ten year study of predictors of student success on the Advanced Placement Computer Science examination

This study examined a model to predict success on the Advanced Placement Computer Science (APCS) examination. The sample included all students (N = 423) who participated in the APCS program in the Palm Beach County Public School System from 1985 to 1994. Predictor variables consisted of the number of courses taken in specific content areas at the secondary level, semester grades in the APCS course, grade point average, and gender. Multiple regression analysis indicated the significance of these variables in predicting the score on the APCS examination (F (12,280) = 5.848, p $<$.001). Further discriminant analysis identified the most accurate subset of predictors. All students were divided into two groups based on their scores on the APCS examination (pass/fail). The variables that occurred most frequently in the best subsets included the number of semesters taken in advanced mathematics; overall high school grade point average; gender; the grades achieved in both first and second semester in Advanced Placement Computer Science; and the semesters in computers. A model based on these six predictors had the highest (p $<$.01) predictive accuracy of all models studied (67.6% hit rate). Additional study of other independent variables that contribute to success on the APCS examination is needed.