Ítem
Acceso Abierto

Inteligencia artificial en el diseño curricular de una rotación clínica en cirugía general de pregrado de medicina. Un estudio de investigación – acción

Mostrar el registro sencillo de la publicación
dc.contributor.advisorIsaza Restrepo, Andrés
dc.creatorVargas Rubiano, Saúl Enrique
dc.creator.degreeMagíster en Educación para Profesionales de la Salud
dc.date.accessioned2025-07-08T21:33:36Z
dc.date.available2025-07-08T21:33:36Z
dc.date.created2025-07-07
dc.descriptionEn esta investigación se exploran la contribución de la Inteligencia Artificial Generativa (IAG) en el diseño de un currículo para una rotación clínica en cirugía general del pregrado de medicina, y cómo la perciben, ajustan y complementan los interesados: directivos, docentes, estudiantes y educadores médicos, mediante un enfoque cualitativo, en un marco constructivista, utilizando la metodología de investigación-acción. En una primera fase metodológica, por medio de Prompts Engineering se construyó un currículo para una rotación clínica de cirugía en el pregrado de medicina siguiendo los pasos propuestos por Hilda Taba y utilizando ChatGPT-4 con ayuda de un experto en IAG. En una segunda fase se adelantó una encuesta de percepción sobre los resultados obtenidos para obtener una calificación cuantitativa, y se realizaron 3 grupos focales (estudiantes de medicina de 6 semestre, estudiantes de medicina de 8 semestre y cirujanos docentes de cirugía) y entrevistas semiestructuradas a expertos en educación médica que proporcionaron retroalimentación sobre este producto obtenido con la IAG. En la encuesta de percepción, la mayoría de los participantes calificó como satisfactorio el currículo diseñado en cuanto a declaración de necesidades, objetivos, contenidos, estrategias de enseñanza aprendizaje y evaluación para una rotación en cirugía general del pregrado de medicina en el contexto propuesto. Sin embargo, mediante los grupos focales y las entrevistas semiestructuradas con actores interesados se logró identificar debilidades en la estrategia para el diseño curricular, posibles sesgos, riesgos o limitaciones de la herramienta, la relevancia del trabajo colaborativo y constructivo y el potencial de la IAG como insumo básico para la construcción de un currículo.
dc.description.abstractThis research explores the contribution of Generative Artificial Intelligence (GAI) to the design of a curriculum for a clinical rotation in general surgery in undergraduate medicine, and how it is perceived, adjusted, and complemented by stakeholders—administrators, faculty, students, and medical educators—using a qualitative approach within a constructivist framework, utilizing action research methodology. In a first methodological phase, a curriculum for a clinical rotation in surgery in undergraduate medicine was constructed using Prompts Engineering, following the steps proposed by Hilda Taba and using ChatGPT-4 with the assistance of an GAI expert. In a second phase, a perception survey was conducted on the results obtained to obtain a quantitative rating. Three focus groups were conducted (sixth-semester medical students, eighth-semester medical students, and surgical instructors) and semi-structured interviews were conducted with medical education experts who provided feedback on this product obtained with GAI. In the perception survey, the majority of participants rated the curriculum designed as satisfactory in terms of its needs statement, objectives, content, teaching-learning strategies, and assessment for a general surgery rotation in the undergraduate medical program in the proposed context. However, through focus groups and semi-structured interviews with stakeholders, weaknesses in the curriculum design strategy, potential biases, risks, or limitations of the tool, the importance of collaborative and constructive work, and the potential of AI as a basic input for curriculum development were identified.
dc.format.extent83 pp
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.48713/10336_45809
dc.identifier.urihttps://repository.urosario.edu.co/handle/10336/45809
dc.language.isospa
dc.publisherUniversidad del Rosario
dc.publisherPontificia Universidad Javeriana. Facultad de Medicina
dc.publisher.departmentEscuela de Medicina y Ciencias de la Salud
dc.publisher.programMaestría en Educación para Profesionales de la Salud
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.accesRightsinfo:eu-repo/semantics/openAccess
dc.rights.accesoAbierto (Texto Completo)
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.source.bibliographicCitationAltun, S., & Yücel-Toy, B. (2015). The Methods of Teaching Course Based on Constructivist Learning Approach: An Action Research. Journal of Education and Training Studies, 3(6), 248-270. https://doi.org/10.11114/jets.v3i6.1047
dc.source.bibliographicCitationArmstrong, F. (2019). Social Constructivism and Action Research: Transforming teaching and learning through collaborative practice. En Investigación-acción para la educación inclusiva. Taylor & Francis. https://discovery.ucl.ac.uk/id/eprint/10068456/3/Armstrong%20x%20Chapter%201%20Social%20Constructivism%20and%20Action%20Research.pdf
dc.source.bibliographicCitationArmstrong, F., & Tsokova, D. (Eds.). (2019). Action research for inclusive education: Participation and democracy in teaching and learning. Routledge.
