ITS in Ill-Defined Domains: Toward Hybrid Approaches

摘要

Classical approaches for supporting tutoring services face several limitations for ill-defined domains. To overcome these limitations, we argue for the utilization of hybrid approaches for supporting tutoring services. In this paper, we describe a hybrid model that combines an expert system, the model-tracing paradigm, and a data mining approach in an ITS for learning to operate a robotic arm. The result is tutoring services that exceed what was possible to offer with each individual approach for this domain.