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Motivation and emotion predict medical students’ attention to computer-based feedback

Overview of attention for article published in Advances in Health Sciences Education, December 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

Mentioned by

twitter
14 tweeters
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
28 Mendeley
Title
Motivation and emotion predict medical students’ attention to computer-based feedback
Published in
Advances in Health Sciences Education, December 2017
DOI 10.1007/s10459-017-9806-x
Pubmed ID
Authors

Laura M. Naismith, Susanne P. Lajoie

Abstract

Students cannot learn from feedback unless they pay attention to it. This study investigated relationships between the personal factors of achievement goal orientations, achievement emotions, and attention to feedback in BioWorld, a computer environment for learning clinical reasoning. Novice medical students (N = 28) completed questionnaires to measure their achievement goal orientations and then thought aloud while solving three endocrinology patient cases and reviewing corresponding expert solutions. Questionnaires administered after each case measured participants' experiences of five feedback emotions: pride, relief, joy, shame, and anger. Attention to individual text segments of the expert solutions was modelled using logistic regression and the method of generalized estimating equations. Participants did not attend to all of the feedback that was available to them. Performance-avoidance goals and shame positively predicted attention to feedback, and performance-approach goals and relief negatively predicted attention to feedback. Aspects of how the feedback was displayed also influenced participants' attention. Findings are discussed in terms of their implications for educational theory as well as the design and use of computer learning environments in medical education.

Twitter Demographics

The data shown below were collected from the profiles of 14 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 7 25%
Researcher 6 21%
Student > Ph. D. Student 6 21%
Student > Master 5 18%
Student > Postgraduate 1 4%
Other 3 11%
Readers by discipline Count As %
Unspecified 9 32%
Psychology 9 32%
Medicine and Dentistry 3 11%
Social Sciences 2 7%
Computer Science 2 7%
Other 3 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 03 August 2018.
All research outputs
#1,813,328
of 13,325,587 outputs
Outputs from Advances in Health Sciences Education
#76
of 608 outputs
Outputs of similar age
#70,034
of 384,368 outputs
Outputs of similar age from Advances in Health Sciences Education
#4
of 14 outputs
Altmetric has tracked 13,325,587 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 608 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 87% 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 384,368 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 14 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 71% of its contemporaries.