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Planificación instruccional usando CBR en Ambientes inteligentes Distribuidos de Aprendizaje

01/2006;

ABSTRACT RESUMEN En este artículo se presenta un mecanismo de planificación instruccional (IP) utilizando la técnica de aprendizaje automático de la inteligencia artificial (AI) denominada razonamiento basado en casos (CBR). El mecanismo fue implementado en el Ambiente Multi-Agente de Enseñanza/Aprendizaje ALLEGRO, el cual fundamente su paradigma instruccional en tres modelos pedagógicos: conductismo, cognitivismo (cognición distribuida y aprendizaje basado en problemas) y la teoría histórico-social. La validación fue realizada a través de diversos casos de estudio en el dominio de gráfica digital para cursos de postgrado en arquitectura.

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    ABSTRACT: In this paper we consider the role case-based reasoning has had in development of computer-aided instruction systems. We survey several case-based teaching systems, each of which is representative of a basic pedagogical principle that motivated its development. Firstly, 15 pedagogical principles are presented that were identified from the analysis of case-based teaching systems. We present some background to the principles, and indicate which systems they are incorporated in. Next, the teaching systems themselves are described, with emphasis on how case-based reasoning has been applied. Finally, we discuss some problems to be addressed when case-based planning is applied to lesson planning within a tutoring system.
    The Knowledge Engineering Review 08/1995; 10(03):235 - 268. · 0.59 Impact Factor

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