Quantitative rigor through critical consciousness: bridging methods in education research

Abstract

This article explores how critical theory informs quantitative methods to tackle systemic inequities in education. We critique traditional quantitative training that prioritizes procedural rigor without examining assumptions and advocate for intersectional regression models, specifically Multilevel Analysis of Individual Heterogeneity and Discriminant Analysis (MAIHDA) and Bayesian approaches. We also address challenges like missing data and model uncertainty through strategies like multiple imputation and compatibility intervals, enhancing methodological robustness, and ethical integrity. We introduce the concept of educational debts to shift the focus from individual deficits to systemic responsibilities, highlighting the practical and theoretical benefits of these approaches. Ultimately, this article guides researchers in using quantitative tools that acknowledge identity and power dynamics, aiming to foster more equitable scientific inquiry.