This study seeks insight as to how the emergence of learning resource collections being created primarily by way of metadata–data about data–harvesting and aggregation might be improved to further empower the searches of students and teachers alike. As it stands, descriptive programming of metadata is often inconsistent among platforms.
Looking at keywords authored under the Learning Object Metadata (LOM) standard, researchers tracked the frequency of use and categorized the keywords under four different classifications: general keywords, classification keywords, entries, and coverage. Ideally, the sample learning objects would fit all four classifications yet none did.
Though their findings were not as successful as they had hoped, there is promise in English being well represented in metadata similarities. This enforces the idea that universal implementation of a meta data standard like LOM could greatly increase the breadth and accuracy of searches for educational resources online.