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Example-based learning: comparing the effects of additionally providing three different integrative learning activities on physiotherapy intervention knowledge

Overview of attention for article published in BMC Medical Education, March 2015
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  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

Mentioned by

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6 X users

Citations

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21 Dimensions

Readers on

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135 Mendeley
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Title
Example-based learning: comparing the effects of additionally providing three different integrative learning activities on physiotherapy intervention knowledge
Published in
BMC Medical Education, March 2015
DOI 10.1186/s12909-015-0308-3
Pubmed ID
Authors

Joseph-Omer Dyer, Anne Hudon, Katherine Montpetit-Tourangeau, Bernard Charlin, Sílvia Mamede, Tamara van Gog

Abstract

Example-based learning using worked examples can foster clinical reasoning. Worked examples are instructional tools that learners can use to study the steps needed to solve a problem. Studying worked examples paired with completion examples promotes acquisition of problem-solving skills more than studying worked examples alone. Completion examples are worked examples in which some of the solution steps remain unsolved for learners to complete. Providing learners engaged in example-based learning with self-explanation prompts has been shown to foster increased meaningful learning compared to providing no self-explanation prompts. Concept mapping and concept map study are other instructional activities known to promote meaningful learning. This study compares the effects of self-explaining, completing a concept map and studying a concept map on conceptual knowledge and problem-solving skills among novice learners engaged in example-based learning. Ninety-one physiotherapy students were randomized into three conditions. They performed a pre-test and a post-test to evaluate their gains in conceptual knowledge and problem-solving skills (transfer performance) in intervention selection. They studied three pairs of worked/completion examples in a digital learning environment. Worked examples consisted of a written reasoning process for selecting an optimal physiotherapy intervention for a patient. The completion examples were partially worked out, with the last few problem-solving steps left blank for students to complete. The students then had to engage in additional self-explanation, concept map completion or model concept map study in order to synthesize and deepen their knowledge of the key concepts and problem-solving steps. Pre-test performance did not differ among conditions. Post-test conceptual knowledge was higher (P < .001) in the concept map study condition (68.8 ± 21.8%) compared to the concept map completion (52.8 ± 17.0%) and self-explanation (52.2 ± 21.7%) conditions. Post-test problem-solving performance was higher (P < .05) in the self-explanation (63.2 ± 16.0%) condition compared to the concept map study (53.3 ± 16.4%) and concept map completion (51.0 ± 13.6%) conditions. Students in the self-explanation condition also invested less mental effort in the post-test. Studying model concept maps led to greater conceptual knowledge, whereas self-explanation led to higher transfer performance. Self-explanation and concept map study can be combined with worked example and completion example strategies to foster intervention selection.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 135 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Bolivia, Plurinational State of 1 <1%
Germany 1 <1%
Belgium 1 <1%
Unknown 132 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 23 17%
Student > Ph. D. Student 15 11%
Researcher 12 9%
Lecturer 11 8%
Student > Bachelor 8 6%
Other 36 27%
Unknown 30 22%
Readers by discipline Count As %
Nursing and Health Professions 29 21%
Medicine and Dentistry 29 21%
Social Sciences 12 9%
Psychology 10 7%
Agricultural and Biological Sciences 3 2%
Other 17 13%
Unknown 35 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 24 May 2015.
All research outputs
#7,296,017
of 25,462,162 outputs
Outputs from BMC Medical Education
#1,297
of 4,002 outputs
Outputs of similar age
#78,770
of 274,176 outputs
Outputs of similar age from BMC Medical Education
#22
of 65 outputs
Altmetric has tracked 25,462,162 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 4,002 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has gotten more attention than average, scoring higher than 67% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 274,176 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 65 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.