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The evaluation of an open source online training system for teaching 12 lead electrocardiographic interpretation

Breen, Cathal, J, Zhu, Tingting, Bond, Raymond, Finlay, D and Clifford, Gari (2016) The evaluation of an open source online training system for teaching 12 lead electrocardiographic interpretation. Journal of Electrocardiology, 49 (3). pp. 454-461. [Journal article]

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URL: http://www.sciencedirect.com/science/article/pii/S0022073616000583

DOI: 10.1016/j.jelectrocard.2016.02.003

Abstract

ntroductionThe aim of this study is to present and evaluate the integration of a low resource JavaScript based ECG training interface (CrowdLabel) and a standardised curriculum for self-guided tuition in ECG interpretation.MethodsParticipants practiced interpreting ECGs weekly using the CrowdLabel interface to assist with the learning of the traditional didactic taught course material during a 6 week training period. To determine competency students were tested during week 7.ResultsA total of 245 unique ECG cases were submitted by each student. Accuracy scores during the training period ranged from 0–59.5% (median = 33.3%). Conversely accuracy scores during the test ranged from 30 – 70% (median = 37.5%) (p < 0.05). There was no correlation between students who interpreted high numbers of ECGs during the training period and their marks obtained.ConclusionsCrowdLabel is shown to be a readily accessible dedicated learning platform to support ECG interpretation competency.KeywordsE Learning; ECG; Pedagogy; Assessment; Healthcare Science

Item Type:Journal article
Keywords:E Learning; ECG; Pedagogy; Assessment; Healthcare Science
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Faculty of Computing & Engineering > School of Engineering
Faculty of Life and Health Sciences
Faculty of Life and Health Sciences > School of Health Sciences
Research Institutes and Groups:Institute of Nursing and Health Research > Centre for Health and Rehabilitation Technologies
Institute of Nursing and Health Research
Engineering Research Institute
Engineering Research Institute > Nanotechnology & Integrated BioEngineering Centre (NIBEC)
Computer Science Research Institute > Smart Environments
Computer Science Research Institute
ID Code:33374
Deposited By: Mr Cathal Breen
Deposited On:24 Feb 2016 00:15
Last Modified:15 May 2017 15:17

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