Predictors of Self-Efficacy Among Secondary Teachers in Multicultural and Multilingual Classrooms Using a Machine Learning Approach

• In Event: Building Bridges & Capacity: Equitable Professional Development for Multilingual Learner Achievement

Abstract

This study investigates predictors of multicultural teaching self-efficacy (MTSE) among U.S. secondary teachers using nationally representative data from the 2018 Teaching and Learning International Survey (TALIS). We employed Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression, a machine learning technique, to analyze how professional preparation, school climate, and teacher demographics influence MTSE. Six key predictors emerged: perceived preparedness in multilingual/multicultural teaching through initial teacher education (ITE), language-specific training, pedagogy-focused professional development (PD), inclusive school practices, and teacher race/ethnicity and gender. Findings underscore the critical role of ITE in multicultural/multilingual education and the distinctive contribution of language-specific training. Pedagogical PD and school-wide inclusive practices also predicted MTSE. These results highlight how the teacher diversity and identity-informed experiences contribute to MTSE.

Authors

• Eunjee Jang, University of Wisconsin - River Falls

• Young Sik Seo, University at Buffalo - SUNY

• Bong Gee Jang, Syracuse University