Assessing and Modeling Student Academic Practices and Performance in First-Year Mathematics Courses in Higher Education

Abstract

Objectives: This research brief explores literature addressing developmental education to identify successful interventions in first-year math courses in higher education. Our goal is to describe the relationship between students’ academic practices and their final course grade in their first-year math courses. Method: Data on 3,249 students have been gathered and analyzed using descriptive statistics and predicative analytics. We describe the Math program, which includes a supplemental support component, and the environment under which it was created. We then examine the behavior between students’ participation in supplemental support and their academic performance. Results: We used classification and regression tree algorithms to obtain a model that gave us data-driven guidelines to aid with future student interventions and success in their first-year math courses. Conclusions: Students’ fulfillment of the supplemental support requirements by specified deadlines is a key predictor of students’ midterm and final course grades.  Implications for Theory and/or Practice: This work provides a roadmap for student interventions and increasing student success with first-year mathematics courses. Keywords: First-year mathematics courses, supplemental support, higher education