Mathematical Modeling in Mathematics Education: A Bibliometric-Systematic Literature Review Highlighting Current Research Trends and Future Research Directions

Iqbal Kharisudin; Amanda Fifi Yaya Mahe

Authors

Iqbal Kharisudin Universitas Negeri Semarang
Amanda Fifi Yaya Mahe Universitas Negeri Semarang

Keywords:

Mathematical Modeling, Mathematics Education, Bibliometric-Systematic Literature Review, Problem Solving, Research Trends

Abstract

Mathematical modeling is a crucial skill in mathematics education that bridges conceptual knowledge and real-world problem-solving. This study aims to evaluate the global research landscape of mathematical modeling in mathematics education to delineate current empirical trends and future research directions. By analyzing 179 Scopus-indexed documents published between 2020 and 2026 through a Bibliometric–Systematic Literature Review (B-SLR) framework., this study reveals a significant upward trend in scientific production, peaking in 2025 with 47 documents (26.26%). Germany emerges as the most productive country (39 publications), with ZDM–Mathematics Education identified as the leading publication source. Keyword co-occurrence analysis highlights an evolutionary shift from fundamental modeling competencies toward broader interdisciplinary themes, including technology integration, sustainability, and computational thinking. Furthermore, the systematic review shows that pre-service teachers are the most frequently studied participants (32%), reflecting an upstream approach to teacher pedagogical readiness. Methodologically, current research is heavily dominated by qualitative approaches (51%) and descriptive study designs (37%), focusing on the holistic, nuanced dimensions of modeling goals. Future research directions suggest expanding empirical investigations into underrepresented cohorts such as primary and upper secondary students and exploring emerging AI-related learning contexts through experimental and longitudinal methodologies.

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