dc.source.bibliographicCitationAsociación Colombiana de Facultades de Medicina. (2025). Portafolio de servicios -Gestión curricular y desarrollo profesoral. Ascofame. https://ascofame.org.co/web/quienes-somos/portafolio-servicios/
dc.source.bibliographicCitationBaker, D., Deekonda, P., Glasbey, J., Humm, G., Mohan, H., Nally, D., Srikandarajah, N., Storey, B., Walker, N., Brown, S., Hughes, I., Peiris, B., Tailor, B., Vithlani, G., Wcislo, K., Webb, S., Adams, N., Ahmed, W.-U.-R., Azam, S., … Zagaran, A. (2020). Core content of the medical school surgical curriculum: Consensus report from the association of surgeons in training (ASIT). International Journal of Surgery, 84, 186-193. https://doi.org/10.1016/j.ijsu.2019.12.036
dc.source.bibliographicCitationBalon, R. (2022). Multiple facets of conflict of interest. Annals of Clinical Psychiatry, 34(2). https://doi.org/10.12788/acp.0070
dc.source.bibliographicCitationBearman, M., & Ajjawi, R. (2024). When I say … artificial intelligence. Medical Education, medu.15408. https://doi.org/10.1111/medu.15408
dc.source.bibliographicCitationBond, M., Khosravi, H., De Laat, M., Bergdahl, N., Negrea, V., Oxley, E., Pham, P., Chong, S. W., & Siemens, G. (2024). A meta systematic review of artificial intelligence in higher education: A call for increased ethics, collaboration, and rigour. International Journal of Educational Technology in Higher Education, 21(1), 4. https://doi.org/10.1186/s41239-023-00436-z
dc.source.bibliographicCitationÇalışkan, S. A., Demir, K., & Karaca, O. (2022). Artificial intelligence in medical education curriculum: An e-Delphi study for competencies. PLOS ONE, 17(7), e0271872. https://doi.org/10.1371/journal.pone.0271872
dc.source.bibliographicCitationChan, K. S., & Zary, N. (2019). Applications and Challenges of Implementing Artificial Intelligence in Medical Education: Integrative Review. JMIR Medical Education, 5(1), e13930. https://doi.org/10.2196/13930
dc.source.bibliographicCitationCosta, A. (2002). The legacy of Hilda Taba. Journal of Curriculum and Supervision, 18(1), 56-62.
dc.source.bibliographicCitationDong, Y., Hou, J., Zhang, N., & Zhang, M. (2020). Research on How Human Intelligence, Consciousness, and Cognitive Computing Affect the Development of Artificial Intelligence. Complexity, 2020, 1-10. https://doi.org/10.1155/2020/1680845
dc.source.bibliographicCitationDuan, S., Liu, C., Rong, T., Zhao, Y., & Liu, B. (2025). Integrating AI in medical education: A comprehensive study of medical students’ attitudes, concerns, and behavioral intentions. BMC Medical Education, 25(1), 599. https://doi.org/10.1186/s12909-025-07177-9
dc.source.bibliographicCitationEpp, S., Reekie, M., Denison, J., De Bosch Kemper, N., Willson, M., & Marck, P. (2021). Radical transformation: Embracing constructivism and pedagogy for an innovative nursing curriculum. Journal of Professional Nursing, 37(5), 804-809. https://doi.org/10.1016/j.profnurs.2021.06.007
dc.source.bibliographicCitationEscobar, J., & Bonilla-Jiménez, F. I. (2017). Grupos focales: Una guía conceptual y metodológica. Cuadernos hispanoamericanos de psicología, 9(1), 51-67. http://biblioteca.udgvirtual.udg.mx/jspui/handle/123456789/957
dc.source.bibliographicCitationFazlollahi, A. M., Yilmaz, R., Winkler-Schwartz, A., Mirchi, N., Ledwos, N., Bakhaidar, M., Alsayegh, A., & Del Maestro, R. F. (2023). AI in Surgical Curriculum Design and Unintended Outcomes for Technical Competencies in Simulation Training. JAMA Network Open, 6(9), e2334658. https://doi.org/10.1001/jamanetworkopen.2023.34658
dc.source.bibliographicCitationGarcía Rillo, A. (2012). Aspectos éticos de la investigación en educación médica. Investigación en educación médica, 1(1), 28-34. http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S2007-50572012000100007&lng=es&tlng=es.
