Building interoperable vocabulary and structures for learning objects

Jian Qin, Naybell Hernández

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


The structural, functional, and production views on learning objects influence metadata structure and vocabulary. The authors drew on these views and conducted a literature review and in-depth analysis of 14 learning objects and over 500 components in these learning objects to model the knowledge framework for a learning object ontology. The learning object ontology reported in this article consists of 8 top-level classes, 28 classes at the second level, and 34 at the third level. Except class Learning object, all other classes have the three properties of preferred term, related term, and synonym. To validate the ontology, we conducted a query log analysis that focused on discovering what terms users have used at both conceptual and word levels. The findings show that the main classes in the ontology are either conceptually or linguistically similar to the top terms in the query log data. The authors built an "Exercise Editor" as an informal experiment to test its adoption ability in authoring tools. The main contribution of this project is in the framework for the learning object domain and the methodology used to develop and validate an ontology.

Original languageEnglish (US)
Pages (from-to)280-292
Number of pages13
JournalJournal of the American Society for Information Science and Technology
Issue number2
StatePublished - Jan 15 2006

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Networks and Communications
  • Artificial Intelligence


Dive into the research topics of 'Building interoperable vocabulary and structures for learning objects'. Together they form a unique fingerprint.

Cite this