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Abstract
Chemistry students frequently struggle to use abstract mathematics to reason about chemical phenomena, even when their procedural mathematical skills are adequate. This paper proposes and conceptually examines an Inductive Contextual Modelling (ICM) algorithm for teaching mathematics to chemistry students. The algorithm integrates three well-established research traditions: inductive teaching as systematised by Prince and Felder, the emergent-modelling design heuristic of Realistic Mathematics Education developed by Gravemeijer, and the mathematical modelling cycle of Blum and Leiß. ICM is defined as a seven-step instructional sequence that begins with a chemical phenomenon, guides students through informal (“model-of”) representations toward formal (“model-for”) mathematical structures, and returns to chemical interpretation through validation. The paper articulates the theoretical foundations of ICM, formalises its seven steps, illustrates them on a chemical-kinetics example (the steady-state approximation), and discusses the algorithm’s coherence with existing empirical evidence on calculus-in-chemistry instruction and mathematical-modelling competence. Testable hypotheses for subsequent quasi-experimental research are outlined.
References
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