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Related Concept Videos

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Updated: Mar 7, 2026

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques
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e-Learning in Advanced Life Support-What factors influence assessment outcome?

C J Thorne1, A S Lockey2, P K Kimani3

  • 1Department of Critical Care Medicine, Heart of England NHS Foundation Trust, Birmingham B9 5SS, UK; Resuscitation Council (UK), Tavistock House North, Tavistock Square, London WC1H 9HR, UK.

Resuscitation
|March 1, 2017
PubMed
Summary
This summary is machine-generated.

Previous Advanced Life Support (ALS) training and experience on resuscitation teams predict better outcomes in the ALS course. Time spent on e-learning did not impact overall results, supporting a blended learning approach.

Keywords:
ALSAdvanced Life SupportAssessmentEducatione-Learning

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Area of Science:

  • Medical Education
  • Resuscitation Science

Background:

  • The Advanced Life Support (ALS) course is crucial for healthcare professionals.
  • Optimizing learning and assessment outcomes in ALS courses is essential for effective resuscitation.
  • A blended learning approach, incorporating e-learning and face-to-face instruction, is increasingly utilized.

Purpose of the Study:

  • To identify factors associated with successful outcomes in the Advanced Life Support (ALS) course.
  • To evaluate the effectiveness of e-learning components in the ALS course.
  • To maximize the learning effect and assessment results for participants.

Main Methods:

  • Analysis of data from 8218 participants in a Resuscitation Council (UK) e-learning ALS (e-ALS) course (2013-2014).
  • Participants completed online e-learning followed by a one-day face-to-face course.
  • Assessment included pre- and post-course multiple-choice questionnaires (MCQ) and a cardiac arrest simulation test (CAS-Test).

Main Results:

  • Mean post-course MCQ score was 87.7%.
  • First attempt pass rate for the CAS-Test was 84.6%, with an overall pass rate of 96.6%.
  • Previous ALS/ILS experience and core resuscitation team membership predicted better performance; increased e-learning time did not significantly affect outcomes.

Conclusions:

  • Clinical experience and prior resuscitation training are key predictors of ALS course success.
  • The time spent on e-learning modules did not correlate with improved assessment outcomes.
  • The blended e-ALS approach allows for personalized learning, accommodating individual needs and prior experience.