Automatic Extraction of Pedagogic Metadata from Learning Content
Annotating learning material with metadata allows easy reusability by different learning/tutoring
systems. Several metadata standards have been developed to represent learning objects and courses. A learning
system needs to use pedagogic attributes including document type, topic, coverage of concepts, and for each
concept the significance and the role. Moreover, in order to have a flexible and reusable repository of e-learning
materials, it is necessary that the annotation of the documents with such metadata be done in an automatic
fashion as far as possible. This paper describes the attributes that represent some important pedagogic
characteristics of learning materials. To reduce the overhead of manual annotation we have explored the
feasibility of automatic annotation of learning materials with metadata. This facilitates the creation of an elearning
open repository for storing these annotated learning materials, which can be used by learning systems.
The automatic annotation is based on a domain knowledge base and a number of algorithms like standard
classification algorithms, parsing and analysis of documents have been used for this purpose. The results show a
fair degree of accuracy, which may be improved in future using more sophisticated algorithms.