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Title: The Use of Receiver Operating Characteristic (ROC) Curve Analysis for the Prediction of Educational Outcomes: Lessons Learned from the National Longitudinal Survey of Youth (NLSY)
Resulting in 1 citation.
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Uekawa, Kazuaki |
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The Use of Receiver Operating Characteristic (ROC) Curve Analysis for the Prediction of Educational Outcomes: Lessons Learned from the National Longitudinal Survey of Youth (NLSY) Presented: Washington DC, American Evaluation Association Annual Conference, October 2013 Cohort(s): NLSY97 Publisher: American Evaluation Association Keyword(s): Dropouts; Educational Outcomes; Modeling Permission to reprint the abstract has not been received from the publisher. Receiver Operating Characteristic (ROC) Curve Analysis can be applied to the prediction of educational outcomes that are dichotomous in nature. Such outcomes include grade retention, dropout, college enrollment, or college graduation. The ROC Curve Analysis is used often in medical science where, given the values of a continuous variable (e.g., blood pressure, hormone level), prediction is made for the dichotomous outcome (e.g., diabetes, pregnancy). Based on a pair of diagnostic statistics, sensitivity and specificity, the analysis helps derive a cut point for the predictor variables such that the prediction result will be optimized. Using publicly available educational databases as examples (e.g., NLSY97, NELS88), the authors will show how the analysis can be implemented in educational systems. For example, this method can be used to predict dropouts for an early warning system, or help superintendents predict retention rates. We will conclude the presentation by discussing this method's strengths and weaknesses as a tool for educational intervention. |
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Bibliography Citation
Uekawa, Kazuaki. "The Use of Receiver Operating Characteristic (ROC) Curve Analysis for the Prediction of Educational Outcomes: Lessons Learned from the National Longitudinal Survey of Youth (NLSY)." Presented: Washington DC, American Evaluation Association Annual Conference, October 2013. |