SAVREMENI TRENDOVI KORIŠĆENJA INFORMACIONO-KOMUNIKACIONIH TEHNOLOGIJA U MEDICINSKOJ EDUKACIJI
Ključne reči:
medicinska edukacija, informaciono-komunikacione tehnologije, onlajn učenje
Sažetak
Od devedesetih godina dvadesetog veka dešava se prodor tehnologija u oblasti edukacije povezan za sve dostupniju računarsku opremu, mobilne uređaje i pristup internetu. Tokom pandemije KOVID-19 došlo je do potpunog prelaska na onlajn učenje. U ovom periodu smo imali novi skok u razvoju tehnologija namenjenih edukaciji i ubrzanom prevođenju materijala u digitalni oblik. Trenutno smo svedoci prodora mašinskog učenja i veštačke inteligencije u nastavne procese ali i u kliničku praksu lekara.
Reference
1. Skinner BF. Teaching machines. Sci Am. 1961;205(5):91–102.
2. Skinner BF. Why we need teaching machines. Harv Educ Rev. 1961;31:377–98.
3. Milic NM, Trajkovic GZ, Bukumiric ZM, Cirkovic A, Nikolic IM, Milin JS, et al. Improving education in medical statistics: Implementing a blended learning model in the existing curriculum. PLoS One. 2016 Feb 1;11(2).
4. Means B, Toyama Y, Murphy R, Baki M. The effectiveness of online and blended learning: A meta-analysis of the empirical literature. Teach Coll Rec. 2013;115(3):1–47.
5. Allen IE, Seaman J. Learning on Demand. 2010.
6. I. Tutty J, Martin F. Effects of Practice Type in the Here and Now Mobile Learning Environment. i-manager’s Journal of Educational Technology. 2014 Sep 15;11(2):17–27.
7. Rung A, Warnke F, Mattheos N. Investigating the Use of Smartphones for Learning Purposes by Australian Dental Students. JMIR Mhealth Uhealth. 2014 Apr 30;2(2):e20.
8. Walsh K. Mobile Learning in Medical Education: Review. Vol. 25, Ethiopian journal of health sciences. 2015. p. 363–6.
9. Wallace S, Clark M, White J. “It’s on my iPhone”: Attitudes to the use of mobile computing devices in medical education, a mixed-methods study. BMJ Open. 2012;2(4).
10. Frolova E V., Rogach O V., Ryabova TM. Benefits and risks of switching to distance learning in a pandemic. Perspektivy Nauki i Obrazovania. 2020 Dec 31;48(6):78–88.
11. Grigorkevich A, Savelyeva E, Gaifullina N, Kolomoets E. Rigid class scheduling and its value for online learning in higher education. Educ Inf Technol (Dordr). 2022 Nov 1;27(9):12567–84.
12. Zawilinski LM, Richard KA, Henry LA. Inverting Instruction in Literacy Methods Courses. Journal of Adolescent & Adult Literacy [Internet]. 2016 May 11;59(6):695–708. Available from: https://ila.onlinelibrary.wiley.com/doi/10.1002/jaal.498
13. Odinokaya M, Krepkaia T, Sheredekina O, Bernavskaya M. The Culture of Professional Self-Realization as a Fundamental Factor of Students’ Internet Communication in the Modern Educational Environment of Higher Education. Educ Sci (Basel) [Internet]. 2019 Jul 17;9(3):187. Available from: https://www.mdpi.com/2227-7102/9/3/187
14. Ottinger ME, Farley LJ, Harding JP, Harry LA, Cardella JA, Shukla AJ. Virtual medical student education and recruitment during the COVID-19 pandemic. Vol. 34, Seminars in Vascular Surgery. W.B. Saunders; 2021. p. 132–8.
15. Rose S. Medical Student Education in the Time of COVID-19. JAMA - Journal of the American Medical Association. 2020 Jun 2;323(21):2131–2.
16. Watson A, McKinnon T, Prior SD, Richards L, Green CA. COVID-19: time for a bold new strategy for medical education. Vol. 25, Medical Education Online. Taylor and Francis Ltd.; 2020.
17. Bonderup Dohn Susan Cranmer Julie-Ann Sime Maarten de Laat Thomas Ryberg Editors Ree ections N. Networked Learning [Internet]. Available from: http://www.springer.com/series/11810
18. Kemp K, Baxa D, Cortes C. Exploration of a Collaborative Self-Directed Learning Model in Medical Education. Med Sci Educ. 2022 Feb 1;32(1):195–207.
19. Hassan Murad M, Varkey P. Annals Academy of Medicine Self-directed Learning-Self-directed Learning in Health Professions Education.
