Multimodal Assessment in Clinical Simulations: A Guide for Moving Towards Precision Education

McGaghie WC, Issenberg SB, Petrusa ER, Scalese RJ. A critical review of simulation-based medical education research: 2003–2009. Med Educ. 2010;44(1):50–63. https://doi.org/10.1111/j.1365-2923.2009.03547.x.

Article  Google Scholar 

Guinez-Molinos S, Martinez-Molina A, Gomar-Sancho C, Arias Gonzalez VB, Szyld D, Garcia Garrido E, et al. A collaborative clinical simulation model for the development of competencies by medical students. Med Teach. 2017;39(2):195–202. https://doi.org/10.1080/0142159X.2016.1248913.

Article  Google Scholar 

Higgins M, Madan C, Patel R. Development and decay of procedural skills in surgery: A systematic review of the effectiveness of simulation-based medical education interventions. Surgeon. 2021;19(4):e67–77. https://doi.org/10.1016/j.surge.2020.07.013.

Article  Google Scholar 

Urbina J, Monks SM. Validating Assessment Tools in Simulation. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing. 2023.. Available from: https://www.ncbi.nlm.nih.gov/books/NBK560531/.

Ryall T, Judd BK, Gordon CJ. Simulation-based assessments in health professional education: a systematic review. J Multidiscip Healthc. 2016;9:69–82. https://doi.org/10.2147/JMDH.S92695.

Article  Google Scholar 

Dias RD, Gupta A, Yule SJ. Using machine learning to assess physician competence: a systematic review. Acad Med. 2019;94(3):427–39. https://doi.org/10.1097/ACM.0000000000002414.

Article  Google Scholar 

Sallaberry LH, Tori R, Nunes FLS. Automatic performance assessment in three-dimensional interactive haptic medical simulators: a systematic review. ACM Comput Surv. 2022;55(7):1–35. https://doi.org/10.1145/3539222.

Article  Google Scholar 

Dick-Smith F, Elliott D, Martinez-Maldonado R, Power T. Comparing real-time feedback modalities to support optimal cardiopulmonary resuscitation for undergraduate nursing students: a quasi-experimental cross-over simulation study. Clin Simul Nurs. 2020;44:59–67. https://doi.org/10.1016/j.ecns.2020.01.007.

Article  Google Scholar 

Di Mitri D, Schneider J, Specht M, Drachsler H. Detecting mistakes in CPR training with multimodal data and neural networks. Sensors (Basel). 2019;19(14). https://doi.org/10.3390/s19143099

Vilmann AS, Norsk D, Svendsen MBS, Reinhold R, Svendsen LB, Park YS, et al. Computerized feedback during colonoscopy training leads to improved performance: a randomized trial. Gastrointest Endosc. 2018;88(5):869–76. https://doi.org/10.1016/j.gie.2018.07.008.

Article  Google Scholar 

Toy S, Huh DD, Materi J, Nanavati J, Schwengel DA. Use of neuroimaging to measure neurocognitive engagement in health professions education: a scoping review. Med Educ Online. 2022;27(1):2016357. https://doi.org/10.1080/10872981.2021.2016357.

Article  Google Scholar 

Toy S, Ozsoy S, Shafiei S, Antonenko P, Schwengel D. Using electroencephalography to explore neurocognitive correlates of procedural proficiency: A pilot study to compare experts and novices during simulated endotracheal intubation. Brain Cogn. 2023;165:105938. https://doi.org/10.1016/j.bandc.2022.105938.

Article  Google Scholar 

Di Mitri D, Schneider J, Limbu B, Mat Sanusi KA, Klemke R. Multimodal learning experience for deliberate practice. In: Publishing CSI, editor. The Multimodal Learning Analytics Handbook2022. p. 183–204. https://doi.org/10.1007/978-3-031-08076-0_8

Villagran I, Moenne-Loccoz C, Aguilera V, Garcia V, Reyes JT, Rodriguez S, et al. Biomechanical analysis of expert anesthesiologists and novice residents performing a simulated central venous access procedure. PLoS ONE. 2021;16(4):e0250941. https://doi.org/10.1371/journal.pone.0250941.

Article  Google Scholar 

Ebina K, Abe T, Hotta K, Higuchi M, Furumido J, Iwahara N, et al. Objective evaluation of laparoscopic surgical skills in wet lab training based on motion analysis and machine learning. Langenbecks Arch Surg. 2022;407(5):2123–32. https://doi.org/10.1007/s00423-022-02505-9.

Article  Google Scholar 

Belmar F, Gaete MI, Escalona G, Carnier M, Duran V, Villagran I, et al. Artificial intelligence in laparoscopic simulation: a promising future for large-scale automated evaluations. Surg Endosc. 2023;37(6):4942–6. https://doi.org/10.1007/s00464-022-09576-1.

