Level of student attitudes towards artificial intelligence: Perspectives from nursing students
John Mark R. Asio 1 * , April J. L. Dela Cruz 2, Shiela M. P. Oconer 2, Victor C. Quimen 2
More Detail
1 Research Development and Community Extension Services, Gordon College, Philippines
2 College of Allied Health Studies, Gordon College, Philippines
* Corresponding Author

Abstract

Artificial intelligence in the healthcare field, especially in the academic community, is making its name and relevance. Hence, knowing how to navigate and deal with Artificial intelligence in the learning process as well as in the healthcare service is a must to keep abreast with the trends. This study aimed to understand nursing students' attitudes toward artificial intelligence from a tertiary educational institution in Olongapo City, Philippines. The investigators employed a descriptive-correlational research design with the help of an online survey as the primary data-gathering tool. Three hundred twenty-four nursing students, via purposive sampling, partook in the said online survey from September to October 2023. The study also used a standardized instrument to gather data on the attitude of student nurses toward Artificial intelligence. For the statistical analysis, the study employed both descriptive (frequency, percentage, and mean) and inferential statistics (Mann-Whitney U, Kruskal-Wallis H, Spearman rho) with the help of statistical software SPSS 23. Results from the demographics of the students mainly included females, first year in level, less than 20 years of age, with smartphones, and have a GPA between 85-89%, and have already used Artificial intelligence in their study or learning. At the same time, the respondents moderately agree with the survey's cognitive, affective, and behavioral aspects regarding the student nurses' attitudes toward Artificial intelligence. Significant differences also occurred among student nurses when the investigators grouped them according to the use of Artificial intelligence in study/ learning, year level, age bracket, and GPA. Finally, moderate to strong relationships occurred between the survey's cognitive, affective, and behavioral aspects. The study then provided pertinent recommendations at the end of the study, which focused on training, faculty development, and student advocacy towards Artificial intelligence learning and adoption.