20. Greveson GC, Spencer JA. Self-directed learning - The importance of concepts and contexts. Vol. 39, Medical Education. 2005. p. 348–9.
21. Liu TH, Sullivan AM. A story half told: a qualitative study of medical students’ self-directed learning in the clinical setting. BMC Med Educ. 2021 Dec 1;21(1).
22. Krupat E, Richards JB, Sullivan AM, Fleenor TJ, Schwartzstein RM. Assessing the effectiveness of case-based collaborative learning via randomized controlled trial. In: Academic Medicine. Lippincott Williams and Wilkins; 2016. p. 723–9.
23. Loyens SMM, Magda J, Rikers RMJP. Self-directed learning in problem-based learning and its relationships with self-regulated learning. Educ Psychol Rev. 2008 Dec;20(4):411–27.
24. Zheng B, Ward A, Stanulis R. Self-regulated learning in a competency-based and flipped learning environment: learning strategies across achievement levels and years. Med Educ Online. 2020 Jan 1;25(1).
25. Wenger E. Communities of Practice. Cambridge University Press; 1998.
26. Jonathan Bergmann, Aaron Sams. Flip Your Classroom: Reach Every Student in Every Class Every Day. International Society for Technology in Education; 2012.
27. Tay Chatbot - Wikipedia [Internet]. [cited 2024 Feb 24]. Available from: https://en.wikipedia.org/wiki/Tay_(chatbot)
28. Májovský M, Černý M, Kasal M, Komarc M, Netuka D. Artificial Intelligence Can Generate Fraudulent but Authentic-Looking Scientific Medical Articles: Pandora’s Box Has Been Opened. J Med Internet Res. 2023 May 31;25:e46924.
29. Kalam KT, Rahman JM, Islam MdR, Dewan SMR. ChatGPT and mental health: Friends or foes? Health Sci Rep [Internet]. 2024 Feb 15;7(2). Available from: https://onlinelibrary.wiley.com/doi/10.1002/hsr2.1912
30. Chatterjee J, Dethlefs N. This new conversational AI model can be your friend, philosopher, and guide. and even your worst enemy. Vol. 4, Patterns. Cell Press; 2023.
31. Cascella M, Montomoli J, Bellini V, Bignami E. Evaluating the Feasibility of ChatGPT in Healthcare: An Analysis of Multiple Clinical and Research Scenarios. J Med Syst. 2023 Dec 1;47(1).
32. Mehta N, Harish V, Bilimoria K, Morgado F, Ginsburg S, Law M, et al. Knowledge and Attitudes on Artificial Intelligence in Healthcare: A Provincial Survey Study of Medical Students. MedEdPublish. 2021;10(1).
33. Lomis K, Jeffries P, Palatta A, Sage M, Sheikh J, Sheperis C, et al. Artificial Intelligence for Health Professions Educators. NAM Perspectives. 2021 Sep 8;
34. Lee J, Wu AS, Li D, Kulasegaram K (Mahan). Artificial Intelligence in Undergraduate Medical Education: A Scoping Review. Academic Medicine. 2021 Nov 27;96(11S):S62–70.
35. Peiffer-Smadja N, Rawson TM, Ahmad R, Buchard A, Pantelis G, Lescure FX, et al. Machine learning for clinical decision support in infectious diseases: a narrative review of current applications. Vol. 26, Clinical Microbiology and Infection. Elsevier B.V.; 2020. p. 584–95.
36. American Medical Association. Digital Health Study Physicians’ motivations and requirements for adopting digital clinical tools [Internet]. 2016 [cited 2024 Feb 17]. Available from: https://www.ama-assn.org/
37. Gong B, Nugent JP, Guest W, Parker W, Chang PJ, Khosa F, et al. Influence of Artificial Intelligence on Canadian Medical Students’ Preference for Radiology Specialty: ANational Survey Study. Acad Radiol. 2019 Apr 1;26(4):566–77.
38. Chockley K, Emanuel E. The End of Radiology? Three Threats to the Future Practice of Radiology. Journal of the American College of Radiology. 2016 Dec 1;13(12):1415–20.
39. Schier R. Artificial Intelligence and the Practice of Radiology: An Alternative View. Vol. 15, Journal of the American College of Radiology. Elsevier B.V.; 2018. p. 1004–7.
40. Obermeyer Z, Emanuel EJ. Predicting the Future — Big Data, Machine Learning, and Clinical Medicine. New England Journal of Medicine. 2016 Sep 29;375(13):1216–9.