Article  Google Scholar 

Toy S, Miller CR, Daly Guris RJ, Duarte SS, Koessel S, Schiavi A. Evaluation of 3 cognitive load measures during repeated simulation exercises for novice anesthesiology residents. Simul Healthc. 2020;15(6):388–96. https://doi.org/10.1097/SIH.0000000000000458.

Article  Google Scholar 

Lapierre A, Arbour C, Maheu-Cadotte M-A, Vinette B, Fontaine G, Lavoie P. Association between clinical simulation design features and novice healthcare professionals’ cognitive load: a systematic review and meta-analysis. Simul Gaming. 2022;53(5):538–63. https://doi.org/10.1177/10468781221120599.

Article  Google Scholar 

Oliveira Silva G, Oliveira FSE, Coelho ASG, Cavalcante A, Vieira FVM, Fonseca LMM, et al. Effect of simulation on stress, anxiety, and self-confidence in nursing students: Systematic review with meta-analysis and meta-regression. Int J Nurs Stud. 2022;133:104282. https://doi.org/10.1016/j.ijnurstu.2022.104282.

Article  Google Scholar 

Cutrer WB, Spickard WA 3rd, Triola MM, Allen BL, Spell N 3rd, Herrine SK, et al. Exploiting the power of information in medical education. Med Teach. 2021;43(sup2):S17–24. https://doi.org/10.1080/0142159X.2021.1925234.

Article  Google Scholar 

Duong MT, Rauschecker AM, Rudie JD, Chen PH, Cook TS, Bryan RN, et al. Artificial intelligence for precision education in radiology. Br J Radiol. 2019;92(1103):20190389. https://doi.org/10.1259/bjr.20190389.

Article  Google Scholar 

Ho CM, Yeh CC, Wang JY, Hu RH, Lee PH. Pre-class online video learning and class style expectation: patterns, association, and precision medical education. Ann Med. 2021;53(1):1390–401. https://doi.org/10.1080/07853890.2021.1967441.

Article  Google Scholar 

Ho CM, Yeh CC, Wang JY, Hu RH, Lee PH. Linking the choice of the class format and preclass learning experiences sheds light on a step further in blended medical education. Med Educ Online. 2023;28(1):2186207. https://doi.org/10.1080/10872981.2023.2186207.

Article  Google Scholar 

Qushem UB, Christopoulos A, Oyelere SS, Ogata H, Laakso MJ. Multimodal technologies in precision education: providing new opportunities or adding more challenges? Educ Sci. 2021;11(7). https://doi.org/10.3390/educsci11070338

Lang C, Siemens G, Wise A, Gasevic D. Handbook of Learning Analytics. New York: SOLAR, Society for Learning Analytics and Research. 2017. https://doi.org/10.18608/hla17

Giannakos M, Spikol D, Di Mitri D, Sharma K, Ochoa X, Hammad R. Introduction to multimodal learning analytics. In: Giannakos M, Spikol D, Di Mitri D, Sharma K, Ochoa X, Hammad R, editors. The Multimodal Learning Analytics Handbook. Cham: Springer International Publishing; 2022. p. 3–28. https://doi.org/10.1007/978-3-031-08076-0_1

Martinez-Maldonado R, Power T, Hayes C, Abdiprano A, Vo T, Axisa C, et al., editors. Analytics meet patient manikins: Challenges in an authentic small-group healthcare simulation classroom. Proceedings of the seventh international learning analytics & knowledge conference. 2017. https://doi.org/10.1145/3027385.3027401

Martinez-Maldonado R, Echeverria V, Fernandez Nieto G, Buckingham Shum S, editors. From data to insights: A layered storytelling approach for multimodal learning analytics. Proceedings of the 2020 chi conference on human factors in computing systems. 2020. https://doi.org/10.1145/3313831.3376148

Le LH, Nguyen HD, Crane M, Mai TT, editors. Multimedia learning analytics feedback in simulation-based training: A brief review. Proceedings of the 1st ACM Workshop on AI-Powered Q&A Systems for Multimedia. 2024. https://doi.org/10.1145/3643479.3662053

Worsley M, Blikstein P, editors. Towards the development of multimodal action based assessment. Proceedings of the third international conference on learning analytics and knowledge. 2013. https://doi.org/10.1145/2460296.2460315

Thomas PA, Kern DE, Hughes MT, Tackett SA, Chen BY. Curriculum development for medical education: a six-step approach: JHU press; 2022. https://doi.org/10.56021/9781421444116

Watts PI, McDermott DS, Alinier G, Charnetski M, Ludlow J, Horsley E, et al. Healthcare simulation standards of best practice™ simulation design. Clin Simul Nurs. 2021;58:14–21. https://doi.org/10.1016/j.ecns.2021.08.009.

Article  Google Scholar 

Rivière E, Saucier D, Lafleur A, Lacasse M, Chiniara G. Twelve tips for efficient procedural simulation. Med Teach. 2018;40(7):743–51. https://doi.org/10.1080/0142159X.2017.1391375.

