Abstract
Abstract : This paper lays out the rationale and implementation of student modeling and updating in the HYDRIVE intelligent tutoring system (ITS) for aircraft hydraulic systems. An epistemic level of modeling concerns the plans and goals students are using to guide their problem-solving, as inferred from specific actions in specific contexts. These results update a student model constructed around more broadly defined aspects of system understanding, strategic knowledge, and procedural skills. Meant to support inferences that transcend particular problem states, this level of student modeling moderates feedback and instructional decisions in HYDRIVE. The applicability of this approach to student modeling in other learning domains is discussed. Bayesian inference networks, Causal probability networks, Cognitive models, HYDRIVE, Intelligent tutoring systems.
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