Ontology-driven incremental annotation of educational content for instruction planning

Amidst the millions of pages available on the Web, it contains an invaluable educational resources pool for planning episodes of learning approach for instructions and guided learning. The un-structured nature and the lack of suitably annotated materials make retrieving the relevant learning contents that meet different pedagogical needs a difficult and time-consuming task. In this paper, we propose a framework as well as the design of a Personalized Instruction planner (PIP) that searches and annotates potentially useful learning content. Our approach is based on an ontology-driven and incremental approach to the annotation of educational content using the multi-agents infrastructure of a Personalized Education System (PES). The PIP which is a subsystem of the PES is composed of three software agents whose roles is to search, retrieve and classify potentially useful learning objects for personalized education guided by multiple ontologies that taxonomize subject domain, instructional design or pedagogy and content. © 2005 Asia-Pacific Society for Computers in Education.