以STEAM跨領域思維促進護理教育創新──AI-NURSE創新教學模式建構

Promoting Innovative Nursing Education Through STEAM Interdisciplinary Thinking: Constructing an AI-NURSE Innovative Teaching Model

背景：人工智慧在醫療照護領域的重要性日益凸顯，護理教育需融合科學、技術、工程、藝術與數學的跨領域思維，以提升學生跨領域能力與人工智慧素養。
目的：本研究旨在探討護理科學生的STEAM（science, technology, engineering, arts, and mathematics）素養、學習興趣及職涯興趣之現況，並基此建構融合AI之創新護理教學模式，以提升學生跨領域能力與職場競爭力。
方法：採問卷調查法，以方便取樣邀請南部某專科學校護理科一年級全體270位學生自由參與本研究，總計回收有效問卷數259份。採用自編的STEAM素養、學習興趣及職涯興趣問卷收集資料，實施描述性統計、t檢定、相關分析及迴歸分析等資料分析，最後，以標準化Z分數矩陣視覺化呈現學生STEAM學習興趣及職涯興趣分布，以建立AI融入護理教育創新教學模式。
結果：護理科學生在STEAM素養表現良好，在倫理與社會責任、協作與溝通、問題解決等能力尤為突出。在STEAM學習興趣與職涯興趣方面，大多數學生對科學與藝術領域呈現正向肯定。STEAM素養、學習興趣與職涯興趣呈顯著正相關，且STEAM素養與學習興趣對職涯興趣有顯著預測能力。Z分數矩陣分析呈現，工程、數學領域在低學習/低職涯興趣象限；值得注意科技領域在低學習/高職涯興趣象限。
結論／實務應用：本研究提出以學生為本之AI-NURSE（artificial intelligence-navigate, utilize, reflect, solve, execute）創新教學模式，並提出評估準則，為AI融入護理教育提供實務參考，促進照護專業人才培育，為未來智慧醫療科技的發展奠定基礎。

Background: 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.
Purpose: 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.
Methods: 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.
Results: 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.
Conclusion/ Implications for Practice: 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.