Abstract
When constructing a system that presents students with problem-solving, the essential problem to be considered is the definition of the system's conceptual model of the problem-solving expertise. We study two possible approaches of the definition of this model: refining generic problem-solving models and modelling by data-abstraction from an observed expertise. We emphasise that these two approaches have opposite advantages. The former facilitates the definition of rational systematic problem-solving models, the latter facilitates the respect of the problem-solving pedagogic specificities of a particular domain. In order to help in the refinement of the model constructed by either method we claim that a paper-based model is not sufficient and advocate the use of prototyping as a means to support modelling. To allow this prototyping we need a high-level language that (1) allows a quick operationalisation of the model while not enforcing predefined conceptual primitives, and (2) allows a control of what problem-solving material is used according to both problem-solving and pedagogical issues, these two aspects not being mixed. We present an example of such a language, the Zola language, and how it tackles these objectives, with examples from a system (under construction) that aims at training students to linear programming techniques.
Published Version
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