Artificial intelligence chatbots in nursing education: a scoping review protocol
DOI:
https://doi.org/10.62741/ahrj.v3iSuppl.124Keywords:
education, nursing, nursing, artificial intelligence, generative artificial intelligenceAbstract
Introduction: The rapid integration of digital technologies and artificial intelligence systems in education has reshaped teaching and learning processes, enhancing personalization, interactivity, and learner autonomy. In nursing education, artificial intelligence -based educational chatbots have emerged as promising tools capable of simulating clinical situations, supporting critical thinking, and providing individualized feedback; however, the literature remains fragmented regarding their pedagogical applications, benefits, and challenges.
Objectives: To map and synthesize the existing evidence on the use of artificial intelligence -based chatbots in nursing education and professional development, identifying their applications, potentialities, limitations, and gaps in the current knowledge.
Methodology: This scoping review will follow the Joanna Briggs Institute methodology and be reported in accordance with the PRISMA-ScR guidelines. Comprehensive searches will be conducted across major databases and grey literature sources, with no restrictions on language or publication date. Studies addressing the development, implementation, evaluation, or perception of chatbot use in formal or non-formal nursing education will be included. Study selection and data extraction will be performed independently by two reviewers.
Conclusion: The findings are expected to provide a broad and detailed overview of the current evidence on educational chatbots in nursing education, supporting pedagogical innovation, guiding the development of more effective educational technologies, and informing future research focused on strengthening nursing education and professional training mediated by artificial intelligence.References
Benevides KDG, Rufino LJGC, Dos Santos DFA, et al. Inteli-gência artificial na educação de indivíduos adultos com 50 anos de idade ou mais: uma abordagem assistiva. ARACÊ 2025;7(8):e7160; doi: 10.56238/arev7n8-085. DOI: https://doi.org/10.56238/arev7n8-085
Florz ET, Florz JAK, Bandeira ELC, et al. A Inteligência Artificial na Formação em Saúde: Desafios Bioéticos e Implicações para a Prática Profissional. Revista de Gestão e Secretariado 2025;16(8):e5173; doi: 10.7769/gesec.v16i8.5173. DOI: https://doi.org/10.7769/gesec.v16i8.5173
Sheikh H, Prins C, Schrijvers E. Mission AI: The New System Technology. Springer Cham; 2023; pp. 15–41; doi: https://doi.org/10.1007/978-3-031-21448-6. DOI: https://doi.org/10.1007/978-3-031-21448-6_2
Helm JM, Swiergosz AM, Haeberle HS, et al. Machine Learning and Artificial Intelligence: Definitions, Applications, and Future Directions. Curr Rev Musculoskelet Med 2020;13(1):69–76; doi: 10.1007/s12178-020-09600-8. DOI: https://doi.org/10.1007/s12178-020-09600-8
Jakhar D, Kaur I. Artificial intelligence, machine learning and deep learning: definitions and differences. Clin Exp Dermatol 2020;45(1):131–132; doi: 10.1111/ced.14029. DOI: https://doi.org/10.1111/ced.14029
Aguiar JJB. Inteligência artificial e tecnologias digitais na educação: oportunidades e desafios. Open Minds Interna-tional Journal 2023;4(2):183–188; doi: 10.47180/omij.v4i2.215. DOI: https://doi.org/10.47180/omij.v4i2.215
Sun L, Yin C, Xu Q, et al. Artificial Intelligence for Healthcare and Medical Education: A Systematic Review. 2023.
De Gagne JC. The State of Artificial Intelligence in Nursing Education: Past, Present, and Future Directions. Int J Envi-ron Res Public Health 2023;20(6); doi: 10.3390/ijerph20064884. DOI: https://doi.org/10.3390/ijerph20064884
Araújo Carvalho J, Henrique Cordeiro J, Cruz da Silva A, et al. O uso da inteligência artificial para o ensino aprendizagem saúde coletiva: perspectivas concretas para a educação. Poblac Salud Mesoam 2025; doi: 10.15517/1ed6ef36. DOI: https://doi.org/10.15517/1ed6ef36
Pereira AJ, Gomes AS, Primo TT. Avaliação de sistema de tutoria inteligente para cooperar com tutores humanos. Ges-tão.org 2024;22(1); doi: 10.51359/1679-1827.2024.263224. DOI: https://doi.org/10.51359/1679-1827.2024.263224
O’Connor T, Gibson J, Lewis J, et al. Decision‐making in nursing research and practice—Application of the Cognitive Continuum Theory: A meta‐aggregative systematic review. J Clin Nurs 2023;32(23–24):7979–7995; doi: 10.1111/jocn.16893. DOI: https://doi.org/10.1111/jocn.16893
Lima SO, Meira J de L. Inteligência artificial e educação: estratégias para avaliar a eficácia do chatbot educacional EducaChat. REVISTA DELOS 2025;18(70):e6206; doi: 10.55905/rdelosv18.n70-068. DOI: https://doi.org/10.55905/rdelosv18.n70-068
Preiksaitis C, Rose C. Opportunities, Challenges, and Future Directions of Generative Artificial Intelligence in Medical Education: Scoping Review. JMIR Med Educ 2023;9:e48785; doi: 10.2196/48785. DOI: https://doi.org/10.2196/48785
