CUSTOMIZING THE INSTRUCTIONAL GRID

The Web contains hundreds of thousands of educational resources available any time and any place. However no smart technology is available to help teachers and students locate appropriate resources customized to their needs and social characteristics. When educational resources are indexed, it is often done by demographics, such as student age and grade. This article describes customized Grid Learning Services (GLS) that will personalize instruction based on an individual's presumed knowledge and cognitive and learning needs. The customized GLS will use real-time student modeling, the Semantic Web, intelligent agents, and pre-tests of cognitive, affective, and social characteristics to personalize the selection of educational resources and problems. Components of the customized GLS include an ontology construction agent, goal-based retrieval mechanisms, a lesson planner, and student and pedagogical agents.