N.º 33 (2025): Out - Dez
Educação Médica Pré e Pós-graduada

Ensino médico – tipos de curriculos e desafios da IA

PDF
  • Teresa Figueiredo
Teresa Figueiredo
Médica Radiologista, Professora Auxiliar da Faculdade de Medicina da UALG

Publicado 04/11/2026

Palavras-chave

  • Educação médica,
  • Método Based Learning,
  • Método Problem Based Learning

Direitos de Autor (c) 2026 Teresa Figueiredo

Creative Commons License

Este trabalho encontra-se publicado com a Licença Internacional Creative Commons Atribuição 4.0.

Como Citar

1.
Figueiredo T. Ensino médico – tipos de curriculos e desafios da IA. Alg Med [Internet]. 11 de abril de 2026 [citado 18 de abril de 2026];(33):6-11. Disponível em: https://algarvemedico.org/index.php/am/article/view/24

Resumo

Medical education in the 21st century is undergoing a profound transformation, driven by demographic, technological, and cultural changes, demanding more flexible, student-centered, and competency-based training models. The integration of artificial intelligence (AI) emerges as an additional axis of this change, with the potential to personalize learning and enhance clinical skills, but also with pedagogical, ethical, and dehumanizing risks that need to be carefully regulated.

PDF

Downloads

Os dados de download ainda não estão disponíveis.

Referências

  1. Gruppen LD, Burkhardt JC, Fitzgerald JT, et al. Competency based education: programme design and challenges to implementation. Med Educ. 2016;50(5):532 9.
  2. Wartman SA, Combs CD. Medical education must move from the information age to the age of artificial intelligence. Acad Med. 2018;93(8):1107 9.
  3. Chan KS, Zary N. Applications and challenges of implementing artificial intelligence in medical education: integrative review. JMIR Med Educ. 2019;5(1):e13930.
  4. Park YS, Konge L, Artino AR Jr. The positivism paradigm of research. Acad Med. 2020;95(5):690 4.
  5. Masters K, Ellaway R, Topps D, Archibald D, Hogue RJ. Mobile technologies in medical education: AMEE Guide No. 105. Med Teach. 2016;38(6):537 49.
  6. Lucey CR, Johnston SC. The transformational effects of COVID 19 on medical education. JAMA. 2020;324(11):1033 4.
  7. Rawson KA, Dunlosky J, McDaniel MA, Bjork RA, Hughes A. Using evidence- based learning strategies to improve medical education. Med Sci Educ. 2023;33(3):911 21
  8. Hunderfund ANL, Dyrbye LN, Starr SR, Mandrekar JN, Tilburt JC, Starr SR, et al. Methods of teaching evidence- based practice: a systematic review. BMC Med Educ. 2022;22(1):742. doi:10.1186/s12909-022-03812-x
  9. Albarqouni L, Hoffmann T, Glasziou P, et al. Methods for teaching evidence- based practice: a scoping review. BMC Med Educ. 2019;19(1):267
  10. Flores N, et al. Enhancing clinical education: evidence- based strategies. Eur Sci Med Dent. 2025; (artigo online first)
  11. Silva J, et al. Active methodologies and didactic techniques in medical education. Med Teach. 2025;
  12. Besche HC, King RW, Shafer KM, Fleet SE, Charles JF, Kaplan TB, et al. Effective and engaging active learning in the medical school classroom: lessons from Case- Based Collaborative Learning. J Med Educ Curric Dev. 2025;12:1 10
  13. Shafer KM, Pusic MV, Halpern SD, et al. The Case- Based Collaborative Learning peer observation tool. MedEDPORTAL. 2017;13:10583
  14. Besche HC, et al. A step- by- step guide to Case- Based Collaborative Learning (CBCL). Harvard Medical School; 2025. Disponível em: https://www.academia.edu/ (acesso on line 12.02.2026)
  15. Martin- Gonzalez R, et al. Perception of medical students on the use of Case- Based Collaborative Learning in a human physiology course. Clin Teach. 2024;
  16. Knopp R, Liu X, Patel R, et al. Integrating artificial intelligence into medical education: a roadmap for curricular innovation. Med Teach. 2025;47(7):e1234 42. doi:10.1080/10872981.2025.2531177
  17. Ahsan Z. Integrating artificial intelligence into medical education: a narrative review. BMC Med Educ. 2025;25(1):1187. doi:10.1186/s12909-025-07744-0
  18. Taylor JJ, Wong R, Osei- Tutu K, et al. AIFM- ed curriculum framework for postgraduate family medicine education: integrating artificial intelligence competencies. JMIR Med Educ. 2025;11(1):e66828
  19. Zhang Y, et al. Artificial intelligence in undergraduate medical education. Med Educ. 2025;59(11):1234 45
  20. Singh P, et al. Integrating generative artificial intelligence into medical education. Acad Med. 2025;100(4):567 73
  21. Miller DD, Patel VL, et al. AI- PACE: a framework for integrating AI into medical education. arXiv [preprint]. 2026 Feb 10. arXiv:2602.10527