An Assessment of Nursing Students’ Utilization and Intent to Adopt Artificial Intelligence in a Selected Higher Education Institution: Basis for Proposed Guidelines on Proper Utilization of Artificial Intelligence

The integration of AI in healthcare education is accelerating, offering innovative learning tools such as virtual simulations, adaptive learning platforms, and AI-assisted writing. Despite the benefits, gaps remain in nursing students’ awareness, readiness, and responsible use of AI. Ethical concerns, data privacy, and over-reliance on AI further underscore the need for structured integration in nursing curricula. This study aimed to assess the level of utilization and intent to adopt Artificial Intelligence (AI) among nursing students in a selected higher education institution. It also sought to propose guidelines for the proper use of AI in nursing education based on the findings. The study employed descriptive correlational quantitative design. Data was gathered from 482 nursing students at Mary Chiles College using a validated survey instrument. Stratified random sampling was applied. The instrument covered demographic profiles, AI usage levels, intent to adopt AI, and ethical assessments. Data were analyzed using statistical methods to determine correlations and significant differences among variables. The overall level of AI utilization was rated as "Moderate", with AI-assisted research and AI-enhanced writing being the most frequently used applications. The intent to adopt AI was also moderate, with readiness and awareness showing relatively higher means. Ethical awareness in AI use was likewise moderate, especially on human oversight and critical thinking. Pearson correlation revealed significant relationships between AI utilization and extent of academic use, intent to adopt AI, and responsible AI usage. An independent t-test showed a significant difference in AI utilization levels across student groups based on their intent to adopt AI. It was found that nursing students moderately engage with AI, showing potential for broader adoption, especially in academic applications. The study supports the development of institutional guidelines to enhance AI literacy, address ethical concerns, and promote responsible use in nursing education.

Artificial Intelligence, Nursing Students, AI Utilization, Intent to Adopt, AI Literacy

1. Ahmad, S. F., Alam, M. M., Rahmat, Mohd. K., Mubarik, M. S., & Hyder, S. I. (2022). Academic and Administrative Role of Artificial Intelligence in Education. Sustainability, 14(3), 1101. https://doi.org/10.3390/su14031101 Date Retrieved: May 30, 2025 [Google Scholar] [Crossref]

2. Akca Sumengen, A., Ozcevik Subasi, D., & Cakir, G. N. (2024). Nursing students’ attitudes and literacy toward artificial intelligence: a cross-sectional study. Teaching and Learning in Nursing. https://doi.org/10.1016/j.teln.2024.10.022. Date Retrieved: December 23, 2024 [Google Scholar] [Crossref]

3. Anna Cañas-Llamas (2024). UPOU Releases Guidelines on AI Use for Teaching and Learning - University of the Philippines Open University. University of the Philippines Open University. https://www.upou.edu.ph/news/upou-releases-guidelines-on-ai-use-for-teaching-and learning/?fbclid=IwZXh0bgNhZW0CMTEAAR3TfTXJav6Xxrvp9wvuatDHyVoS3D1fmp8dvRO21zVBw5xmO1TsZ3nv4M_aem_dm5J05g8vL4hznnzcixE-A Date Retrieved: December 20, 2024 [Google Scholar] [Crossref]

4. Asirit, B. L., & Hua, J. H. (2023). Converging perspectives: Assessing AI readiness and utilization in Philippine higher education. ResearchGate; Polaris Global Research Organization Inc.https://www.researchgate.net/publication/376702456_Converging_perspectives_Assessing_AI_readiness_and_utilization_in_Philippine_higher_education Date Retrieved: March 28, 2025 [Google Scholar] [Crossref]

5. Benfatah, M., Abdelghafour Marfak, Saad, E., Abderraouf Hilali, Chakib Nejjari, & Ibtissam Youlyouz-Marfak. (2024). Assessing the efficacy of ChatGPT as a virtual patient in nursing simulation training: A study on nursing students’ experience. Teaching and Learning in Nursing. https://doi.org/10.1016/j.teln.2024.02.005 Date Retrieved: December 23, 2024 [Google Scholar] [Crossref]

