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

Cathal, J Breen, Tingting Zhu, Raymond Bond, D Finlay, Gari Clifford

Research output: Contribution to journalArticle

5 Citations (Scopus)

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
LanguageEnglish
Pages454-461
JournalJournal of Electrocardiology
Volume49
Issue number3
Early online date11 Feb 2016
DOIs
Publication statusPublished - 14 Mar 2016

Fingerprint

Online Systems
Teaching
Electrocardiography
Learning
Students
Curriculum
Delivery of Health Care

Keywords

  • E Learning
  • ECG
  • Pedagogy
  • Assessment
  • Healthcare Science

Cite this

@article{d8cc3516898a44d2b37fd83f20a28edd,
title = "The evaluation of an open source online training system for teaching 12 lead electrocardiographic interpretation",
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",
keywords = "E Learning, ECG, Pedagogy, Assessment, Healthcare Science",
author = "Breen, {Cathal, J} and Tingting Zhu and Raymond Bond and D Finlay and Gari Clifford",
year = "2016",
month = "3",
day = "14",
doi = "10.1016/j.jelectrocard.2016.02.003",
language = "English",
volume = "49",
pages = "454--461",
journal = "Journal of Electrocardiology",
issn = "0022-0736",
publisher = "Elsevier",
number = "3",

}

The evaluation of an open source online training system for teaching 12 lead electrocardiographic interpretation. / Breen, Cathal, J; Zhu, Tingting; Bond, Raymond; Finlay, D; Clifford, Gari.

In: Journal of Electrocardiology, Vol. 49, No. 3, 14.03.2016, p. 454-461.

Research output: Contribution to journalArticle

TY - JOUR

T1 - The evaluation of an open source online training system for teaching 12 lead electrocardiographic interpretation

AU - Breen, Cathal, J

AU - Zhu, Tingting

AU - Bond, Raymond

AU - Finlay, D

AU - Clifford, Gari

PY - 2016/3/14

Y1 - 2016/3/14

N2 - 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

AB - 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

KW - E Learning

KW - ECG

KW - Pedagogy

KW - Assessment

KW - Healthcare Science

U2 - 10.1016/j.jelectrocard.2016.02.003

DO - 10.1016/j.jelectrocard.2016.02.003

M3 - Article

VL - 49

SP - 454

EP - 461

JO - Journal of Electrocardiology

T2 - Journal of Electrocardiology

JF - Journal of Electrocardiology

SN - 0022-0736

IS - 3

ER -