Date

12-16-2025

Department

School of Education

Degree

Doctor of Philosophy in Education (PhD)

Chair

Janice Kooken

Keywords

self-efficacy, mathematical modeling, motivation, data cycle, effectance motivation, elementary mathematics, teachers

Disciplines

Education | Mathematics

Abstract

The purpose of this non-experimental quantitative predictive correlational study was to investigate the extent to which efficacy for pedagogy in mathematics, efficacy for teaching mathematics content, effectance motivation in mathematics, years of experience, and access to statistics, data science, or mathematical modeling courses predict attitudes toward constructivist practices in mathematical modeling of Virginia primary school mathematics teachers. The goal of the research was to understand what affective characteristics support effective adoption Virginia's mathematics curriculum change. Higher levels of mathematics teacher self-efficacy have been associated with constructivist instructional practices and higher levels of student achievement. The sample included kindergarten through fifth-grade teachers in a large district in Virginia. Predictor variables were measured via the Self-Efficacy for Teaching Mathematics Instrument, effectance motivation in mathematics via Fennema–Sherman Math Attitudes Scale – Teacher, and two demographic questions on years of experience and appropriate training. The criterion variable was measured with the constructivist subscale of the Mathematical Modeling Attitude Scale. A multiple linear regression was used to analyze the data. The results of the study found that effectance motivation and efficacy for pedagogy in mathematics were significant predictors of attitudes towards constructivist practices in mathematical modeling. Further investigations are recommended to include diverse populations, differing geographic locations, and the implications of attitudes on instructional choices.

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