Keywords

References

  • Abuzaid, M. M., Elshami, W., & Fadden, S. M. (2022). Integration of artificial intelligence into nursing practice. Health and Technology, 12(6), 1109–1115. https://doi.org/10.1007/s12553-022-00697-0
  • Ahmed, Z., Bhinder, K. K., Tariq, A., Tahir, M. J., Mehmood, Q., Tabassum, M. S., Malik, M., Aslam, S., Asghar, M.S., & Yousaf, Z. (2022). Knowledge, attitude, and practice of artificial intelligence among doctors and medical students in Pakistan: A cross-sectional online survey. Annals of Medicine and Surgery, 76, 103493. https://doi.org/10.1016/j.amsu.2022.103493
  • Ajlouni, A. O., Wahba, F. A. A., & Almahaireh, A. S. (2023). Students' attitudes towards using chatgpt as a learning tool: the case of the university of Jordan. International Journal of Interactive Mobile Technologies, 17(18), 99 – 117. https://doi.org/10.3991/ijim.v17i18.41753
  • Al Zaabi, A., AlMaskari, S., & AalAbdulsalam, A. (2023). Are physicians and medical students ready for artificial intelligence applications in healthcare? Digital Health, 9, 20552076231152167. https://doi.org/10.1177/20552076231152167
  • Alghamdi, S. A., & Alashban, Y. (2024). Medical science students' attitudes and perceptions of artificial intelligence in healthcare: A national study conducted in Saudi Arabia. Journal of Radiation Research and Applied Sciences, 17(1), 100815. https://doi.org/10.1016/j.jrras.2023.100815
  • Baigi, S. F. M., Sarbaz, M., Ghaddaripouri, K., Ghaddaripouri, M., Mousavi, A. S., & Kimiafar, K. (2023). Attitudes, knowledge, and skills towards artificial intelligence among healthcare students: A systematic review. Health Science Reports, 6(3), e1138. https://doi.org/10.1002/hsr2.1138
  • Balay-Odao, E. M., Omirzakova, D., Bolla, S. R., Almazan, J. U., & Cruz, J. P. (2024). Health professions students’ perceptions of artificial intelligence and its integration to health professions education and healthcare: a thematic analysis. Ai & Society, 40, 1863–1873. https://doi.org/10.1007/s00146-024-01957-5
  • Boillat, T., Nawaz, F. A., & Rivas, H. (2022). Readiness to embrace artificial intelligence among medical doctors and students: questionnaire-based study. JMIR Medical Education, 8(2), e34973. https://doi.org/10.2196/34973
  • 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
  • Cruz, J. P., Sembekova, A., Omirzakova, D., Bolla, S. R., & Balay-odao, E. M. (2024). Attitudes toward and readiness for medical artificial intelligence among medical and health science students. Health Professions Education, 10(3), 15. https://doi.org/10.55890/2452-3011.1296
  • Dai, Y., Chai, C. S., Lin, P. Y., Jong, M. S. Y., Guo, Y., & Qin, J. (2020). Promoting students’ well-being by developing their readiness for the artificial intelligence age. Sustainability, 12(16), 6597. https://doi.org/10.3390/su12166597
  • De Gagne, J. C. (2023). Values clarification exercises to prepare nursing students for artificial intelligence integration. International journal of environmental research and public health, 20(14), 6409. https://doi.org/10.3390/ijerph20146409
  • Devi, B., Devi, R., Pradhan, S., Giri, D., Lepcha, N., & Basnet, S. (2022). Application of correlational research design in nursing and medical research. Journal of Xi’an Shiyou University, 65(11), 60 – 69. https://doi.org/10.17605/OSF.IO/YRZ68
  • Ergin, E., Karaarslan, D., Şahan, S., & Çınar Yücel, Ş. (2022). Artificial intelligence and robot nurses: From nurse managers' perspective: A descriptive cross‐sectional study. Journal of Nursing Management, 30(8), 3853-3862. https://doi.org/10.1111/jonm.13646
  • Falcon, R. M. G., Alcazar, R. M. U., Babaran, H. G., Caragay, B. D. B., Corpuz, C. A. A., Kho, M. V. S., ... & Isip-Tan, I. T. C. (2024). Exploring filipino medical students’ attitudes and perceptions of artificial intelligence in medical education: A mixed-methods study. MedEdPublish, 14(282), 282. https://doi.org/10.12688/mep.20590.2
  • Gillissen, A., Kochanek, T., Zupanic, M., & Ehlers, J. (2022, April). Medical students’ perceptions towards digitization and artificial intelligence: a mixed-methods study. Healthcare, 10(4), 723. https://doi.org/10.3390/healthcare10040723
  • Grunhut, J., Wyatt, A. T., & Marques, O. (2021). Educating Future Physicians in Artificial Intelligence (AI): An Integrative Review and Proposed Changes. Journal of Medical Education and Curricular Development, 8. https://doi.org/10.1177/23821205211036836
  • Hamedani, Z., Moradi, M., Kalroozi, F., Manafi Anari, A., Jalalifar, E., Ansari, A., Aski, B.H., Nexamzadeh, M., & Karim, B. (2023). Evaluation of acceptance, attitude, and knowledge towards artificial intelligence and its application from the point of view of physicians and nurses: A provincial survey study in Iran: A cross‐sectional descriptive‐analytical study. Health Science Reports, 6(9), e1543. https://doi.org/10.1002/hsr2.1543
  • Hussain, I. (2020). Attitude of university students and teachers towards instructional role of artificial intelligence. International Journal of Distance Education and E-Learning, 5(2), 158–177. http://dx.doi.org/10.36261/ijdeel.v5i2.1057
