Identifying students at risk in academics Analysis of Korean language academic attrition at the Defense Language Institute Foreign Language Center
Haupt, Adam Christian
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Purpose – This paper aims to use a data-driven approach to identify the factors and metrics that provide the best indicators of academic attrition in the Korean language program at the Defense Language Institute Foreign Language Center. Design methodology approach – This research develops logistic regression models to aid in the identification of at-risk students in the Defense Language Institute’s Korean language school. Findings – The results from this research demonstrates that this methodology can detect significant factors and metrics that identify students at-risk. Additionally, this research shows that school policy changes can be detected using logistic regression models and stepwise regression. Originality value – This research represents a real-world application of logistic regression modeling methods applied to the problem of identifying at-risk students for the purpose of academic intervention or other negative outcomes. By using logistic regression, the authors are able to gain a greater understanding of the problem and identify statistically significant predictors of student attrition that they believe can be converted into meaningful policy change.
The article of record as published may be found at http://dx.doi.org/10.1108/JDAL-05-2017-0008
RightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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