Course Composition based on Semantic Topical Dependency

Abstract: This paper describes an approach that can facilitate composition of course materials by machine assistance over the web using semantic web technology. A Semantic Topic Graph (STG) that encodes the conceptual knowledge metadata space is used as the front-end to the course resources. STG provides ontologies and properties of the concepts space and course materials are then connected with respect to their relation to this concept space. A course composer system is demonstrated which can intelligently compose various course materials based on pedagogical consideration. Some interesting comparisons of human guided machine-composed courses with real human composed courses in use in US graduate programs are shown