Academic performance in university courses is influenced by numerous factors, ranging from individual characteristics such as gender, race, and prior academic achievement to external variables such as course sequencing and instructor characteristics. This study focuses on potential factors influencing student success in an advanced agricultural finance course. Although previous research has explored how demographics and other variables influence outcomes in economics and accounting courses, there are no such research on agricultural finance courses.

We used multiple linear regression to analyze factors that significantly influence student performance in an upper-level agricultural finance course. The explanatory variables included gender, age, SAT scores, prerequisite course performance, average grades in math and statistics courses, the number of math-related courses taken, the time gap between completing prerequisite courses. Additionally, we assess how factors like enrollment in specific semesters, instructor assignments, and living proximity to campus might contribute to academic success. The transfer status of students, with particular focus on transfers from different colleges, is another important variable under consideration. By examining these factors collectively, this study aims to identify the key predictors of success in the course and provide actionable insights for improving student outcomes.

The findings suggest that a combination of the students' SAT scores, transferring institution, grades in prerequisite courses, the semester that they took the course, the primary instructors, number of previous math-related courses taken, and their final course grades in math and statistics courses significantly contribute to students' performance. The results also indicated that gender and age were not significantly correlated with student performance. These results have implications for advising and curriculum design, particularly in relation to enhancing student success through tailored academic support and course sequencing.