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Quality Metrics for Learning Object Metadata Xavier Ochoa, ESPOL, Ecuador Erik Duval, KULeuven, Belgium
Standardization and Interoperability of Learning Objects Repositories has solved the “chicken and egg” problem… …but has created new ones.
The production, management and consumption of Learning Object Metadata is vastly surpassing the human capacity to review or process these metadata.
Why Measuring Quality? ,[object Object],[object Object]
How to Measure Metadata Quality? ,[object Object],[object Object]
But we cannot measure the quality  manually anymore…
… but is a good idea to follow the same quality characteristics.
Our Proposal: Use Metrics ,[object Object],[object Object]
Quality Characteristics ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Quality Metrics ,[object Object]
Quality Metric Readability Textual Information Content Nominal Information Content Weighted Completeness Simple Completeness Metric Formula Metric Name
Evaluation of the Metrics ,[object Object],[object Object],[object Object],[object Object],[object Object]
Evaluation Results
Applications ,[object Object],[object Object],[object Object],[object Object]
Repository Evaluation
Quality Visualization
Automated Evaluation of Quality
Further Work ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Thank you, Gracias Comments, Suggestions, Critics… are Welcome! More Information: http://ariadne.cti.espol.edu.ec/M4M

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Quality Metrics for Learning Object Metadata