Prediction of senior year medical students who do not pass the graduation exam by logistic analysis using data on gender, experience of repetition, and results of previous exams

Main Article Content

Kazuo Goto

Abstract

Background.
The number of students who must repeat an academic year due to an inability to attain enough credits has been increasing in Japan. It is important for universities to be able to identify these students in advance to ensure that they pass their examinations without need of repetition. In this study, we tried to predict the likelihood of students’ repetition of their senior year using the factors of gender, experience of repetition up to the junior year, and scores on tests conducted four times before their graduation exam in the senior year.
Methods.
Seventy-three students belonging to the senior class of a medical technology college in Tokyo were studied. The students were divided into three groups: Group 1, composed of students who passed the graduation exam on the first attempt (n=35); Group 2, composed of students who failed to pass the graduation exam at the first attempt, but passed the graduation re-exam (n=26); and Group 3, composed of students who did not pass the graduation exam or the re-exam (n=12).
Results.
We found that gender was not a factor of senior-year repetition. Students who had experienced of repetition prior to junior year tended to be six times more likely to fail the graduation exam than those who did not (OR=6.52, 95% CI: 1.17 – 32.44, P=0.03). Low scores on Test 4, administered two months before the graduation exam, were associated with students who fail to pass the graduation exam (OR=15.2, 95% CI: 3.29 – 70.14, P=0.00). The graduation exam score was associated with students who fail to pass the re-exam (OR=55.2, 95% CI: 1.13 – 2679.86, P=0.04).
Conclusion.
This study suggests that we need to support senior-year students based on the results of pre-graduation testing, and we need to increase support for students with repetition experience before junior year.

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Prediction of senior year medical students who do not pass the graduation exam by logistic analysis using data on gender, experience of repetition, and results of previous exams . (2020). Medical Technologies Journal, 4(1), 497-503. https://doi.org/10.26415/2572-004X-vol4iss1p497-503
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Medical technologies

How to Cite

Prediction of senior year medical students who do not pass the graduation exam by logistic analysis using data on gender, experience of repetition, and results of previous exams . (2020). Medical Technologies Journal, 4(1), 497-503. https://doi.org/10.26415/2572-004X-vol4iss1p497-503

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References

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