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Do research findings on schema-based instruction translate to the classroom?

Overview of attention for article published in Tijdschrift voor Medisch Onderwijs, October 2015
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Title
Do research findings on schema-based instruction translate to the classroom?
Published in
Tijdschrift voor Medisch Onderwijs, October 2015
DOI 10.1007/s40037-015-0225-5
Pubmed ID
Authors

Sarah Blissett, Mark Goldszmidt, Matt Sibbald

Abstract

Schema-based instruction has been shown to improve diagnostic performance and reduce cognitive load. However, to date, this has only been studied in controlled research settings. More distractions in classrooms may limit generalizability to real-world settings. We evaluated whether schema-based instruction would maintain its effects on cognitive load optimization and performance in a classroom. Focused on the approach of interpreting cardiac auscultation findings, 101 first-year medical students at Western University were randomized to receive a traditional (n = 48) or a schema-based lecture (n = 53). Students completed four written questions to test diagnostic performance and a cognitive load assessment at the end of the lecture. Diagnostic performance and cognitive load were compared with independent t-tests. Schema-based instruction was associated with increased diagnostic performance on written questions (64 ± 22 % vs 44 ± 25 % p < 0.001) and reduced intrinsic cognitive load (mean difference = 15 %, standard error 3 %, p < 0.001). There was no significant difference in reported extraneous (p = 0.36) or germane (p = 0.42) cognitive load. Our results demonstrate that schema-based instruction can be used to reduce intrinsic load and improve diagnostic performance in a real-world classroom setting. The results would be strengthened by replication across other locations and topics.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 6%
Unknown 29 94%

Demographic breakdown

Readers by professional status Count As %
Lecturer 4 13%
Student > Ph. D. Student 3 10%
Researcher 3 10%
Professor > Associate Professor 3 10%
Student > Master 3 10%
Other 8 26%
Unknown 7 23%
Readers by discipline Count As %
Medicine and Dentistry 10 32%
Social Sciences 4 13%
Nursing and Health Professions 2 6%
Psychology 2 6%
Engineering 2 6%
Other 5 16%
Unknown 6 19%