Yu H, Guo Y. Generative Artificial Intelligence Empowers Educational Reform: Current Status, Issues, and Prospects. Front Educ (Lausanne) 2023;8; doi: 10.3389/feduc.2023.1183162. DOI: https://doi.org/10.3389/feduc.2023.1183162
Hobensack M, von Gerich H, Vyas P, et al. A rapid review on current and potential uses of large language models in nursing. Int J Nurs Stud 2024;154:104753; doi: 10.1016/j.ijnurstu.2024.104753. DOI: https://doi.org/10.1016/j.ijnurstu.2024.104753
Hu Y, Xiong Q, Yi L, et al. Nurse Town: An LLM-Powered Simulation Game for Nursing Education. In: 2025 IEEE Conference on Artificial Intelligence (CAI) IEEE; 2025; pp. 215–222; doi: 10.1109/CAI64502.2025.00041. DOI: https://doi.org/10.1109/CAI64502.2025.00041
Labrague LJ, Sabei S Al. Integration of AI-Powered Chatbots in Nursing Education: A Scoping Review of Their Utilization, Outcomes, and Challenges. Teaching and Learning in Nurs-ing 2025;20(1):e285–e293; doi: 10.1016/j.teln.2024.11.010. DOI: https://doi.org/10.1016/j.teln.2024.11.010
Velasco AM, Coelho EWF, Paes VLS, et al. A Inteligência Artificial na saúde: os Chatbots e suas aplicações na educação e pesquisa científica médicas. Caderno Pedagógico 2025;22(5):e15048; doi: 10.54033/cadpedv22n5-216. DOI: https://doi.org/10.54033/cadpedv22n5-216
Falcão HP de S, Correia C de C, Silva AF da, et al. Uso da inteligência artificial com um chatbot treinado na Metodologia SENAI de Educação Profissional (MSEP) no processo de avaliação formativa: estudo de caso com estudantes em uma escola do SENAI Ceará. Caderno Pedagógico 2025;22(1):e13611; doi: 10.54033/cadpedv22n1-235. DOI: https://doi.org/10.54033/cadpedv22n1-235
Lee H. The rise of ChatGPT: Exploring its potential in medi-cal education. Anat Sci Educ 2024;17(5):926–931; doi: 10.1002/ase.2270. DOI: https://doi.org/10.1002/ase.2270
Arksey H, O’Malley L. Scoping studies: towards a methodological framework. Int J Soc Res Methodol 2005;8(1):19–32; doi: 10.1080/1364557032000119616. DOI: https://doi.org/10.1080/1364557032000119616
Peters MD, Godfrey C, McInerney P, et al. Scoping Reviews. In: JBI Manual for Evidence Synthesis JBI; 2024; doi: 10.46658/JBIMES-24-09.
Zhang S, Yang X, Zhang L, et al. Exploring the Role and Potential of Chatbots in Learning From the Perspective of Nursing Students: A Systematic Review of Qualitative Studies. Int Nurs Rev 2025;72(3); doi: 10.1111/inr.70060. DOI: https://doi.org/10.1111/inr.70060
Levac D, Colquhoun H, O’brien KK. Scoping Studies: Ad-vancing the Methodology. 2010. DOI: https://doi.org/10.1186/1748-5908-5-69
Peters MD, Godfrey C, McInerney P, et al. Scoping Reviews (2020). In: JBI Manual for Evidence Synthesis. (Aromataris E, Lockwood C, Porritt K, et al. eds) JBI; 2024; doi: 10.46658/JBIMES-24-09. DOI: https://doi.org/10.46658/JBIMES-24-09
Munn Z, Peters MDJ, Stern C, et al. Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach. BMC Med Res Methodol 2018;18(1); doi: 10.1186/s12874-018-0611-x. DOI: https://doi.org/10.1186/s12874-018-0611-x
Tricco AC, Lillie E, Zarin W, et al. PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Ann Intern Med 2018;169(7):467–473; doi: 10.7326/m18-0850. DOI: https://doi.org/10.7326/M18-0850
Peters MDJ, Godfrey CM, Khalil H, et al. Guidance for conducting systematic scoping reviews. Int J Evid Based Healthc 2015;13(3):141–146; doi: 10.1097/XEB.0000000000000050. DOI: https://doi.org/10.1097/XEB.0000000000000050
McGowan J, Sampson M, Salzwedel DM, et al. PRESS Peer Review of Electronic Search Strategies: 2015 Guide-line Statement. J Clin Epidemiol 2016;75:40–46; doi: 10.1016/j.jclinepi.2016.01.021. DOI: https://doi.org/10.1016/j.jclinepi.2016.01.021
Peters MDJ, Marnie C, Tricco AC, et al. Updated methodological guidance for the conduct of scoping reviews. JBI Evid Synth 2020;18(10):2119–2126; doi: 10.11124/jbies-20-00167. DOI: https://doi.org/10.11124/JBIES-20-00167
Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;n71; doi: 10.1136/bmj.n71. DOI: https://doi.org/10.1136/bmj.n71
Peters MDJ, Godfrey C, McInerney P, et al. Best practice guidance and reporting items for the development of scoping review protocols. JBI Evid Synth 2022;20(4):953–968; doi: 10.11124/JBIES-21-00242. DOI: https://doi.org/10.11124/JBIES-21-00242
Pollock D, Peters MDJ, Khalil H, et al. Recommendations for the extraction, analysis, and presentation of results in scoping reviews. JBI Evid Synth 2023;21(3):520–532; doi: 10.11124/JBIES-22-00123. DOI: https://doi.org/10.11124/JBIES-22-00123
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Athena Health & Research Journal
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright of published papers is assigned to the Journal, but all content is licensed under the terms of Creative Commons Non-comercial 4.0 International License. Thus users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, without asking prior permission from the publisher or the author. This is in accordance with the BOAI definition of open access.
