Research Output
The evaluation of an open source online training system for teaching 12 lead electrocardiographic interpretation
  Introduction
The 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.

Methods
Participants 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.

Results
A 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.

Conclusions
CrowdLabel is shown to be a readily accessible dedicated learning platform to support ECG interpretation competency.

  • Type:

    Article

  • Date:

    11 February 2016

  • Publication Status:

    Published

  • Publisher

    Elsevier BV

  • DOI:

    10.1016/j.jelectrocard.2016.02.003

  • Cross Ref:

    10.1016/j.jelectrocard.2016.02.003

  • ISSN:

    0022-0736

  • Funders:

    Historic Funder (pre-Worktribe)

Citation

Breen, C., Zhu, T., Bond, R., Finlay, D., & Clifford, G. (2016). The evaluation of an open source online training system for teaching 12 lead electrocardiographic interpretation. Journal of Electrocardiology, 49(3), 454-461. https://doi.org/10.1016/j.jelectrocard.2016.02.003

Authors

Keywords

E Learning, ECG, Pedagogy, Assessment, Healthcare Science

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