There is less attention on examining algorithmic fairness in secondary education dropout predictions. Also, the inclusion of protected attributes in machine learning models remains a subject of debate. This study delves into the use of machine learning models for predicting high school dropouts, focusing on the role of protected attributes like…

This study examined the relationship between individual and institutional characteristics for student veterans who borrow money while enrolled in degree-seeking programs. Using data from the National Postsecondary Student Aid Study (NPSAS 16), we established predictors of borrowing, implications of borrowing, and examined patterns in total aid…

Dual enrollment (DE)--where students earn college credits during high school--is expanding rapidly. To facilitate DE, institutional actors across K-12 schools and colleges must build or repurpose structures across separate organizations to determine course offerings, assignments, modality, and composition. Yet the organization and implications of…