Student attrition remains a significant challenge for higher education institutions,particularly during the freshman to sophomore year transition.This study introduces a comprehensive decision-support framework that i...Student attrition remains a significant challenge for higher education institutions,particularly during the freshman to sophomore year transition.This study introduces a comprehensive decision-support framework that integrates stateof-the-art predictive machine learning(ML)techniques,local ML explanation techniques,and Generative AI to enhance individualized intervention programs aimed at reducing freshman student attrition.Utilizing a dataset encompassing 13 years of enrollment data from a sizable US academic institution,we developed predictive models using deep neural networks to identify students at risk of leaving school with an overall accuracy of 86%.SHapley Additive exPlanations(SHAP)was then used to enhance the transparency of the model by providing granular insights into the contribution of various factors to individual students'dropout risks.Notably,we employed Generative AI to translate SHAP scores into comprehensible and actionable intervention recommendations presented via an interactive decision-support dashboard.展开更多
文摘Student attrition remains a significant challenge for higher education institutions,particularly during the freshman to sophomore year transition.This study introduces a comprehensive decision-support framework that integrates stateof-the-art predictive machine learning(ML)techniques,local ML explanation techniques,and Generative AI to enhance individualized intervention programs aimed at reducing freshman student attrition.Utilizing a dataset encompassing 13 years of enrollment data from a sizable US academic institution,we developed predictive models using deep neural networks to identify students at risk of leaving school with an overall accuracy of 86%.SHapley Additive exPlanations(SHAP)was then used to enhance the transparency of the model by providing granular insights into the contribution of various factors to individual students'dropout risks.Notably,we employed Generative AI to translate SHAP scores into comprehensible and actionable intervention recommendations presented via an interactive decision-support dashboard.
