Measuring Teacher Agency: A Quantitative Investigation of the Ecological Model

• In Event: Extending the General Linear Model: From Classical Regression to Bayesian Estimation and Machine Learning

Abstract

The purpose of this study was to quantitatively examine the ecological model of teacher agency; a framework historically grounded in qualitative research. Using survey data from 314 secondary mathematics teachers across the United States, a multiple linear regression analysis was performed to analyze how 29 predictor variables rooted within the ecological model could predict teachers’ perceived sense of agency. The final model identified nine significant predictors and explained over 40% of the variance in agency, offering strong empirical support for the model’s multidimensional structure. This study demonstrates the viability of regression-based approaches for exploring complex, context-dependent constructs like teacher agency and provides a methodological foundation for future research that seeks to utilize quantitative methodologies to better understand teacher agency.

Author

• Christopher Carter, University of Kansas