6. Bevans, R. (2020). Multiple Linear Regression | A Quick and Simple Guide. Scribbr. https://www.scribbr.com/statistics/multiple-linear-regression/ Date Retrieved: January 22, 2025 [Google Scholar] [Crossref]

7. Buchanan, C., Howitt, M. L., Wilson, R., Booth, R. G., Risling, T., & Bamford, M. (2021). Predicted Influences of Artificial Intelligence on Nursing Education: Scoping Review. JMIR Nursing, 4(1), e23933. https://doi.org/10.2196/23933. Date Retrieved: December 20, 2024 [Google Scholar] [Crossref]

8. Carroll, W. M. (2023). Generative AI in clinical practice and operations. Nursing Management, 54(10), 56. https://doi.org/10.1097/nmg.0000000000000056. Date Retrieved: December 23, 2024 [Google Scholar] [Crossref]

9. Cecilia, C., & Katherine, L. (2023). The AI Generation gap: Are Gen Z Students More Interested in Adopting Generative AI Such as ChatGPT in Teaching and Learning than Their Gen X And Millennial Generation teachers? https://doi.org/10.48550/arxiv.2305.02878 Date Retrieved: March 28, 2025 [Google Scholar] [Crossref]

10. Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1), 1–18. https://doi.org/10.1186/s41239-023-00411-8 Date Retrieved: March 28, 2025 [Google Scholar] [Crossref]

11. Cherry, K. (2023). Gardner’s theory of multiple intelligences. Verywell Mind. https://www.verywellmind.com/gardners-theory-of-multiple-intelligences-2795161 Date Retrieved: December 23, 2024 [Google Scholar] [Crossref]

12. Columbia School of Nursing. (2021). Q&A: Artificial Intelligence and Nursing. https://www.nursing.columbia.edu/news/q-artificial-intelligence-and-nursing. Date Retrieved: December 13, 2024 [Google Scholar] [Crossref]

13. Dancey, C. P., & Reidy, J. (2004). Statistics Without Maths for Psychology: Using SPSS for Windows. Prentice Hall. Date Retrieved: May 30, 2025 [Google Scholar] [Crossref]

14. De Gagne, J. C. (2023). The State of Artificial Intelligence in Nursing Education: Past, Present, and Future Directions. International Journal of Environmental Research and Public Health, 20(6), 4884. https://doi.org/10.3390/ijerph20064884 Date Retrieved: December 23, 2024 [Google Scholar] [Crossref]

15. Devi, B., Lepcha, N., & Basnet, S. (2022). Application of correlational research design in nursing and medical research. Journal of Xi’an Shiyou University, Natural Sciences Edition, 65(11). https://doi.org/10.17605/OSF.IO/YRZ68 Date Retrieved: February 25, 2024 [Google Scholar] [Crossref]

16. Dorin, M., & Atkinson, H. L. (2024). Getting to know AI: Gaps and opportunities for nurse educators. Teaching and Learning in Nursing, 19(3), 218–224. https://doi.org/10.1016/j.teln.2024.02.013. [Google Scholar] [Crossref]

17. Date Retrieved: December 20, 2024 [Google Scholar] [Crossref]

18. Educational Trends and Innovations. (2023). Adaptive learning and AI in education. Universitat Oberta de Catalunya. https://blogs.uoc.edu/elearning-innovation-center/ai-will-help-drive a-definitive-revolution-in-education/. Date Retrieved: December 20, 2024 [Google Scholar] [Crossref]

19. Glass, G. (2024). The Future of AI and Education. GoodNewsPilipinas.com. https://www.goodnewspilipinas.com/the-future-of-ai-and-education/. Date Retrieved: December 23, 2024 [Google Scholar] [Crossref]

20. Glauberman, G., Ito-Fujita, A., Katz, S., & Callahan, J. (2023). Artificial intelligence in nursing Education: Opportunities and challenges. https://pmc.ncbi.nlm.nih.gov/articles/PMC10713739/. [Google Scholar] [Crossref]

