The ASIC Framework: An Alternative Operational Matrix to Support the Technology and Innovations in Medical Education based on the Primary Learning Domains

Document Type : Commentary

Author

Department of Anatomy, Division of Basic Medical Science University of Global Health Equity Kigali Heights, Rwanda, Africa

Abstract

Educational technology and innovations as well as creative approaches to teaching, learning, and training have become increasingly integral to the delivery of medical education. Arguably, the COVID-19-related challenges of the years 2020-2022 would mark a watershed point in terms of the integration of digital technology and innovations into education, especially medical education. This article presents an operational matrix, aligned with learning in the primary domains, namely cognitive, psychomotor, and effective domains, to support the medical education-associated technology and innovations. It is therefore named the ASIC-CPA operational matrix or the alternative ASIC Framework operational matrix relative to the originally developed and published matrix. Accordingly, the ASIC Framework has been developed, as a foremost instrument to ensure the adaptation, standardisation, and integration of technology in compliant ways. An operational tool or matrix is conducive to ensuring that this ASIC Framework could be used in the most beneficial ways. This article presents an operational matrix that has been developed with emphasis on how EdTech and innovations influence learning in the domains of knowledge or the cognitive, skill-related, or psychomotor and attitude or the affective. Utilizing this tool, technology operators can specifically align their use of educational technology and innovations with learning in these basic domains.

Keywords


Owolabi J. Proposing a Framework Guide for the Integration of Educational Technologies and Innovations into the Teaching of Anatomy and Medical Sciences: The ASIC Framework. Adv Med Educ Pract. 2021;12:1277-1282. doi:10.2147/AMEP.S338262.
Horton R. Offline: COVID-19 is not a pandemic. Lancet. 2020; 396:874. doi: 10.1016/S0140-6736(20)32000-6.
Hulvej-Rod M, Hulvej-Rod N. Towards a syndemic public health response to COVID-19. Scand J Public Health. 2021; 49:14–16. doi: 10.1177/1403494820982862.
(4)Santana EA, Orquera PA, Valenzuela JJ, Orellana MI, Gold MH, De La Paz Garcia G. Anatomical software as a tool in the teaching-learning process of human anatomy. Literature review. FASEB J. 2020;34:1. doi:10.1096/fasebj.2020.34.s1.09262.
Zargaran A, Turki MA, Bhaskar J, Spiers H, Zargaran D. The role of technology in anatomy teaching: striking the right balance. Advan Med Educ Pract. 2020;11:259–266. doi:10.2147/AMEP.S240150.
Zhao J, Xu X, Jiang H, et al. The effectiveness of virtual reality-based technology on anatomy teaching: a meta-analysis of randomized controlled studies. BMC Med Educ. 2020;20:127. doi:10.1186/s12909-020-1994-z.
Dawidziuk A, Kawka M, Szyszka B, Wadunde I, Ghimire A. Global access to technology-enhanced medical education during the COVID-19 pandemic: the role of students in narrowing the gap. Glob Health Sci Pract. 2021;9(1):10–14. doi:10.9745/GHSP-D-20-00455.
Moran J, Briscoe G,  Peglow S. Current Technology in Advancing Medical Education: Perspectives for Learning and Providing Care. Acad Psychiatry. 2018; 42: 796–799. doi:10.1007/s40596-018-0946-y.
Han ER, Yeo S, Kim MJ et al. Medical education trends for future physicians in the era of advanced technology and artificial intelligence: an integrative review. BMC Med Educ. 2019; 19:460. doi:10.1186/s12909-019-1891-5.
Roussin CJ, Weinstock P. SimZones: An Organizational Innovation for Simulation Programs and Centers. Acad Med. 2017;92(8):1114-1120. doi: 10.1097/ACM.0000000000001746. PMID: 28562455.
Roussin C, Sawyer T, Weinstock P. Assessing competency using simulation: the SimZones approachBMJ Simulation and Technology Enhanced Learning 2020;6:262-267.
Motola I, Devine LA, Chung HS, Sullivan JE, Issenberg SB. Simulation in healthcare education: a best evidence practical guide. AMEE Guide No. 82. Med Teach. 2013; 35(10):e1511-30. doi: 10.3109/0142159X.2013.818632. PMID: 23941678.
Linderman SW, Appukutty AJ, Russo MV et al. Advancing healthcare technology education and innovation in academia. Nat Biotechnol. 2020; 38:1213–1217. doi.org/10.1038/s41587-020-0689-7.
Fallavollita P. Innovative Technologies for Medical Education, Human Anatomy - Reviews and Medical Advances, Alina Maria Sisu, IntechOpen. 2017. doi: 10.5772/intechopen.68775. Available from: https://www.intechopen.com/chapters/55203.
Wartman, SA, Combs, CD. Medical education must move from the information age to the age of artificial intelligence. Acad Med. 2018;93:1107-1109.
Masters K. Artificial intelligence in medical education. Med Teach. 2019;41:976-980.
Chan KS, Zary N. Applications and challenges of implementing artificial intelligence in medical education: integrative review. JMIR Med Educ. 2019;5:e13930.
Wood EA, Ange BL, Miller DD. Are We Ready to Integrate Artificial Intelligence Literacy into Medical School Curriculum: Students and Faculty Survey. Journal of Medical Education and Curricular Development. 2021; doi:10.1177/23821205211024078
Shaw N. Medical education & health informatics: time to join the 21st century? Stud Health Technol Inform. 2010;160(Pt 1):567-71. PMID: 20841750.
Webster PC. Curricula reform needed to develop more tech-savvy physicians. CMAJ : Canadian Medical Association journal ( journal de l'Association medicale Canadienne) 2011; 183(10): E621–E622. doi:10.1503/cmaj.109-3913.
Qian Z-W, Huang G. Human Capital and Innovation Ability in Medical Education: An Empirical Study. EURASIA Journal of Mathematics Science and Technology Education. 2017; 13(8):5395-5403.