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Related Concept Videos

Steps in the Modeling Process01:14

Steps in the Modeling Process

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Albert Bandura's theory of observational learning identifies four critical processes: attention, retention, motor reproduction, and reinforcement or motivation.
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Measuring learning gain: Comparing anatomy drawing screencasts and paper-based resources.

James D Pickering1

  • 1Division of Anatomy, Leeds Institute of Medical Education, School of Medicine, University of Leeds, Leeds, United Kingdom.

Anatomical Sciences Education
|December 7, 2016
PubMed
Summary
This summary is machine-generated.

Anatomy drawing screencasts significantly improved medical students' learning gain compared to traditional textbooks. This technology-enhanced learning approach offers a more effective educational resource for anatomy.

Keywords:
cognitive loadcomputer-based learninggross anatomy educationlearning gainmultimediatechnology-enhanced learning

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Area of Science:

  • Medical Education
  • Anatomical Sciences
  • Educational Technology

Background:

  • Technology-enhanced learning (TEL) is prevalent in healthcare education.
  • Empirical evidence quantifying learning gain from TEL resources is limited.
  • This study compares learning gain from anatomy drawing screencasts versus traditional textbooks.

Observation:

  • Year 2 medical students were randomly assigned to screencast or textbook groups.
  • A pre-test/post-test protocol measured learning gain at immediate, 1-week, and 4-week intervals.
  • Learning gain was calculated using statistical analyses.

Findings:

  • The screencast group demonstrated a significant increase in learning gain at all test points.
  • Large effect sizes were observed for the screencast group compared to the textbook group.
  • Differences in learning gain may be attributed to instructional design variations.

Implications:

  • Anatomy drawing screencasts are effective TEL resources for anatomical education.
  • Findings support the cognitive theory of multimedia learning for effective and efficient learning.
  • This research contributes to evidence-based design of digital learning tools in medicine.