21. Date Retrieved: December 20, 2024 [Google Scholar] [Crossref]

22. Green, J. L., Manski, S. E., Hansen, T. A., & Broatch, J. E. (2023). Descriptive statistics. International Encyclopedia of Education(Fourth Edition), 723–733. https://doi.org/10.1016/b978-0-12-818630-5.10083-1. Date Retrieved: January 22, 2025 [Google Scholar] [Crossref]

23. Gunawan, J., Aungsuroch, Y., Marzilli, C., Nazliansyah, Chaerani, E., & Montayre, J. (2024). Artificial Intelligence Chatbot as Perceived by Nursing Students: A Qualitative Study. Sage Open, 14(4).https://doi.org/10.1177/21582440241303453 Date retrieved: December 23, 2024 [Google Scholar] [Crossref]

24. Halton, C. (2023). Diffusion Of Innovations Theory Definition. Investopedia. https://www.investopedia.com/terms/d/diffusion-of-innovations-theory.asp Date Retrieved: December 13, 2024 [Google Scholar] [Crossref]

25. Han, S., Kang, H. S., Gimber, P., & Lim, S. (2025). Nursing Students’ Perceptions and Use of Generative Artificial Intelligence in Nursing Education. Nursing Reports, 15(2), 68. https://doi.org/10.3390/nursrep15020068 Date Retrieved: May 30, 2025 [Google Scholar] [Crossref]

26. Hanlon, A. (2020). What is the The Diffusion of Innovation model? Smart Insights. https://www.smartinsights.com/marketing-planning/marketing-models/diffusion-innovation-model/ [Google Scholar] [Crossref]

27. Date Retrieved: May 30, 2025 [Google Scholar] [Crossref]

28. HITRUST. (2023). The Ethics of AI in Healthcare. Hitrustalliance.net. https://hitrustalliance.net/blog/the-ethics-of-ai-in-healthcare. Date Retrieved: December 10, 2024 [Google Scholar] [Crossref]

29. IDP Philippines. (2025). Artificial Intelligence (AI) in Education | Idp.com. https://www.idp.com/philippines/blog/artificial-intelligence-in-education/?fbclid= IwZXh0bgNhZW0CMTEAAR3I6TDYjmcgs6viXR8ognuiAJOW-IMnH6sgVrOwcbFa6tyZD7Nc3hJ3DYc_aem_FzZuyHCJBsCofx1k9qyWQg Date Retrieved: February 6, 2025 [Google Scholar] [Crossref]

30. James, J. (2023). Understanding the Unified Theory of Acceptance and Use of Technology - Enablers of Change. Enablers of Change. https://www.enablersofchange.com.au/understanding-the-unified-theory-of-acceptance-and-use-of-technology/ Date Retrieved: December 13, 2024 [Google Scholar] [Crossref]

31. James, J. (2023). What is the Technology Acceptance Model? - Enablers of Change. Enablers of Change. https://www.enablersofchange.com.au/what-is-the-technology-acceptance-model/ [Google Scholar] [Crossref]

32. Date Retrieved: December 13, 2024 [Google Scholar] [Crossref]

33. Jordan, A. (2023). 5 Ways AI is Transforming Nursing Education. Provo College. https://www.provocollege.edu/blog/ways-ai-is-transforming-nursing education/. Date Retrieved: December 23, 2024 [Google Scholar] [Crossref]

34. Joshi, R. (2023). Adaptive learning in nursing education: A focus on generative AI. Healthcare Technology Review https://www.researchgate.net/publication/372701884 Adaptive Learning_through_Artificial_Intelligence. Date Retrieved: December 23, 2024 [Google Scholar] [Crossref]

35. Kamalov, F., Calonge, D. S., & Gurrib, I. (2023). New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution. Sustainability, 15(16), 12451. mdpi. https://doi.org/10.3390/su151612451 Date Retrieved: May 30, 2025 [Google Scholar] [Crossref]

36. Katsamakas, E., Pavlov, O. V., & Saklad, R. (2024). Artificial intelligence and the transformation of higher education institutions. https://arxiv.org/abs/2402.08143 Date Retrieved: February 24, 2025 [Google Scholar] [Crossref]

