Knowledge Discovery and modeling in Intelligent Tutoring Systems

点击翻译按钮获取中文摘要

Knowledge acquisition has always been the major bottleneck for knowledge-based systems (KBS). This is especially true for Intelligent Tutoring Systems (ITS) in which knowledge base includes domain ontology and problem solving knowledge. In order for ITSs to thrive in fields where knowledge evolves rapidly, such as business and industrial settings, new, easy-to-use tools must be developed for knowledge acquisition and maintenance. The first knowledge creation problem finds its source in the fact that the knowledge base usually has to be created manually, from scratch. However, crucial information already exists, hidden in legions of existing documents and databases within communities and organizations. Domain expert are required to make it explicit and provide relevant knowledge to the artificial tutor so that it will be able to guide the learner through competence and problem solving skills development. However, in several domains, problem solving knowledge is not easy to predetermine and it evolves.