dc.source.bibliographicCitationGeneral Medical Council. (2023). Practical skills and procedures. GMC. https://www.gmc-uk.org/-/media/gmc-site/education/downloads/guidance/practical_skills_and_procedures_a4_july_2023.pdf
dc.source.bibliographicCitationGlossop, S. C., Bhachoo, H., Murray, T. M., Cherif, R. A., Helo, J. Y., Morgan, E., & Poacher, A. T. (2023). Undergraduate teaching of surgical skills in the UK: Systematic review. BJS Open, 7(5), zrad083. https://doi.org/10.1093/bjsopen/zrad083
dc.source.bibliographicCitationGreenwood, D. J., & Levin, M. (2007). Introduction to action research: Social research for social change (2nd ed). Sage Publications.
dc.source.bibliographicCitationGundumogula, M. (2020). Importance of Focus Groups in Qualitative Research. The International Journal of Humanities & Social Studies, 8(11). https://doi.org/10.24940/theijhss/2020/v8/i11/HS2011-082
dc.source.bibliographicCitationHernández Sampieri, R., & Fernández-Collado, C. F. (2014). Metodología de la investigación (P. Baptista Lucio, Ed.; 6a. ed.). McGraw-Hill Education.
dc.source.bibliographicCitationHuston, J. C., & Kaminski, N. (2023). A Picture Worth a Thousand Words, Created with One Sentence: Using Artificial Intelligence–created Art to Enhance Medical Education. ATS Scholar, 4(2), 145-151. https://doi.org/10.34197/ats-scholar.2022-0141PS
dc.source.bibliographicCitationJeyaraman, M., K, S. P., Jeyaraman, N., Nallakumarasamy, A., Yadav, S., & Bondili, S. K. (2023). ChatGPT in Medical Education and Research: A Boon or a Bane? Cureus. https://doi.org/10.7759/cureus.44316
dc.source.bibliographicCitationLee, J., Wu, A. S., Li, D., & Kulasegaram, K. (Mahan). (2021). Artificial Intelligence in Undergraduate Medical Education: A Scoping Review. Academic Medicine, 96(11S), S62-S70. https://doi.org/10.1097/ACM.0000000000004291
dc.source.bibliographicCitationLueddeke, G. R. (1999). Toward a Constructivist Framework for Guiding Change and Innovation in Higher Education. The Journal of Higher Education, 70(3), 235-260. https://doi.org/10.1080/00221546.1999.11780763
dc.source.bibliographicCitationMalkani, K. V., Tholey, R. M., Okusanya, O. T., & Grenda, T. R. (2022). Optimizing the general surgery clerkship: Opportunities for student engagement. The American Journal of Surgery, 223(2), 430-431. https://doi.org/10.1016/j.amjsurg.2021.08.026
dc.source.bibliographicCitationMasters, K. (2020). Artificial Intelligence developments in medical education: A conceptual and practical framework. MedEdPublish, 9(1). https://doi.org/10.15694/mep.2020.000239.1
dc.source.bibliographicCitationMoritz, S., Romeike, B., Stosch, C., & Tolks, D. (2023). Generative AI (gAI) in medical education: Chat-GPT and co. GMS Journal for Medical Education, 40(4). https://doi.org/10.3205/ZMA001636
dc.source.bibliographicCitationMota-Valtierra, G., Rodríguez-Reséndiz, J., & Herrera-Ruiz, G. (2019). Constructivism-Based Methodology for Teaching Artificial Intelligence Topics Focused on Sustainable Development. Sustainability, 11(17), 4642. https://doi.org/10.3390/su11174642
dc.source.bibliographicCitationMuthukrishnan, N., Maleki, F., Ovens, K., Reinhold, C., Forghani, B., & Forghani, R. (2020). Brief History of Artificial Intelligence. Neuroimaging Clinics of North America, 30(4), 393-399. https://doi.org/10.1016/j.nic.2020.07.004
dc.source.bibliographicCitationOnyura, B., Baker, L., Cameron, B., Friesen, F., & Leslie, K. (2016). Evidence for curricular and instructional design approaches in undergraduate medical education: An umbrella review. Medical Teacher, 38(2), 150-161. https://doi.org/10.3109/0142159X.2015.1009019
dc.source.bibliographicCitationOrtíz Ortíz, W. U. (2019). Modelos curriculares: Teorías y propuestas. https://www.researchgate.net/publication/336084659_MODELOS_CURRICULARES_TEORIAS_Y_PROPUESTAS
dc.source.bibliographicCitationPetrova, E., Dewing, J., & Camilleri, M. (2016). Confidentiality in participatory research: Challenges from one study. Nursing Ethics, 23(4), 442-454. https://doi.org/10.1177/0969733014564909
dc.source.bibliographicCitationPhillips, D. C. (1995). The good, the bad, and the ugly: The many faces of constructivism. Educational Researcher, 24(7), 5-12. https://doi.org/10.3102/0013189X024007005
dc.source.bibliographicCitationPosner, G. J. (2004). Analyzing the curriculum (3rd ed). McGraw-Hill.