  • Hwang, G. J., Tang, K. Y., & Tu, Y. F. (2024). How artificial intelligence (AI) supports nursing education: profiling the roles, applications, and trends of AI in nursing education research (1993–2020). Interactive Learning Environments, 32(1), 373-392. https://doi.org/10.1080/10494820.2022.2086579
  • Jackson, P., Ponath Sukumaran, G., Babu, C., Tony, M. C., Jack, D. S., Reshma, V. R., Davis, D., Kurian, N., & John, A. (2024). Artificial intelligence in medical education-perception among medical students. BMC Medical Education, 24(1), 804. https://doi.org/10.1186/s12909-024-05760-0
  • Jussupow, E., Spohrer, K., & Heinzl, A. (2022). Identity threats as a reason for resistance to artificial intelligence: survey study with medical students and professionals. JMIR Formative Research, 6(3), e28750. https://doi.org/10.2196/28750
  • Khlaif, Z.N., Salameh, N., Ajouz, M., Mousa, A.. Itmazi, J., Alwawi, A. & Alkaissi, A. (2025). Using generative AI in nursing education: Nursing students’ perceptions, benefits, and challenges. BMC Medical Education, 25(1), 926. https://doi.org/10.1186/s12909-025-07416-z
  • Kimiafar, K., Sarbaz, M., Tabatabaei, S. M., Ghaddaripouri, K., Mousavi, A. S., Mehneh, M. R., & Baigi, S. F. M. (2023). Artificial intelligence literacy among healthcare professionals and students: a systematic review. Frontiers in Health Informatics, 12, 168. http://dx.doi.org/10.30699/fhi.v12i0.524
  • Labrague, L. J., Aguilar-Rosales, R., Yboa, B. C., Sabio, J. B., & de Los Santos, J. A. (2023). Student nurses' attitudes, perceived utilization, and intention to adopt artificial intelligence (AI) technology in nursing practice: a cross-sectional study. Nurse Education in Practice, 73, 103815. https://doi.org/10.1016/j.nepr.2023.103815
  • Mariano, M. E. M., Shahin, M. A. H., Ancheta, S. J., Kunjan, M. V., Al Dossary, N. M., Al Ojaimi, S. F., ... & Al Harbi, H. F. (2025). Exploring artificial intelligence knowledge, attitudes, and practices among nurses, faculty, and students in Saudi Arabia: A cross-sectional analysis. Social Sciences & Humanities Open, 11, 101384. https://doi.org/10.1016/j.ssaho.2025.101384
  • Moldt, J. A., Festl-Wietek, T., Madany Mamlouk, A., Nieselt, K., Fuhl, W., & Herrmann-Werner, A. (2023). Chatbots for future docs: exploring medical students’ attitudes and knowledge towards artificial intelligence and medical chatbots. Medical Education Online, 28(1), 2182659. https://doi.org/10.1080/10872981.2023.2182659
  • Ng, Z. Q. P., Ling, L. Y. J., Chew, H. S. J., & Lau, Y. (2022). The role of artificial intelligence in enhancing clinical nursing care: A scoping review. Journal of Nursing Management, 30(8), 3654–3674. https://doi.org/10.1111/jonm.13425
  • O'Connor, S., Yan, Y., Thilo, F. J., Felzmann, H., Dowding, D., & Lee, J. J. (2023). Artificial intelligence in nursing and midwifery: A systematic review. Journal of Clinical Nursing, 32(13-14), 2951–2968. https://doi.org/10.1111/jocn.16478
  • Qin, K. X., Ahmad, N., Soomro, K., Shedu, Y., Singogo, T. D., & Rasheed, A. J. (2024). Knowledge, attitude, and practice of artificial intelligence (AI) among medical students: A cross-sectional study from Ipoh, Perak. Quest International Journal of Medical and Health Sciences, 7(1), 9–15. https://doi.org/10.5281/zenodo.13143048
  • Shang, Z. (2021). A concept analysis on the use of artificial intelligence in nursing. Cureus, 13(5), 14857. https://doi.org/10.7759%2Fcureus.14857
  • Suh, W., & Ahn, S. (2022). Development and validation of a scale measuring student attitudes toward artificial intelligence. SAGE Open, 12(2), 463. https://doi.org/10.1177/21582440221100463
  • Syed, W., & Basil A. Al-Rawi, M. (2023). Assessment of awareness, perceptions, and opinions towards artificial intelligence among healthcare students in Riyadh, Saudi Arabia. Medicina, 59(5), 828. https://doi.org/10.3390/medicina59050828
  • Taber, K.S. (2018). The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education. Research in Science Education, 48, 1273–1296. https://doi.org/10.1007/s11165-016-9602-2
  • Villarino, R. T. (2025). Artificial Intelligence (AI) integration in Rural Philippine Higher Education: Perspectives, challenges, and ethical considerations. IJERI: International Journal of Educational Research and Innovation, 23, 1 – 25. https://doi.org/10.46661/ijeri.10909
  • Wang, X., Pang, H., Wallace, M. P., Wang, Q., & Chen, W. (2024). Learners’ perceived AI presences in AI-supported language learning: A study of AI as a humanized agent from community of inquiry. Computer Assisted Language Learning, 37(4), 814–840. https://doi.org/10.1080/09588221.2022.2056203
  • Yüzbaşıoğlu, E. (2021). Attitudes and perceptions of dental students towards artificial intelligence. Journal of Dental Education, 85(1), 60-68. https://doi.org/10.1002/jdd.12385

License

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.