Artificial Intelligence Literacy and Its Association with Academic Integrity and Critical Thinking Among Undergraduate Nursing Students: A Cross Sectional Study
DOI:
https://doi.org/10.68716/IJAMSR.2026.1202Keywords:
Artificial intelligence literacy; Academic integrity; Critical thinking; Nursing education; Undergraduate nursing students; Ethical scholarshipAbstract
Background: Artificial Intelligence (AI) literacy has emerged as a critical competency in healthcare education, influencing both ethical academic practices and the development of higher-order thinking skills. Concerns persist that AI access may foster academic misconduct, yet empirical evidence remains limited.
Objective: This study examined the association between AI literacy and academic integrity and critical thinking disposition among nursing students in India.
Methods: A cross-sectional survey was conducted among 477 nursing students, of whom 434 provided valid, consented responses. Data were collected using standardised 5-point Likert scales assessing AI literacy, academic integrity, and critical thinking. Statistical analyses included descriptive statistics, Pearson correlations, simple linear regression, independent-samples t-tests, and one-way ANOVA.
Results: Participants were predominantly female (75.3%), enrolled in B.Sc. Nursing (66.1%), and from private institutions (98.6%). Overall, AI literacy was moderate-to-high (Mean = 3.35, SD = 0.73). AI literacy was strongly and positively correlated with academic integrity (r = 0.821, p < 0.001, R² = 0.674) and critical thinking (r = 0.788, p < 0.001, R² = 0.621). Sub-domains of academic honesty behaviours (Mean = 3.43) and reflective judgment in AI use (Mean = 3.43) were particularly high. Demographic analyses showed no significant differences across gender, course, or year of study, suggesting uniform AI literacy levels.
Conclusion: Findings show that higher AI literacy is strongly associated with stronger academic integrity and critical thinking among nursing students. Contrary to prevailing concerns, AI literacy fosters responsible and ethical use of generative tools while strengthening reflective judgment and open-mindedness. Educational institutions should integrate standardised AI literacy and ethics curricula across all years of nursing education to promote ethical scholarship and clinical reasoning.
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1. Han S, Kang HS, Gimber P, Lim S. Nursing Students' Perceptions and Use of Generative Artificial Intelligence in Nursing Education. Nurs Rep. 2025;15(2):68. doi: 10.3390/nursrep15020068.
2. Khlaif ZN, Salameh N, Ajouz M, Mousa A, Itmazi J, Alwawi A, Alkaissi A. Using Generative AI in nursing education: Students' perceptions. BMC Med Educ. 2025;25(1):926. doi: 10.1186/s12909-025-07416-z.
3. Shin H, De Gagne JC, Kim SS, Hong M. The Impact of Artificial Intelligence-Assisted Learning on Nursing Students' Ethical Decision-making and Clinical Reasoning in Pediatric Care: A Quasi-Experimental Study. Comput Inform Nurs. 2024;42(10):704-11. doi: 10.1097/CIN.0000000000001177.
4. Long D, Magerko B. What is AI literacy? Competencies and design considerations. In: Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI ’20); 2020; Honolulu, HI, USA. New York: ACM; 2020. p. 1 26. doi:10.1145/3313831.3376727.
5. Lifshits I, Rosenberg D. Artificial intelligence in nursing education: A scoping review. Nurse Educ Pract. 2024;80:104148. doi: 10.1016/j.nepr.2024.104148.
6. El-Banna MM, Sajid MR, Rizvi MR, Sami W, McNelis AM. AI literacy and competency in nursing education: preparing students and faculty members for an AI-enabled future-a systematic review and meta-analysis. Front Med (Lausanne). 2025;12:1681784. doi: 10.3389/fmed.2025.1681784.
7. Cotton DRE, Cotton PA, Shipway JR. Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innov Educ Teach Int. 2024;61(2):228 39. doi:10.1080/14703297.2023.2190148.
