Understanding Teachers’ Endorsement of Deficit Discourses in Mathematics Through Latent Class Analysis

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Abstract

In this study, we used a survey instrument to understand patterns in teachers’ attribution beliefs and to make inferences about the types of deficit and anti-deficit discourses engaged by elementary teachers. We were also interested in determining whether explicitly naming racial or gender groups influenced teachers’ endorsement of various attributions. Using Latent Class Analysis (LCA), we fit a series of models and selected a four-class solution. The results suggested that teachers exhibited different patterns of attribution beliefs that varied with respect to students’ race and gender. Furthermore, the clustering within this variation revealed by the LCA method was a substantial advance in understanding teachers’ equity beliefs. The study’s implications and limitations are discussed in full paper.

Authors

• Dubravka Svetina Valdivia, Indiana University

• Erik D. Jacobson, Indiana University