The Early Identification of At-Risk Students in an Undergraduate Marketing Metrics Course
This research describes the development of a diagnostic tool to permit the early identification of at-risk students in an undergraduate marketing metrics course. Using multiple discriminant analysis, students were classified into performance categories by drawing on a set of predictor variables conceptually linked to student performance in math-based courses. The discriminant model included math ability, perceived self-efficacy, math anxiety and overconfidence as potential discriminators of student performance. The model successfully identifies at-risk students at three times the chance probability. The early identification of at-risk students is a critical first step in the process to improve student performance.
Pilling, Bruce K. and Nasser, David L.
"The Early Identification of At-Risk Students in an Undergraduate Marketing Metrics Course,"
Atlantic Marketing Journal: Vol. 4:
1, Article 6.
Available at: https://digitalcommons.kennesaw.edu/amj/vol4/iss1/6