Human-Generated Learning Object Metadata

Abstract

The paper examines how to address the need for a production process for e-learning resources to include human generated metadata, and considers how users will exploit this metadata. It identifies situations in which human production of metadata is unavoidable, and examines fundamental problems concerned with human metadata generation such as motivation and shared understanding. It proposes and discusses some methods to exploit endemic motivational factors within communities in an attempt to ensure good quality human generated metadata, and identifies how ontological constructs can support the exploitation of such metadata. The relevance of these methods to the semantic web in general is discussed.