37. Kelly, R. (2024). Survey: 86% of Students Already Use AI in Their Studies. Campus Technology. https://campustechnology.com/Articles/2024/08/28/Survey-86-of-Students-Already-Use-AI-in-Their-Studies.aspx Date Retrieved: February 26, 2025 [Google Scholar] [Crossref]

38. Kwak, Y., Seo, Y. H., & Ahn, J.-W. (2022). Nursing students’ intent to use AI-based healthcare technology: Path analysis using the unified theory of acceptance and use of technology. Nurse Education Today, 119, 105541. https://doi.org/10.1016/j.nedt.2022.105541. [Google Scholar] [Crossref]

39. Date Retrieved: December 20, 2024 [Google Scholar] [Crossref]

40. Labrague, L. J., Aguilar-Rosales, R., Yboa, B. C., Sabio, J. B., & de Los Santos, J. A. A. (2023). Student nurses’ attitudes, perceived utilization, and intention to adapt artificial intelligence (AI) technology in nursing practice: A cross-sectional study. Nurse Education in Practice, 73, 103815. https://pubmed.ncbi.nlm.nih.gov/37922736/. Date Retrieved: December 23, 2024 [Google Scholar] [Crossref]

41. Laerd statistics. (2018). How to perform a Multiple Regression Analysis in SPSS Statistics | Laerd Statistics. Laerd Statistics. https://statistics.laerd.com/spss-tutorials/multiple-regression-using-spss-statistics.php. Date Retrieved: January 22, 2025 [Google Scholar] [Crossref]

42. Laerd Statistics. (2018). One-way ANOVA - An introduction to when you should run this test and the test hypothesis. Laerd.com. https://statistics.laerd.com/statistical-guides/one-way-anova-statistical-guide.php Date Retrieved: January 22, 2025 [Google Scholar] [Crossref]

43. Lukić, A., Kudelić, N., Antičević, V., Lazić-Mosler, E., Glunčić, V., Hren, D., & Lukić, I. K. (2023). First-year nursing students’ attitudes towards artificial intelligence: Cross-sectional multi-centre study. Nurse Education in Practice, 71, 103735. https://doi.org/10.1016/j.nepr.2023.103735. [Google Scholar] [Crossref]

44. Date Retrieved: December 10, 2024 [Google Scholar] [Crossref]

45. Mapua University. (2024). Mapua.edu.ph. https://www.mapua.edu.ph/news/mapua-university-leads-the-way-in-ai-integrated-education-in-the-philippines. Date Retrieved: December 23, 2024 [Google Scholar] [Crossref]

46. Marikyan, D., & Papagiannidis, S. (2021). Unified Theory of Acceptance and Use of Technology: A review. Open.ncl.ac.uk. https://open.ncl.ac.uk/theories/2/unified-theory-of-acceptance-and-use-of-technology/ Date Retrieved: December 23, 2024 [Google Scholar] [Crossref]

47. MSU-IIT Webteam. (2024). Asia’s university leaders urge responsible integration of AI in higher education at HELF 2024. Msuiit.edu.ph. https://msuiit.edu.ph/news/news-detail.php?id=1994. [Google Scholar] [Crossref]

48. Date Retrieved: December 23, 2024 [Google Scholar] [Crossref]

49. Nashwan, A. J., & Abujaber, A. A. (2023). Embracing artificial intelligence in nursing education: Preparing future nurses for a technologically advanced healthcare landscape. Evidence-Based Nursing. https://pubmed.ncbi.nlm.nih.gov/38228384/. Date Retrieved: December 10, 2024 [Google Scholar] [Crossref]

50. Ng, Z. Q. P., Ling, L. Y. J., Chew, H. S. J., & Lau, Y. (2021). The Role of artificial intelligence in enhancing clinical nursing care: A Scoping Review. Journal of Nursing Management, 30(8). https://doi.org/10.1111/jonm.13425. Date Retrieved: December 23, 2024 [Google Scholar] [Crossref]

51. Nguyen, A., Ngo, H. N., Hong, Y., Dang, B., & Nguyen, B.-P. T. (2022). Ethical principles for artificial intelligence in education. Education and Information Technologies, 28(28). https://link.springer.com/article/10.1007/s10639-022-11316-w Date Retrieved: May 30, 2025 [Google Scholar] [Crossref]

