The investigation of multiple paths to success in college‐level mathematics: A fuzzy qualitative comparative analysis

This paper aims to describe how a fuzzy qualitative comparative analysis can be used to describe which combinations of academic factors are most influential for achieving success in college‐level mathematics. Using a fuzzy qualitative comparative analysis allows for the comparison of all possible combinations for a collection of predictor variables, as well as strategies for determining which configurations of these sets of variables are the most consistent with success in college‐level mathematics. Recent advances in fuzzy qualitative comparative analysis techniques have now integrated traditional qualitative comparative analysis strategies with formal statistical tests, thus allowing for the analysis and comparison of complex relationships that are difficult to describe with more traditional statistical methods such as regression analysis.

Data were collected from 259 full‐time, first‐time freshmen at a large state university in the USA. They were analysed using fuzzy‐set qualitative comparative analysis (FQCA).

Findings from this study suggest that the most parsimonious configuration of college remediation status, spending less time away from mathematics, and doing better in high school mathematics are key to success in college‐level mathematics.

Although numerous studies have made great progress in describing the complex relationship between prior mathematics exposure in high school with success in college‐level mathematics, one limitation of many studies is that they rely on analytic methods that only estimate the net effect of a single predictor variable, or a very small collection of predictor variables. This study utilises fuzzy‐set qualitative comparative analysis (FQCA) which can be used to analyze more complex interrelationships among a collection of predictor variables.