Randomized trial demonstrates improved understanding of activity coefficients in chemical engineering students, suggesting an effective teaching reform strategy.
Activity and activity coefficients in chemical engineering thermodynamics feature both in-depth microscopic molecular mechanisms and intensive macroscopic engineering calculations, representing a core teaching pain point where students struggle to internalize concepts and tend to solve problems mechanically. Traditional teaching generally introduces activity coefficient models─ideal solution, Margules, Van Laar, Flory–Huggins, Wilson, NRTL, etc.─in chronological order of their development, leading to severely fragmented knowledge points, disconnected physical mechanisms, and a situation where students only apply formulas without understanding engineering model selection. This article breaks away from the outdated teaching paradigm of “listing models by era” and innovatively adopts a new perspective of classification by physical mechanisms. All activity coefficient models are uniformly categorized into four physical types: enthalpy-effect-dominated, entropy-effect-dominated, local composition microscopic enrichment, and energy–volume coupling. An integrated cognitive chain is constructed: “root of molecular forces → two core mechanisms of nonideality → progressive physical classification of models → precise selection for engineering scenarios”. Taking the typical polar–nonpolar ethanol–cyclohexane mixture system as a case throughout the course, the reform is supported by problem-oriented modular teaching, molecular dynamics microscopic visualization demonstrations, and an integrated “prediction–validation–modeling” reform of vapor–liquid equilibrium experiments. This achieves a cognitive leap for students from “memorizing formulas for numerical calculation” to “understanding mechanisms for model selection”. Teaching practice shows that the proportion of students who grasped the physical essence of activity coefficients rose from 12.2% to 88.0% after the reform and that the score rate of students’ ability to select and apply engineering models increased by 38.9%, as verified by standardized pretests and post-tests covering three dimensions, including conceptual understanding, phenomenon interpretation, and engineering application, as well as an independent sample t test. This provides a directly replicable paradigm reference for the advanced teaching reconstruction of core concepts in chemical engineering thermodynamics in universities and is mainly applicable to senior undergraduate students and graduate students majoring in chemical engineering.
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Hu et al. (2026) studied this question.
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