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Resumo
Resumo: As regras de produção constituem o modelo computacional mais comumente empregado no desenvolvimento do módulo de tomada de decisão em Sistemas Tutores Inteligentes. Este artigo apresenta um mecanismo de inferência alternativo ao propor um agente pedagógico bayesiano para selecionar as táticas de ensino. A rede bayesiana implementada no módulo de tomada de decisão do agente pedagógico utiliza como evidências, características extraídas a partir da interação do aluno com o STI. A fim de exemplificar e validar o mecanismo de inferência proposto, um STI foi implementado.
Abstract: The production rules constitute the major computational model used for the development of the module of taking of decision in Intelligent Tutorial Systems. This article presents an alternative mechanism of inference: a bayesian pedagogical agent to select the learning tactics. The implemented bayesian net in the module of taking of decision of the pedagogical agent uses as evidences, characteristics extracted from the interaction of the student with the STI. In order to show and to validate the inference mechanism considered, a STI was implemented.
Abstract: The production rules constitute the major computational model used for the development of the module of taking of decision in Intelligent Tutorial Systems. This article presents an alternative mechanism of inference: a bayesian pedagogical agent to select the learning tactics. The implemented bayesian net in the module of taking of decision of the pedagogical agent uses as evidences, characteristics extracted from the interaction of the student with the STI. In order to show and to validate the inference mechanism considered, a STI was implemented.
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PDFDOI: https://doi.org/10.5753/cbie.sbie.2005.42-51