Abstract

<p style="text-align:justify">Several concerted movements toward mathematical modeling have been seen in the last decade, reflecting the growing global relationship between the role of mathematics in the context of modern science, technology and real life. The literature has mainly covered the theoretical basis of research questions in mathematical modeling and the use of effective research methods in the studies. Driven by the Realistic Mathematics Education (RME) theory and empirical evidence on metacognition and modeling competency, this research aimed at exploring the interrelationships between metacognition and mathematical modeling and academic year level as a moderator via the SEM approach. This study involved 538 students as participants. From this sample, 133 students (24.7%) were from the first academic year, 223 (41.4%) were from the second and 182 (33.8%) were from the third. A correlational research design was employed to answer the research question. Cluster random sampling was used to gather the sample. We employed structural equation modeling (SEM) to test the hypothesized moderation employing IBM SPSS Amos version 18. Our findings confirmed the direct correlation between metacognition and mathematical modeling was statistically significant. Academic year level as a partial moderator significantly moderates the interrelationships between the metacognitive strategies and mathematical modeling competency. The effect of metacognition on mathematical modeling competency was more pronounced in the year two group compared to the year one and three groups.</p>

Highlights

  • The last decade has witnessed several concerted movements toward mathematical modeling competency given the increasing worldwide relation of the role of mathematics in modern science, technology and real-life context

  • The path analysis outputs revealed that the recommended regression model was suitable, and metacognition was a significant predictor of the mathematical modeling competency (β = 0.462, p < 0.001)

  • Several concerted movements toward mathematical modeling have been witnessed in the last decade, reflecting the growing global relationship between the role of mathematics in the context of modern science, technology and real life

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Summary

Introduction

The last decade has witnessed several concerted movements toward mathematical modeling competency given the increasing worldwide relation of the role of mathematics in modern science, technology and real-life context. Modeling competencies engage the movement of knowledge and skills between contexts and is viewed as a basic feature of science, technology, engineering and mathematics (STEM) education (Hallström & Schönborn, 2019). In the mathematical modeling classroom, students need to simplify a given real-world situation, explain, analyze, justify, identify, compare, reject, validate or revise mathematical solutions (Blomhoej & Jensen, 2003; Blum et al, 2007; English, 2003; Kaiser & Schwarz, 2006; Maaß, 2006). Students perceived frustration in the first step of the modeling process, which was to make simplifying assumptions concerning the real-life task

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