Mathematical Literacy and Financial Decision-Making among Undergraduate Students in Nigeria: Evidence from Selected Universities

Authors

https://doi.org/10.22105/masi.v3i2.106

Abstract

This study empirically investigates the relationship between Mathematical Literacy (ML) and Financial Decision-Making (FDM) among undergraduate students in Nigerian universities. While existing literature heavily isolates conceptual Financial Literacy (FL) as a primary driver of financial well-being, this study addresses an empirical gap by analyzing the quantitative cognitive assets required to apply that knowledge effectively. Utilizing an ex-post quantitative research design, structured questionnaires were administered to a stratified, multi-stage random sample of 500 undergraduate students across selected public and private universities in Nigeria, yielding 472 fully valid responses. Data were analyzed using Ordinary Least Squares (OLS) multiple linear regression analysis. The empirical results reveal that ML has a highly significant positive impact on FDM (β1 = 0.284, p < 0.001), exerting a stronger predictive influence than general FL (β2 = 0.195, p < 0.001). Among the socio-demographic control variables, higher disposable income, male gender, and advanced level of study also statistically improve financial choices, whereas chronological age exhibits a negligible effect. These findings indicate that abstract financial concepts are insufficient without foundational numeracy skills to navigate non-linear financial instruments. It is recommended that the National Universities Commission (NUC) integrate applied ML into the compulsory General Studies (GST) curriculum across Nigerian universities.      

Keywords:

Financial Decision-Making, Higher Education, Human Capital Theory, Mathematical Literacy, Undergraduate Students.

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Published

2026-06-07

How to Cite

Awwalu, H. B. ., & Yusuf, J. A. (2026). Mathematical Literacy and Financial Decision-Making among Undergraduate Students in Nigeria: Evidence from Selected Universities. Management Analytics and Social Insights, 3(2). https://doi.org/10.22105/masi.v3i2.106

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