ABSTRACT

Knowledge is collected and organized into technology-based systems in various ways to support learning and performance. Four main types of systems are identified under the general term of knowledge systems: (1) expert or knowledge-based, (2) knowledge management, (3) knowledge communities, and (4) hybrid systems that combine elements of the other types. Expert systems are computer programs that use knowledge derived from human experts to provide guidance to novices. A number of these systems have been adapted to assist in learning. Expert systems use captured knowledge to help a computer program provide assistance to a user. In knowledge management systems, the knowledge is captured and organized for direct access by the user. The third type of system is aimed at facilitating direct human-to-human communication of knowledge and includes research that comes under the categories of communities of practice or knowledge communities. This area also includes informal knowledge sharing networks that emerge through such technologies as instant messaging. This chapter highlights common research issues that cut across the three approaches, including how knowledge is derived from human sources; how knowledge is encoded in a machine readable form; how collections of digital knowledge are organized using taxonomies, metadata, and ontology; and, finally, knowledge quality assurance.