Article  Google Scholar 

Boulet JR, Murray DJ, Warner DS. Simulation-based assessment in anesthesiology: requirements for practical implementation. J Am Soc Anesthesiologists. 2010;112(4):1041–52. https://doi.org/10.1097/ALN.0b013e3181cea265.

Article  Google Scholar 

Cloude EB, Wiedbusch MD, Dever DA, Torre D, Azevedo R. The Role of Metacognition and Self-regulation on Clinical Reasoning: Leveraging Multimodal Learning Analytics to Transform Medical Education. In: Giannakos M, Spikol D, Di Mitri D, Sharma K, Ochoa X, Hammad R, editors. The Multimodal Learning Analytics Handbook. Cham: Springer International Publishing. 2022. p. 105–29. https://doi.org/10.1007/978-3-031-08076-0_5

Hammad R, Bahja M, Kuhail MA. Bridging the Gap Between Informal Learning Pedagogy and Multimodal Learning Analytics. In: Giannakos M, Spikol D, Di Mitri D, Sharma K, Ochoa X, Hammad R, editors. The Multimodal Learning Analytics Handbook. Cham: Springer International Publishing. 2022. p. 159–79. https://doi.org/10.1007/978-3-031-08076-0_7

Alwahaby H, Cukurova M, Papamitsiou Z, Giannakos M. The evidence of impact and ethical considerations of Multimodal Learning Analytics: A Systematic Literature Review. The multimodal learning analytics handbook. 2022:289–325. https://doi.org/10.1007/978-3-031-08076-0_12

Cook DA, Brydges R, Zendejas B, Hamstra SJ, Hatala R. Technology-enhanced simulation to assess health professionals: a systematic review of validity evidence, research methods, and reporting quality. Acad Med. 2013;88(6):872–83. https://doi.org/10.1097/ACM.0b013e31828ffdcf.

Article  Google Scholar 

Di Mitri D, Schneider J, Specht M, Drachsler H. From signals to knowledge: A conceptual model for multimodal learning analytics. J Comput Assist Learn. 2018;34(4):338–49. https://doi.org/10.1111/jcal.12288.

Article  Google Scholar 

Yudkowsky R, Downing SM, Tekian A. Standard setting. In: Yudkowsky R, Park Y, Downing S, editors. Assessment in health professions education: Routledge. 2019. p. 86–105. https://www.taylorfrancis.com/books/edit/10.4324/9781138054394/assessment-health-professions-education-rachel-yudkowsky-yoon-soo-park-steven-downing

Yudkowsky R, Park YS, Lineberry M, Knox A, Ritter EM. Setting mastery learning standards. Acad Med. 2015;90(11):1495–500. https://doi.org/10.1097/ACM.0000000000000887.

Article  Google Scholar 

Feldman M, Lazzara EH, Vanderbilt AA, DiazGranados D. Rater training to support high-stakes simulation-based assessments. J Contin Educ Health Prof. 2012;32(4):279–86. https://doi.org/10.1002/chp.21156

Gawad N, Fowler A, Mimeault R, Raiche I. The inter-rater reliability of technical skills assessment and retention of rater training. J Surg Educ. 2019;76(4):1088–93. https://doi.org/10.1016/j.jsurg.2019.01.001.

Article  Google Scholar 

Pacheco Granda FA, Salik I. Simulation Training and Skill Assessment in Critical Care. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing. 2023. Available from: https://www.ncbi.nlm.nih.gov/books/NBK549895/.

Saqr M. A literature review of empirical research on learning analytics in medical education. Int J Health Sci (Qassim). 2018;12(2):77–82.

Google Scholar 

Ellaway RH, Pusic MV, Galbraith RM, Cameron T. Developing the role of big data and analytics in health professional education. Med Teach. 2014;36(3):216–22. https://doi.org/10.3109/0142159X.2014.874553.

Article  Google Scholar 

Pappada S, Owais MH, Aouthmany S, Schneiderman J, Toy S, Schiavi A, et al. Personalizing simulation-based medical education: the case for novel learning management systems. Journal of Healthcare Simulation. 2022:1–8. https://doi.org/10.54531/mngy8113

Verbert K, Govaerts S, Duval E, Santos JL, Van Assche F, Parra G, et al. Learning dashboards: an overview and future research opportunities. Pers Ubiquit Comput. 2014;18(6):1499–514. https://doi.org/10.1007/s00779-013-0751-2.

Article  Google Scholar 

Schwendimann BA, Rodriguez-Triana MJ, Vozniuk A, Prieto LP, Boroujeni MS, Holzer A, et al. Perceiving learning at a glance: a systematic literature review of learning dashboard research. Ieee T Learn Technol. 2017;10(1):30–41. ht

留言 (0)

沒有登入
gif