Semantic tools for e-learning

Learning can be significantly enhanced if a computer system could manipulate the knowledge based on learner needs and progress. Next generation learning management systems will behave more like programs than databases in that they will produce highly interactive and responsive content under algorithmic control. Before this can happen, how information and knowledge are stored in computers must be transformed so that computers (algorithms) can infer the meaning and context of content from the content itself. Recent advances in the “semantic web” and the web ontology language, OWL, now make it possible to produce such context-aware databases that adhere to international standards and protocols . What is left is to produce the algorithms and programs that can traverse, extract, and manipulate the knowledge in a semantic database and deliver a truly interactive and adaptive learning system. The central technical objectives of this grant are: 1) to create a representative knowledge database compatible with the OWL standards; 2) to produce a preliminary set of programs that can extract and manipulate this knowledge database based on learner input and perceived needs; and 3) to empirically demonstrate the effectiveness of these tools for appropriate learner populations.