Historical student data can help elucidate the factors that promote student success in mathematics courses. Herein we use both multiple regression and principal component analyses to explore ten years of historical data from over 20,000 students in an introductory college-level Algebra course in an urban American research university with a diverse student population in order to understand the relationship between course success and student performance in previous courses, student demographic background, and time spent on coursework. We find that indicators of students' past performance and experience, including grade-point-average and the number of accumulated credit hours, best predict student success in this course. We also find that overall final grades are representative of the entire course and are not unduly weighted by any one topic. Furthermore, the amount of time spent working on assignments led to improved grade outcomes. With these baseline data, our team plans to design targeted interventions that can increase rates of student success in future courses.
Notes for Practice• Past studies have found that student grades are influenced by several factors, including student ability, student demographic background, and course specific factors.• This study finds that student prior performance in past courses is the best predictor of final grade outcome in an introductory mathematics course.• We recommend early interventions to target at-risk students, particularly students with low grade-point averages, students who are part time, and first semester students.• We found that time spent on assignments is associated with higher grades. Therefore, to the extent possible, assignments should be given in an online format that incorporates a timestamp, thereby allowing instructors to identify in real-time students who may need intervention.