dc.source.bibliographicCitationPrieto, M. A., & March Cerda, J. C. (2006). Investigación cualitativa: Paso a paso en el diseño de un estudio mediante grupos focales. En Antología preparada para el primer curso diplomado en desarrollo humano local: Género, infancia, población y salud (p. 323). Universitas Cuba.
dc.source.bibliographicCitationRampton, V., Mittelman, M., & Goldhahn, J. (2020). Implications of artificial intelligence for medical education. The Lancet Digital Health, 2(3), e111-e112. https://doi.org/10.1016/S2589-7500(20)30023-6
dc.source.bibliographicCitationRavenscroft, A. (2001). Designing e-Learning Interactions in the 21st Century: Reviewing and Rethinking the Role of European Theory. Journal of Education, 36(2), 133-156.
dc.source.bibliographicCitationSell, N. M., & Phitayakorn, R. (2020). Developing and refining a surgical curriculum. Surgery, 167(3), 528-531. https://doi.org/10.1016/j.surg.2019.06.008
dc.source.bibliographicCitationSteinert, J. I., Atika Nyarige, D., Jacobi, M., Kuhnt, J., & Kaplan, L. (2021). A systematic review on ethical challenges of ‘field’ research in low-income and middle-income countries: Respect, justice and beneficence for research staff? BMJ Global Health, 6(7), e005380. https://doi.org/10.1136/bmjgh-2021-005380
dc.source.bibliographicCitationStellefson, M., Paige, S. R., Alber, J. M., Barry, A. E., & James, D. (2015). Proposing Ethical Practice Standards for Community-Engaged Research in Health Education. American Journal of Health Education, 46(2), 61-66. https://doi.org/10.1080/19325037.2014.997942
dc.source.bibliographicCitationTaba, H. (1974). Curriculum development theory and practice (1962.a ed.). Troquel S.Ax.
dc.source.bibliographicCitationWang, S., Yang, L., & Li, M. (2023). The application of Artificial Intelligence to medical education in the last decade—A bibliometric analysis (Preprint). https://doi.org/10.2196/preprints.51411
dc.source.bibliographicCitationWebster, C. S. (2021). Artificial intelligence and the adoption of new technology in medical education. Medical Education, 55(1), 6-7. https://doi.org/10.1111/medu.14409
dc.source.bibliographicCitationWhite, J., Fu, Q., Hays, S., Sandborn, M., Olea, C., Gilbert, H., Elnashar, A., Spencer-Smith, J., & Schmidt, D. C. (2023). A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT. https://doi.org/10.48550/ARXIV.2302.11382
dc.source.bibliographicCitationWhite, J., Hays, S., Fu, Q., Spencer-Smith, J., & Schmidt, D. C. (2023). ChatGPT Prompt Patterns for Improving Code Quality, Refactoring, Requirements Elicitation, and Software Design. https://doi.org/10.48550/ARXIV.2303.07839
dc.source.instnameinstname:Universidad del Rosario
dc.source.reponamereponame:Repositorio Institucional EdocUR
dc.subjectInteligencia artificial
dc.subjectcurrículo
dc.subjecteducación médica
dc.subjectrotación clínica de cirugía general
dc.subjectdiseño curricular
dc.subjectinvestigación-acción
dc.subject.keywordArtificial intelligence
dc.subject.keywordCurriculum
dc.subject.keywordMedical education
dc.subject.keywordGeneral surgery clinical rotation
dc.subject.keywordCurriculum design
dc.subject.keywordAction research
dc.titleInteligencia artificial en el diseño curricular de una rotación clínica en cirugía general de pregrado de medicina. Un estudio de investigación – acción
dc.title.TranslatedTitleArtificial intelligence in the curriculum design of a clinical rotation in general surgery in medical schools. An action research study
dc.typemasterThesis
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersion
dc.type.spaTrabajo de grado
local.department.reportEscuela de Medicina y Ciencias de la Salud
local.regionesBogotá
Archivos
Bloque original
Mostrando1 - 1 de 1
Miniatura
Nombre:
Inteligencia_artificial_en_el_diseno_curricular.pdf
Tamaño:
925.75 KB
Formato:
Adobe Portable Document Format
Descripción:
Descargar
Colecciones
Maestría en Educación para Profesionales de la Salud