52. O’Connor, S. (2023). Artificial intelligence in nursing education 1: strengths and weaknesses. Nursing Times [online]; 119: 10. https://www.nursingtimes.net/education-and-training/artificial-intelligence-in-nursing-education-1-strengths-and-weaknesses-11-09-2023/. Date Retrieved: December 20, 2024 [Google Scholar] [Crossref]

53. Omari, O. A., Muna Alshammari, Jabri, W. A., Asma Al Yahyaei, Khalid Abdullah Aljohani, Hala Mohamed Sanad, Al-Jubouri, M. B., Ibrahim Bashayreh, Fawaz, M., ALBashtawy, M., Abdullah Alkhawaldeh, Qaddumi, J., Shalaby, S. A., Abdallah, H. M., Loai AbuSharour, Qadire, M. A., & Maen Aljezawi. (2024). Demographic factors, knowledge, attitude and perception and their association with nursing students’ intention to use artificial intelligence (AI): a multicentre survey across 10 Arab countries. BMC Medical Education, 24(1). https://doi.org/10.1186/s12909-024-06452-5. [Google Scholar] [Crossref]

54. Date Retrieved: December 10, 2024 [Google Scholar] [Crossref]

55. Ouyang, F., & Jiao, P. (2021). Artificial Intelligence in Education: the Three Paradigms. Computers and Education: Artificial Intelligence, 2(1), 100020. https://doi.org/10.1016/j.caeai.2021.100020 [Google Scholar] [Crossref]

56. Date Retrieved: May 30, 2025 [Google Scholar] [Crossref]

57. Pailaha, A. D. (2023). The impact and issues of artificial intelligence in nursing science and healthcare settings. SAGE Open Nursing, 9. https://doi.org/10.1177/23779608231196847. [Google Scholar] [Crossref]

58. Date Retrieved: December 10, 2024 [Google Scholar] [Crossref]

59. Pascual, J. (2023). PH schools adapting AI; UP among first in Asia: Group. ABS-CBN News. https://www.abs-cbn.com/business/11/16/23/ph-schools-adapting-a-up-mong-first-in-asia-group. [Google Scholar] [Crossref]

60. Date Retrieved: December 10, 2024 [Google Scholar] [Crossref]

61. Regie Boy Fabro, Rivera, J. C., Sambrano, L. C., & Joy, L. (2024). Perceptions and Extent of Utilization of Generative Artificial Intelligence (AI) among Filipino Students. ResearchGate, 12(7). https://www.researchgate.net/publication/383121815_Perceptions_and_Extent_of_Utilization_of_Generative_Artificial_Intelligence_AI_among_Filipino_Students Date Retrieved: March 28, 2025 [Google Scholar] [Crossref]

62. Sansom, R. (2021). Theory of Planned Behavior. Change Theories Collection; ASCN. https://ascnhighered.org/ASCN/change_theories/collection/planned_behavior.html Date Retrieved: December 13, 2024 [Google Scholar] [Crossref]

63. Shin, H., De, J. C., Sang Suk Kim, & Hong, M. (2024). The impact of Artificial Intelligence-Assisted Learning on nursing students’ ethical decision-making and clinical reasoning in pediatric care. CIN Computers Informatics Nursing. https://doi.org/10.1097/cin.0000000000001177. Date Retrieved: December 10, 2024 [Google Scholar] [Crossref]

64. Smith, J., & Johnson, L. (2023). Ethical considerations in the use of artificial intelligence in education. Journal of Educational Technology, 15(2), 45-59. Date Retrieved: May 30, 2025 [Google Scholar] [Crossref]

65. Smith, J., & Kumar, R. (2023). Digital literacy and critical evaluation skills in the age of AI: Implications for higher education. Journal of Educational Technology & Society, 26(1), 45-58. [Google Scholar] [Crossref]

