The Shareable Content Object Reference Model (SCORM) is a widely adopted collection of specifications for web-based e-learning to which most Learning Management Systems adhere. While it allows reusability of content, it requires extensive, slow and expensive metadata annotation, and this fact prevents many content producers from properly creating and using Learning Objects. We propose an automatic metadata generation procedure that allows to label specific Learning Objects (scientific papers) with general metadata compliant to the SCORM. As some metadata are intrinsically unrelated to structure while others are strictly connected to structure, two different techniques were developed: one based on vocabularies and the other based on structural features. Results show that, in the provided context and for the "general" metadata category, the accuracy of annotations is comparable to that of a human expert.

Automatic generation of SCORM compliant metadata for portable document format files

MARATEA, Antonio;PETROSINO, Alfredo;MANZO, Mario
2012-01-01

Abstract

The Shareable Content Object Reference Model (SCORM) is a widely adopted collection of specifications for web-based e-learning to which most Learning Management Systems adhere. While it allows reusability of content, it requires extensive, slow and expensive metadata annotation, and this fact prevents many content producers from properly creating and using Learning Objects. We propose an automatic metadata generation procedure that allows to label specific Learning Objects (scientific papers) with general metadata compliant to the SCORM. As some metadata are intrinsically unrelated to structure while others are strictly connected to structure, two different techniques were developed: one based on vocabularies and the other based on structural features. Results show that, in the provided context and for the "general" metadata category, the accuracy of annotations is comparable to that of a human expert.
2012
9781450311939
9781450311939
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11367/32339
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