41. Liew C. The future of radiology augmented with Artificial Intelligence: A strategy for success. Vol. 102, European Journal of Radiology. Elsevier Ireland Ltd; 2018. p. 152–6.
42. Tang A, Tam R, Cadrin-Chênevert A, Guest W, Chong J, Barfett J, et al. Canadian Association of Radiologists White Paper on Artificial Intelligence in Radiology. Vol. 69, Canadian Association of Radiologists Journal. Canadian Medical Association; 2018. p. 120–35.
2. Skinner BF. Why we need teaching machines. Harv Educ Rev. 1961;31:377–98.
3. Milic NM, Trajkovic GZ, Bukumiric ZM, Cirkovic A, Nikolic IM, Milin JS, et al. Improving education in medical statistics: Implementing a blended learning model in the existing curriculum. PLoS One. 2016 Feb 1;11(2).
4. Means B, Toyama Y, Murphy R, Baki M. The effectiveness of online and blended learning: A meta-analysis of the empirical literature. Teach Coll Rec. 2013;115(3):1–47.
5. Allen IE, Seaman J. Learning on Demand. 2010.
6. I. Tutty J, Martin F. Effects of Practice Type in the Here and Now Mobile Learning Environment. i-manager’s Journal of Educational Technology. 2014 Sep 15;11(2):17–27.
7. Rung A, Warnke F, Mattheos N. Investigating the Use of Smartphones for Learning Purposes by Australian Dental Students. JMIR Mhealth Uhealth. 2014 Apr 30;2(2):e20.
8. Walsh K. Mobile Learning in Medical Education: Review. Vol. 25, Ethiopian journal of health sciences. 2015. p. 363–6.
9. Wallace S, Clark M, White J. “It’s on my iPhone”: Attitudes to the use of mobile computing devices in medical education, a mixed-methods study. BMJ Open. 2012;2(4).
10. Frolova E V., Rogach O V., Ryabova TM. Benefits and risks of switching to distance learning in a pandemic. Perspektivy Nauki i Obrazovania. 2020 Dec 31;48(6):78–88.
11. Grigorkevich A, Savelyeva E, Gaifullina N, Kolomoets E. Rigid class scheduling and its value for online learning in higher education. Educ Inf Technol (Dordr). 2022 Nov 1;27(9):12567–84.
12. Zawilinski LM, Richard KA, Henry LA. Inverting Instruction in Literacy Methods Courses. Journal of Adolescent & Adult Literacy [Internet]. 2016 May 11;59(6):695–708. Available from: https://ila.onlinelibrary.wiley.com/doi/10.1002/jaal.498
13. Odinokaya M, Krepkaia T, Sheredekina O, Bernavskaya M. The Culture of Professional Self-Realization as a Fundamental Factor of Students’ Internet Communication in the Modern Educational Environment of Higher Education. Educ Sci (Basel) [Internet]. 2019 Jul 17;9(3):187. Available from: https://www.mdpi.com/2227-7102/9/3/187
14. Ottinger ME, Farley LJ, Harding JP, Harry LA, Cardella JA, Shukla AJ. Virtual medical student education and recruitment during the COVID-19 pandemic. Vol. 34, Seminars in Vascular Surgery. W.B. Saunders; 2021. p. 132–8.
15. Rose S. Medical Student Education in the Time of COVID-19. JAMA - Journal of the American Medical Association. 2020 Jun 2;323(21):2131–2.
16. Watson A, McKinnon T, Prior SD, Richards L, Green CA. COVID-19: time for a bold new strategy for medical education. Vol. 25, Medical Education Online. Taylor and Francis Ltd.; 2020.
17. Bonderup Dohn Susan Cranmer Julie-Ann Sime Maarten de Laat Thomas Ryberg Editors Ree ections N. Networked Learning [Internet]. Available from: http://www.springer.com/series/11810
18. Kemp K, Baxa D, Cortes C. Exploration of a Collaborative Self-Directed Learning Model in Medical Education. Med Sci Educ. 2022 Feb 1;32(1):195–207.
19. Hassan Murad M, Varkey P. Annals Academy of Medicine Self-directed Learning-Self-directed Learning in Health Professions Education.
20. Greveson GC, Spencer JA. Self-directed learning - The importance of concepts and contexts. Vol. 39, Medical Education. 2005. p. 348–9.
21. Liu TH, Sullivan AM. A story half told: a qualitative study of medical students’ self-directed learning in the clinical setting. BMC Med Educ. 2021 Dec 1;21(1).
22. Krupat E, Richards JB, Sullivan AM, Fleenor TJ, Schwartzstein RM. Assessing the effectiveness of case-based collaborative learning via randomized controlled trial. In: Academic Medicine. Lippincott Williams and Wilkins; 2016. p. 723–9.
