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…

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…

Mathematical giftedness (MG) is an intriguing phenomenon, the nature of which has yet to be sufficiently explored. This study goes a step further in understanding how MG is related to expertise in mathematics (EM) and general giftedness (G). Cognitive testing was conducted among 197 high school students with different levels of G and of EM. Based…

There has been a general decline in the dropout rate and an increase in the high school completion rate over the last three decades. This research investigates causes for the decline in the dropout rate over the periods using decomposition analysis. Traditional cross-section analysis was inadequate to perform this task. Using the two cohort…