A Formal Model of Learning Object Metadata

In this paper, we introduce a new, formal model of learning object metadata. The model enables more formal, rigorous reasoning over metadata. An important feature of the model is that it allows for 'fuzzy' metadata, that have an associated confidence value. Another important aspect is that we explicitly address context dependent metadata. 1 The Formal Model of Metadata In this paper we develop a formal or mathematical model for learning object metadata. Such a model helps to build a formal, rigorous reasoning about metadata in the case of share and reuse. One of the situations in which such a formal model is useful, is, for example, the discussion of automatic indexing of learning objects. One of the important aspects we introduce in this formal model is the representation of context-awareness in metadata. A context represents a specific situation in which a learning object can be used. These contexts allow us to define more advanced metadata values which enable a better, i.e...

• Type: Conference
• Year: 2006
• Where: ECTEL
• Authors: Kris Cardinaels, Erik Duval, Henk J. Olivié
• Keywords: ECTEL 2006, Formal Model, Learning Objects, Machine Learning, Model