23. Loyens SMM, Magda J, Rikers RMJP. Self-directed learning in problem-based learning and its relationships with self-regulated learning. Educ Psychol Rev. 2008 Dec;20(4):411–27.
24. Zheng B, Ward A, Stanulis R. Self-regulated learning in a competency-based and flipped learning environment: learning strategies across achievement levels and years. Med Educ Online. 2020 Jan 1;25(1).
25. Wenger E. Communities of Practice. Cambridge University Press; 1998.
26. Jonathan Bergmann, Aaron Sams. Flip Your Classroom: Reach Every Student in Every Class Every Day. International Society for Technology in Education; 2012.
27. Tay Chatbot - Wikipedia [Internet]. [cited 2024 Feb 24]. Available from: https://en.wikipedia.org/wiki/Tay_(chatbot)
28. Májovský M, Černý M, Kasal M, Komarc M, Netuka D. Artificial Intelligence Can Generate Fraudulent but Authentic-Looking Scientific Medical Articles: Pandora’s Box Has Been Opened. J Med Internet Res. 2023 May 31;25:e46924.
29. Kalam KT, Rahman JM, Islam MdR, Dewan SMR. ChatGPT and mental health: Friends or foes? Health Sci Rep [Internet]. 2024 Feb 15;7(2). Available from: https://onlinelibrary.wiley.com/doi/10.1002/hsr2.1912
30. Chatterjee J, Dethlefs N. This new conversational AI model can be your friend, philosopher, and guide. and even your worst enemy. Vol. 4, Patterns. Cell Press; 2023.
31. Cascella M, Montomoli J, Bellini V, Bignami E. Evaluating the Feasibility of ChatGPT in Healthcare: An Analysis of Multiple Clinical and Research Scenarios. J Med Syst. 2023 Dec 1;47(1).
32. Mehta N, Harish V, Bilimoria K, Morgado F, Ginsburg S, Law M, et al. Knowledge and Attitudes on Artificial Intelligence in Healthcare: A Provincial Survey Study of Medical Students. MedEdPublish. 2021;10(1).
33. Lomis K, Jeffries P, Palatta A, Sage M, Sheikh J, Sheperis C, et al. Artificial Intelligence for Health Professions Educators. NAM Perspectives. 2021 Sep 8;
34. Lee J, Wu AS, Li D, Kulasegaram K (Mahan). Artificial Intelligence in Undergraduate Medical Education: A Scoping Review. Academic Medicine. 2021 Nov 27;96(11S):S62–70.
35. Peiffer-Smadja N, Rawson TM, Ahmad R, Buchard A, Pantelis G, Lescure FX, et al. Machine learning for clinical decision support in infectious diseases: a narrative review of current applications. Vol. 26, Clinical Microbiology and Infection. Elsevier B.V.; 2020. p. 584–95.
36. American Medical Association. Digital Health Study Physicians’ motivations and requirements for adopting digital clinical tools [Internet]. 2016 [cited 2024 Feb 17]. Available from: https://www.ama-assn.org/
37. Gong B, Nugent JP, Guest W, Parker W, Chang PJ, Khosa F, et al. Influence of Artificial Intelligence on Canadian Medical Students’ Preference for Radiology Specialty: ANational Survey Study. Acad Radiol. 2019 Apr 1;26(4):566–77.
38. Chockley K, Emanuel E. The End of Radiology? Three Threats to the Future Practice of Radiology. Journal of the American College of Radiology. 2016 Dec 1;13(12):1415–20.
39. Schier R. Artificial Intelligence and the Practice of Radiology: An Alternative View. Vol. 15, Journal of the American College of Radiology. Elsevier B.V.; 2018. p. 1004–7.
40. Obermeyer Z, Emanuel EJ. Predicting the Future — Big Data, Machine Learning, and Clinical Medicine. New England Journal of Medicine. 2016 Sep 29;375(13):1216–9.
41. Liew C. The future of radiology augmented with Artificial Intelligence: A strategy for success. Vol. 102, European Journal of Radiology. Elsevier Ireland Ltd; 2018. p. 152–6.
42. Tang A, Tam R, Cadrin-Chênevert A, Guest W, Chong J, Barfett J, et al. Canadian Association of Radiologists White Paper on Artificial Intelligence in Radiology. Vol. 69, Canadian Association of Radiologists Journal. Canadian Medical Association; 2018. p. 120–35.
Objavljeno
2025/07/18
Broj časopisa
Rubrika
Mini pregledni članak