Using Artificial Intelligence in Nursing Education From the Eyes of Nursing Academics: An Online Cross‐Sectional Study

Abstract

In the realm of higher education, artificial intelligence (AI) has dramatically transformed numerous industries. It is vital to grasp the perspectives of nursing academics, as their insights significantly influence the integration of AI within educational frameworks, including nursing education. The incorporation of AI into nursing curricula remains a nascent endeavor, presenting both obstacles and promising avenues for those pioneering this innovative domain. This study described nursing academics′ views on using AI in nursing education in terms of their knowledge, attitudes and beliefs, emotional responses, perceived impact of AI in various fields, usefulness, advantages, and disadvantages. A quantitative research design was implemented utilizing an electronic survey using a cross‐sectional study with a convenience sample of 328 nursing academics recruited from different governmental and private universities. Nursing academics positively perceive the integration of AI in nursing education (M = 3.34; SE = 0.062; 95% CI [3.21–3.46]). Most nursing academics feel quite knowledgeable about AI‐integrated education, as reflected by the median score of 6.00/10.00, and they reported that the internet and social media were their primary sources of knowledge. In relation to knowledge, around 42% of nursing academics used AI tools while teaching students, namely, ChatGPT. Nursing academics generally hold favorable attitudes and beliefs about incorporating AI into nursing education (M = 3.35; SE = 0.043). However, they believed that machinery using AI is very expensive and resource‐intensive to build and maintain (M = 3.64; SE = 0.048), and AI may lead to losing jobs (M = 3.62; SE = 0.054). Caused by AI, most nursing academics had a feeling of curiosity and fear. The top disciplines benefiting from AI were education and medicine, thus considered a useful application in nursing education, as reflected with a median score of 7.00/10.00. Although AI was advantageous for teaching, learning, and evaluation processes, it came with a lack of a therapeutic relationship between students and teachers, as well as internet addiction. Comprehending the viewpoints of academics could enable educational institutions to incorporate AI into educational frameworks seamlessly; addressing the concerns of nursing academics while optimizing their learning experiences is an essential step in integrating AI into nursing education. While the topic is complex and warrants further study to enhance the learning experiences of nursing academics, the findings offer valuable insights for educators and higher education administrators. By understanding these perspectives, educational institutions could make informed decisions to leverage the benefits of AI while addressing its challenges, ensuring the successful implementation of AI technologies in nursing education. Additional research in this field could build upon the insights gleaned from the present study, further enhancing such AI integration.

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