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Education Sciences
Article . 2025 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Preservice Mathematics Teachers’ Mathematical Modeling Competencies: Mathematical Beliefs Perspective

Authors: Gürcan Kaya; Yüksel Dede;

Preservice Mathematics Teachers’ Mathematical Modeling Competencies: Mathematical Beliefs Perspective

Abstract

This study investigated the relationship between preservice elementary mathematics teachers’ beliefs about mathematics and their mathematical modeling competencies. In the study, the belief categories of the preservice teachers were first determined using Q methodology and then classified into traditional and non-traditional belief. A Mathematical Modeling Competencies Rubric was developed in line with the literature and expert opinions. Three independent experts used this rubric to evaluate holistic modeling tasks that the participants completed. The resulting scores were analyzed using the Many-Facet Rasch Model to test for differences in modeling competencies among the belief groups. The findings revealed that preservice mathematics teachers with non-traditional beliefs demonstrated higher modeling competencies than those with traditional beliefs (χ2 = 84.7, df = 3, p < 0.001). In conclusion, the study highlights that preservice mathematics teachers’ beliefs about mathematics play a crucial role in developing modeling competencies and suggests that belief structures should be considered in teacher education programs.

Country
Turkey
Keywords

mathematical modeling competencies, mathematical beliefs, Many-Facet Rasch Model, Q methodology, teacher education

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
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