bard, can be used, for example, to create different and realistic clinical stories, to ensure that health sciences students receive instant help in unique clinical cases, and to improve students' communication skills (Sallam, 2023). Additionally, generative AI can assist health science students in self-learning and group work. The usefulness of productive artificial intelligence and the individualized interaction it provides have made it accepted as a source of motivation for students (Connor 2023; Kosak et al., 2023; Gilson et al., 2023; Khan et al., 2023). Additionally, educators can promote deep learning by teaching students to critically evaluate information generated by generative AI, make informed decisions about the accuracy of information, and think about their responsibilities in the use of generative AI (Sun et al., 2023). For example, as homework, health sciences students may be asked to create an evidence-based protocol for stress management. Students can use generative AI to prepare the protocol. Thus, students can spend their time learning subject-related concepts or gaining knowledge about various topics. In recent years, rapid developments in artificial intelligence technologies have affected all social systems, including economy, politics, science and education (Luan et al., 2020, Stephanidis et al., 2019). However, people are often unaware of the existence of artificial intelligence applications (Tai, 2020). Gansser and Reich (2021) define artificial intelligence as a technology developed simply to facilitate human life and assist people in certain scenarios. In fact, artificial intelligence is used in many useful contexts, such as diagnosing diseases, protecting environmental resources, predicting natural disasters, improving education, preventing violent acts, and reducing risks in the workplace (Brooks, 2019). Test anxiety is defined as the unpleasant feelings and emotional states experienced by the student during an exam or any evaluation. It is stated that test anxiety negatively affects the academic success of the student.