The ABCs of Keeping On Track to Graduation: Research Findings from Baltimore

This study of graduation outcomes in Baltimore uses multivariate analysis of longitudinal student cohort data to examine the impact of factors identified in previous research as early warning indicators of a dropout outcome. Student cohort files were constructed from longitudinal administrative data (following all first-time 2004–2005 and 2005–2006 9th graders forward in time until their on-time graduation year and 1 year past). Sequentially estimated logistic regression hierarchical linear modeling models indicated the strongest predictors of graduation were 9th-grade attendance and course failure, although gender was still significant. Multinomial logistic regression models were used to analyze the relationship between the 4 categories of college enrollment outcomes (enrollment in a 4-year college, enrollment in a 2-year college, graduation with no college enrollment, and nongraduation) and student-level predictor variables, including grade point average (GPA) and 8th-grade test scores. Results suggest that equipping schools to implement interventions to address chronic absenteeism and course failure in 9th grade is a crucial strategy for increasing both high school graduation and college enrollment.