| Title |
ECG rhythm analysis with expert and learner-generated schemas in novice learners
|
|---|---|
| Published in |
Advances in Health Sciences Education, December 2014
|
| DOI | 10.1007/s10459-014-9572-y |
| Pubmed ID | |
| Authors |
Sarah Blissett, Rodrigo Cavalcanti, Matthew Sibbald |
| Abstract |
Although instruction using expert-generated schemas is associated with higher diagnostic performance, implementation is resource intensive. Learner-generated schemas are an alternative, but may be limited by increases in cognitive load. We compared expert- and learner-generated schemas for learning ECG rhythm interpretation on diagnostic accuracy, cognitive load and knowledge acquisition. Fifty-seven medical students were randomized to two experiments. Experiment 1 (n = 29) compared use of traditional teaching frameworks to expert generated schemas. Participants randomly received either a traditional framework or an expert-generated schema to practice each of two content areas in a crossed design. Learning accuracy and cognitive load were measured during the training phase. Discriminating knowledge and diagnostic accuracy were tested immediately after the training phase and 1-2 weeks after. Using the same methodology, experiment 2 (n = 28) compared use of learner-generated versus expert-generated schemas. In experiment 1, learning from expert-generated schemas was associated with lower cognitive load (13 vs 16, p < 0.001), higher diagnostic accuracy on immediate testing (40 vs 29 %, p = 0.018), and higher discriminating knowledge (81 vs 71 %, p < 0.001). Both groups performed similarly on delayed testing (14 vs 8 %, p = 0.6). In experiment 2, use of learner-generated schemas reduced diagnostic accuracy during the training phase (55 vs 77 %, p < 0.001), with similar performance on the immediate (30 vs 33 %, p = 0.89) and delayed (7 vs 5 %, p = 0.79) testing phases.. Learner-generated schema generation was associated with increased cognitive load (17.1 vs 13.5, p < 0.001). When compared to traditional frameworks, use of an expert-generated schema improved learning of ECG rhythm interpretation. Participants generating their own schemas perform similarly to those using expert-generated schemas despite reporting higher cognitive load. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 20% |
| United Kingdom | 1 | 20% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 40% |
| Practitioners (doctors, other healthcare professionals) | 2 | 40% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Israel | 1 | 2% |
| United States | 1 | 2% |
| Unknown | 58 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 17% |
| Student > Bachelor | 7 | 12% |
| Student > Master | 6 | 10% |
| Student > Postgraduate | 5 | 8% |
| Professor | 4 | 7% |
| Other | 17 | 28% |
| Unknown | 11 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 23 | 38% |
| Psychology | 7 | 12% |
| Nursing and Health Professions | 3 | 5% |
| Social Sciences | 3 | 5% |
| Business, Management and Accounting | 2 | 3% |
| Other | 6 | 10% |
| Unknown | 16 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 January 2016.
All research outputs
#7,138,125
of 22,774,233 outputs
Outputs from Advances in Health Sciences Education
#383
of 851 outputs
Outputs of similar age
#101,395
of 360,226 outputs
Outputs of similar age from Advances in Health Sciences Education
#4
of 18 outputs
Altmetric has tracked 22,774,233 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 851 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one has gotten more attention than average, scoring higher than 53% of its peers.
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We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.