Mathematical modeling of local problems: impact on reasoning and transfer
DOI:
https://doi.org/10.64747/63djye85Keywords:
mathematical modeling, reasoning, transfer of learning, open data, basic educationAbstract
This study examines the effect of a local-problem, model-eliciting instructional sequence on mathematical reasoning and transfer among lower-secondary students in Guayaquil, Ecuador. We employed a quasi-experimental cluster design with MEAs and control groups, pretest–posttest measures, and follow-up. The intervention combined context-rich tasks using open data, metacognitive scaffolding with modeling logs, and formative assessment using analytic rubrics. Primary outcomes were (a) latent scores on a Mathematical Reasoning Test (PRM) calibrated through IRT, and (b) a transfer index (success on near and far transfer tasks). The final sample comprised n = 889 students across 30 classes. A multilevel ANCOVA (controlling for pretest and covariates) indicated a significant intervention effect on reasoning (β = 0.24, SE = 0.05, p < .001; d ≈ 0.38). Multilevel logistic models for transfer showed absolute increases of +10.7 percentage points (near; OR = 1.63, 95% CI [1.32, 2.02]) and +12.3 points (far; OR = 1.88, 95% CI [1.45, 2.44]). At follow-up, effects persisted with attenuation (β = 0.18; +9.6 points for far transfer). We observed improvements in argument quality and multiple representations, with an average implementation fidelity of 0.83. Findings indicate that territory-anchored mathematical modeling strengthens reasoning and enables transfer to novel contexts, with scaling feasibility across public and subsidized schools. We recommend institutionalizing MEAs as signature tasks in units on proportional reasoning, functions, and data analysis; adopting rubrics and formative feedback; and sustaining spaced practice to consolidate gains. Methodological transparency (IRT, HLM, DiD) and open data foster replicability and policy uptake.
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Copyright (c) 2025 Celso Cristóbal Aguirre Quinde, Ana María Pozo Mejía, Carmen Amanda Robayo Gonzalez, Daniel Fernando Rodríguez Vallejo (Autor/a)
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