Predicting Success in Intermediate Algebra: The Role of Gender, Race, PERT Scores, Homework Grade, Tutoring Hours, and Self-Efficacy in Math

The purpose of this quantitative, predictive, correlational study was to examine if community college students' success in Intermediate Algebra can be predicted from a linear combination of gender, race, PERT score, online homework grade, hours of tutoring attended during the semester, and Math Skills Self-Efficacy Assessment score. The study employed binomial logistic regression to analyze data from 173 students enrolled in Intermediate Algebra. Results revealed that the model, while statistically non-significant, χ²(13) = 8.648, p = .799, explained 6.5% of the variance in course success and correctly classified 62% of cases. Despite these findings, no predictor variables had a significant effect on student success. This research underscores the complexity of predicting academic success and suggests that factors beyond those examined may influence outcomes in intermediate algebra. Further research is recommended to explore additional variables and refine predictive models. The implications of this study are critical for educators and policymakers seeking to enhance educational strategies and student support services in community colleges.