The early identification of first-year students at risk of dropping out of high-school entry medical school

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Subtitle: The usefulness of teachers’ ratings of class participation
Author list: Araújo, A. M., Leite, C., Costa, P., & Costa, M. J.
Publisher: Springer (part of Springer Nature): Springer Open Choice Hybrid Journals
Publication year: 2018
Journal: Advances in Health Sciences Education (1382-4996)
Start page: 1
End page: 18
Number of pages: 18
ISSN: 1382-4996
eISSN: 1573-1677
Languages: English-Great Britain (EN-GB)


Dropping out from undergraduate medical education is costly for
students, medical schools, and society in general. Therefore, the early
identification of potential dropout students is important. The
contribution of personal features to dropout rates has merited
exploration. However, there is a paucity of research on aspects of
student experience that may lead to dropping out. In this study,
underpinned by theoretical models of student commitment, involvement,
and engagement, we explored the hypothesis of using inferior
participation as an indicator of a higher probability of dropping out in
year 1. Class participation was calculated as an aggregate score based
on teachers' daily observations in class. The study used a longitudinal
dataset of six cohorts of high-school entry students (N = 709, 67%
females) in one medical school with an annual intake of 120 students.
The findings confirmed the initial hypothesis and showed that lower
scores of class participation in year 1 added predictive ability to
pre-entry characteristics (Pseudo-R2 raised from 0.22 to 0.28). Even
though the inclusion of course failure in year 1 resulted in higher
explanatory power than participation in class (Pseudo-R2 raised from
0.28 to 0.63), ratings of class participation may be advantageous to
anticipate dropout identification, as those can be collected prior to
course failure. The implications for practice are that teachers' ratings
of class participation can play a role in indicating medical students
who may eventually drop out. We conclude that the scores of class
participation can contribute to flagging systems for the early detection
of student dropouts.


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Last updated on 2019-13-08 at 00:46