2,662
Views
8
CrossRef citations to date
0
Altmetric
Medical Education

Pre-class online video learning and class style expectation: patterns, association, and precision medical education

, , , &
Pages 1390-1401 | Received 08 Mar 2021, Accepted 05 Aug 2021, Published online: 23 Aug 2021

References

  • Challa K, Sayed A, Acharya Y. Modern techniques of teaching and learning in medical education: a descriptive literature review. MedEdPublish. 2021;10(1):18.
  • Hurtubise L, Martin B, Gilliland A, et al. To play or not to play: leveraging video in medical education. J Grad Med Educ. 2013;5(1):13–18.
  • Dominguez M, DiCapua D, Leydon G, et al. A neurology clerkship curriculum using video-based lectures and just-in-time teaching (JiTT). MedEdPORTAL. 2018;14:10691.
  • Brame CJ. Effective educational videos: principles and guidelines for maximizing student learning from video content. CBE Life Sci Educ. 2016;15:es6.
  • Dodson S, Roll I, Fong M, et al. An active viewing framework for video-based learning. In: Proceedings of the Fifth Annual ACM Conference on Learning at Scale; 2018. p. 1–4.
  • Fong M, Dodson S, Harandi NM, et al. Instructors desire student activity, literacy, and video quality analytics to improve video-based blended courses. In: Proceedings of the Sixth (2019) ACM Conference on Learning@ Scale; 2019. p. 1–10.
  • Seo K, Fels S, Yoon D, et al. Artificial intelligence for video-based learning at scale. In: Proceedings of the Seventh (2020) ACM Conference on Learning@ Scale; 2020. p. 215–217.
  • Seo K, Dodson S, Harandi NM, et al. Active learning with online video: the impact of learning context on engagement. Comput Educ. 2021;165:104132.
  • Clare B. A guide to precision medical education [cited 2021 Apr 28]. Available from: https://one45.com/analytics/precision-medical-education-guide/
  • Hart SA. Precision education initiative: moving towards personalized education. Mind Brain Educ. 2016;10(4):209–211.
  • Chahine S, Kulasegaram KM, Wright S, et al. A call to investigate the relationship between education and health outcomes using big data. Acad Med. 2018;93:829–832.
  • Duong MT, Rauschecker AM, Rudie JD, et al. Artificial intelligence for precision education in radiology. Br J Radiol. 2019;92(1103):20190389.
  • Theoret C, Ming X. Our education, our concerns: the impact on medical student education of COVID-19. Med Educ. 2020;54(7):591–592.
  • Emanuel EJ. The inevitable reimagining of medical education. JAMA. 2020;323(12):1127–1128.
  • Ho CM, Wang JY, Yeh CC, et al. Experience of applying threshold concepts in medical education. J Formos Med Assoc. 2021;120(4):1121–1126.
  • Sweller J. Cognitive load theory, learning difficulty, and instructional design. Learn Instr. 1994;4(4):295–312.
  • Sweller J. Cognitive load theory: recent theoretical advances. In: Plass J, Moreno R, Brünken R, editors. Cognitive load theory. Cambridge: Cambridge University Press; 2010. p. 29–47.
  • Mayer RE. Multimedia learning. 2nd ed. Cambridge: Cambridge University Press; 2009.
  • Mayer RE, Moreno R. Nine ways to reduce cognitive load in multimedia learning. Educ Psychol. 2003;38(1):43–52.
  • Hodell C. ISD from the ground up: a no-nonsense approach to instructional design. 4th ed. Alexandria (VA): Association for Talent Development; 2016.
  • World Federation for Medical Education. WFME global standards for quality improvement: basic medical education. The 2020 edition [cited 2021 Jul 10]. Available from: https://wfme.org/wp-content/uploads/2020/12/WFME-BME-Standards-2020.pdf
  • NTU COurses OnLine (NTU COOL) [cited 2020 Aug 28]. Available from: https://cool.ntu.edu.tw/login/portal
  • Ho CM, Wang JY, Yeh CC, et al. Efficient undergraduate learning of liver transplant: building a framework for teaching subspecialties to medical students. BMC Med Educ. 2018;18(1):161.
  • Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006;3(2):77–101.
  • Estacio RR, Raga RC. Jr Analyzing students online learning behavior in blended courses using moodle. AAOUJ. 2017;12(1):52–68.
  • Prensky M. Digital natives, digital immigrants part 1. On the Horizon. 2001;9(5):1–6.
  • Prensky M. Digital natives, digital immigrants, part 2: do they really think differently? On the Horizon. 2001;9(6):1–6.
  • Schwartz AC, McDonald WM, Vahabzadeh AB, et al. Keeping up with changing times in education: fostering lifelong learning of millennial learners. Focus. 2018;16(1):74–79.
  • Eckleberry-Hunt J, Tucciarone J. The challenges and opportunities of teaching “generation Y”. J Grad Med Educ. 2011;3(4):458–461.
  • Loh CYR, Teo TC. Understanding Asian students learning styles, cultural influence and learning strategies. J Educ Soc Policy. 2017;7:194–210.
  • Jalani NH, Lai CS. The example-problem-based learning model: applying cognitive load theory. Procedia Soc Behav Sci. 2015;195:872–880.
  • Martin S. Measuring cognitive load and cognition: metrics for technology-enhanced learning. Educ Res Eval. 2014;20(7–8):592–621.
  • Gogia L. Reconciling competency-based and precision medical education; 2018 [cited 2021 Jan 27]. Available from: https://googleguacamole.wordpress.com/2018/08/03/reconciling-competency-based-and-precision-medical-education/
  • Smitth P. Precision education in the School of Medicine's 125th year; 2018 [cited 2021 Jan 27]. Available from: https://www.hopkinsmedicine.org/office-of-johns-hopkins-physicians/best-practice-news/precision-education-in-the-school-of-medicines-125th-year
  • Cook CR, Kilgus SP, Burns MK. Advancing the science and practice of precision education to enhance student outcomes. J Sch Psychol. 2018;66:4–10.
  • Singhal S, Hough J, Cripps D. Twelve tips for incorporating gamification into medical education. MedEdPublish. 2019;8(3):67.