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Using integrated problem- and lecture-based learning teaching modes for imaging diagnosis education

Overview of attention for article published in BMC Medical Education, August 2018
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Mentioned by

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2 tweeters
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1 Facebook page

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8 Mendeley
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Title
Using integrated problem- and lecture-based learning teaching modes for imaging diagnosis education
Published in
BMC Medical Education, August 2018
DOI 10.1186/s12909-018-1303-2
Pubmed ID
Authors

Jun-Yan Yue, Jie Chen, Wen-Guang Dou, Chang-Hua Liang, Qing-Wu Wu, Yi-Yong Ma, Zhi-Ping Zhu, Mei-Xia Li, Yan-Long Hu

Abstract

There are two parts included in traditional imaging diagnosis teaching: theoretical lessons and experimental lessons. Most of the time, the experimental lesson is a review of the theoretical lesson. The teacher is the centre of the course and students are passive learners. Thus, in this study we included the patient problem of the imaging centre in our imaging diagnosis education. The traditional theoretical lessen was used to discuss prior knowledge, the discussion and analysis of patient problems was arranged under class, and the experimental lesson was used to synthesize and test the newly acquired information. The aim of this study is to determine whether or not integration of problem- and lecture-based learning teaching modes in imaging diagnosis education was associated with a good teaching effect. Forty-six of sixty students (76.7%) like integrated problem- and lecture-based learning teaching mode and 53 of 60 students (88.3%) think that integrated problem- and lecture-based learning teaching mode can make their ability of self-study be improved. Sixty students participated in a prospective study with a two-phase cross-over design. All of the students were divided into 2 groups of 30 each. In the first term, the first group participated in an integration of the problem- and lecture-based learning teaching mode, whereas students in the second group underwent the lecture-based learning teaching mode alone. During the second term, the teaching modes were exchanged between the two groups. A close-exam and survey were used to evaluate the teaching effect, and the data were analysed means of analysis of variance with a two-phase cross-over design and a χ2 test with a 2-tailed α of 0.05. There was a statistically significant difference in the test scores between the integration of the problem- and lecture-based learning teaching mode and the lecture-based learning teaching mode alone (P < 0.05). The integration of problem- and lecture-based learning teaching mode was well-appraised. Integration of the problem- and lecture-based learning teaching modes in teaching imaging diagnosis education resulted in a good teaching effect.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 25%
Lecturer 2 25%
Student > Bachelor 1 13%
Other 1 13%
Researcher 1 13%
Other 1 13%
Readers by discipline Count As %
Medicine and Dentistry 4 50%
Nursing and Health Professions 2 25%
Social Sciences 1 13%
Unspecified 1 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 20 October 2018.
All research outputs
#8,039,121
of 12,818,993 outputs
Outputs from BMC Medical Education
#1,245
of 1,810 outputs
Outputs of similar age
#159,551
of 268,002 outputs
Outputs of similar age from BMC Medical Education
#1
of 1 outputs
Altmetric has tracked 12,818,993 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,810 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one is in the 23rd percentile – i.e., 23% of its peers scored the same or lower than it.
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 268,002 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them