Despite current research efforts in mathematics and science problem solving that emphasize situated and socially mediated approaches to solving authentic, complex problems, story problems remain the most common form of problem solving in K-12 schools and universities. Story problems typically present a quantitative solution problem embedded within a shallow story context. Most often, students use a procedural approach to their solution, directly translating story values into solvable algorithms. Research shows that this direct translation strategy results in a lack of conceptual understanding and the inability to transfer any problem-solving skills that are developed. Because traditional approaches to story problem-solving instruction do not support conceptual understanding of problem structures during their solution, more effective instructional approaches are needed for supporting story problems. This research review shows that solving story problems requires that learners construct a conceptual model of the problem that integrates the situational (story) content with an understanding of the semantic structure of the problem based on the principles of mathematics or science being practiced in the problem. The model also contains the processing operations required to solve the problem quantitatively. Constructing such a conceptual model enables learners to classify story problems before attempting any solution, a step essential to transfer. Based on research findings, I propose a model for designing a technology-enhanced story problem-solving environment. The model includes a set identifier, situational model, structural model builder, and equation builder.

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