[Promoting Innovative Nursing Education Through STEAM Interdisciplinary Thinking: Constructing an AI-NURSE Innovative...

The role of artificial intelligence (AI) in medical care has become increasingly prominent. There is an urgent need to integrate the cross-disciplinary thinking of science, technology, engineering, arts, and mathematics (STEAM) into nursing education to strengthen cross-disciplinary competencies and AI literacy in students.

This study was developed to explore the current status of STEAM literacy, learning interest, and career interest among nursing students. Based on the findings, a targeted, innovative nursing teaching model that integrates AI was developed to improve the cross-disciplinary competencies and workplace competitiveness of these students.

A self-developed questionnaire on STEAM literacy, learning interest, and career interest was used to collect study data. All 270 first-year nursing students from a junior college in southern Taiwan were invited to participate on a voluntary basis, with 259 valid questionnaires collected. Descriptive statistics, t-tests, correlation analysis, and regression analysis were conducted to examine the predictive power of STEAM literacy and learning interest on career interest. A standardized Z-score matrix was adopted to present the distribution of STEAM learning and career interests visually, establishing an innovative teaching model that helps integrate AI into nursing education.

The participants performed well in STEAM literacy, particularly in terms of ethics and social responsibility, collaboration and communication, and problem solving competencies. The survey on STEAM learning interest and STEAM career interest revealed most of the participants exhibited significantly positive affirmation of the science and art fields. STEAM literacy, learning interest, and career interest were found to be significantly positively correlated, with STEAM literacy and STEAM learning interest identified as significant predictors of STEAM career interest. Finally, the results of the Z-score matrix analysis indicate engineering and mathematics fields are associated with the low learning-interest / career-interest quadrant, while the science and technology field is associated with the low learning-interest / high career-interest quadrant.

The innovative student-centered AI-NURSE (artificial intelligence-navigate, utilize, reflect, solve, execute) teaching model proposed in this study provides specific evaluation criteria as a practical reference for integrating AI into nursing education. The findings may be used to promote the cultivation of nursing professionals, laying the foundation for the future development of smart medical technology.