8. Shishakly R, Nachouki M. Academic integrity and students’ ethical use of ChatGPT in higher education. J Inf Technol Educ Res. 2026;25:Article 8. doi:10.28945/5730.
9. Dodson TM, Thompson Hairston K, Reed JM. Nursing students’ AI literacy and ethical understanding of AI in nursing education. Teach Learn Nurs. 2025;1 5. doi:10.1016/j.teln.2025.07.004.
10. Koohkan A. Critical thinking and clinical reasoning in nursing. J Nurs Adv Clin Sci. 2025;2(2):113 4. doi:10.32598/JNACS.2411.1072.
11. Tiwari A, Avery A, Lai P. Critical thinking disposition of Hong Kong Chinese and Australian nursing students. J Adv Nurs. 2003;44(3):298-307. doi: 10.1046/j.1365-2648.2003.02805.x.
12. Gouseti A, James F, Fallin L, Burden K. The ethics of using AI in K 12 education: a systematic literature review. Technol Pedagogy Educ. 2025;34(2):161 82. doi:10.1080/1475939X.2024.2428601.
13. Valan AP, Kannan LS, Subbarayalu AV, Prabaharan S, Hassan EMG, Nashaat NAM, et al. Knowledge, attitudes and perception of nursing students about artificial intelligence in India. Int Res J Multidiscip Scope. 2026;7(3):395 409. doi:10.47857/irjms.2026.v07i03.09899.
14. Fernandes F, Encarnação R, Alves J, Pais-Vieira C, Lima SBS, Alves P. Educational Applications of AI-Based Chatbots in Nursing: A Scoping Review. Nurs Rep. 2026;16(3):87. doi: 10.3390/nursrep16030087.
15. Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019;25(1):44-56. doi: 10.1038/s41591-018-0300-7.
16. Mies-Padilla S, Rodríguez-Suárez C-A, González-de la Torre H. Assessment Instruments for Artificial Intelligence Literacy in Healthcare Professionals: A Scoping Review. Information. 2026;17(9):914. doi: 10.3390/info17090914
17. Siah CR, Lim JV, Lyu MM, Levett-Jones T, Mattar I. Authenticity and academic integrity in Generative Artificial Intelligence (GenAI) use among undergraduate nursing students. J Prof Nurs. 2026;62:45-51. doi: 10.1016/j.profnurs.2025.10.007.
18. Zgambo M, Costello M, Buhlmann M, Maldon J, Anyango E, Adama E. Artificial intelligence and academic integrity in nursing education: A mixed methods study on usage, perceptions, and institutional implications. Nurse Educ Today. 2025;153:106796. doi: 10.1016/j.nedt.2025.106796.
19. Ronquillo CE, Peltonen LM, Pruinelli L, Chu CH, Bakken S, Beduschi A, et al. Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative. J Adv Nurs. 2021;77(9):3707-17. doi: 10.1111/jan.14855.
20. Holmes W, Porayska-Pomsta K, Holstein K, Sutherland E, Baker T, Buckingham Shum S, et al. Ethics of AI in Education: Towards a Community-Wide Framework. Int J Artif Intell Educ. 2022;32(3):504 26. doi: 10.1007/s40593-021-00239-1
21. Cui W, Zhang X. The association between AI dependence, AI literacy, and critical thinking ability among nursing interns: a multicenter cross-sectional study. Front Psychol. 2026;17:1823047. doi: 10.3389/fpsyg.2026.1823047.
22. Li F, Feng K, Wang S, Xue S, Zhang J, Li W. A study on the current status and associated factors of artificial intelligence literacy among undergraduate nursing students. Front Public Health. 2026;14:1930077. doi:10.3389/fpubh.2026.1930077.
23. Alanazy W, Almutairi N, Alaseeri R. Artificial intelligence literacy and intention to use AI in clinical practice among healthcare students in Saudi Arabia: A cross-sectional study. J Pioneering Med Sci. 2026;15(S01):44 52. doi:10.47310/jpms202515S0110.
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