66. Date Retrieved: May 30, 2025 [Google Scholar] [Crossref]

67. Song, Y., & Wang, S. (2024). A Survey and Research on the Use of Artificial Intelligence by Chinese Design-College Students. Buildings, 14(9), 2957. https://doi.org/10.3390/buildings14092957. [Google Scholar] [Crossref]

68. Date Retrieved: December 13, 2024 [Google Scholar] [Crossref]

69. Statistics Canada. (2021). Statistics: Power from Data! Organizing data: Frequency distribution tables. Statcan.gc.ca. https://www150.statcan.gc.ca/n1/edu/power-pouvoir/ch8/5214814-eng.htm [Google Scholar] [Crossref]

70. Date Retrieved: December 20, 2024 [Google Scholar] [Crossref]

71. Stryker, C., & Kavlakoglu, E. (2024). What Is Artificial Intelligence (AI)? IBM. https://www.ibm.com/think/topics/artificial-intelligence Date Retrieved: February 10, 2025 [Google Scholar] [Crossref]

72. The University of Tennessee Health Science Center. (2021). Multiple intelligence theory. UTHSC. https://www.uthsc.edu/tlc/intelligence-theory.php Date Retrieved: May 30, 2025 [Google Scholar] [Crossref]

73. United Nations. (2015). The 17 sustainable development goals. United Nations. https://sdgs.un.org/goals Date Retrieved: December 20, 2024 [Google Scholar] [Crossref]

74. University of the Philippines Manila. (2024). Experts: Use of Artificial Intelligence Can Improve Healthcare Delivery. University of the Philippines Manila - the Health Sciences Center. https://www.upm.edu.ph/cpt_news/experts-use-of-artificial-intelligence-can-improve-healthcare-delivery/ Date Retrieved: December 20, 2024 [Google Scholar] [Crossref]

75. University of the Philippines Open University. (2023). UPOU hosts the 2023 TriConference on AI in Education. UPOUOfficialPage. https://www.upou.edu.ph/news/upou-initiatives-in-the-use-of-artifici l-inteligence-ai-in-teaching-and-learning/. Date Retrieved: December 10, 2024 [Google Scholar] [Crossref]

76. Webb, R. (2023). 11.1: One-Way ANOVA. Statistics LibreTexts. https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Mostly_Harmless_Statistics_(Webb)/11%3A_Analysis_of_Variance/11.01%3A_One-Way_ANOVA. Date Retrieved: January 22, 2025 [Google Scholar] [Crossref]

77. Western Governors University. (2023). How AI Is Influencing Nursing Education. https://www.wgu.edu/blog/how-ai-influencing-nursing-education237.html. Date Retrieved: December 10, 2024 [Google Scholar] [Crossref]

78. White, A., Maguire, M. B., Brown, A., & Keen, D. (2024). Impact of Artificial Intelligence on Nursing Students’ Attitudes toward Older Adults: A Pre/Post-Study. Nursing Reports, 14(2), 1129-1135. https://doi.org/10.3390/nursrep14020085 Date Retrieved: December 20, 2024 [Google Scholar] [Crossref]

79. Wikipedia. (2018). Technology acceptance model. Wikipedia; Wikimedia Foundation. https://en.wikipedia.org/wiki/Technology_acceptance_model Date Retrieved: May 30, 2025 [Google Scholar] [Crossref]

80. Zhang, C., & Lu, Y. (2021). Study on Artificial Intelligence: The State of the Art and Future Prospects. Journal of Industrial Information Integration, 23(23), 100224. https://doi.org/10.1016/j.jii.2021.100224 [Google Scholar] [Crossref]

81. Date Retrieved: April 2, 2025 [Google Scholar] [Crossref]

• Knowledge and Attitude of Undergraduate Nursing Students towards Organ Donation
• Cold Hip Bath Therapy for Labor Pain Management: A Review of Non-Pharmacological Interventions in Women's Health
• Work Settings Utilizing the S.C.O.R.E Model on the Psychological Empowerment of Hospital Nurses in Cebu City
• An Assessment on the Quality of Life of PLHIV Residents in Digos City Barangays: Basis for Health Teaching Program
• Work-Related Stress and Its Psychodermatological Impact on Nursing Professionals