A Classification-Based Framework for Learning Object Assembly
ICALT '05 Proceedings of the Fifth IEEE International Conference on Advanced Learning Technologies
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When machine-understandability is required to build software modules that automatically retrieve and combine learning objects, learning object relationships should be carefully considered, as they raise important semantic issues that influence runtime behaviour. In this paper, we analyse how learning object relationships have an effect on learning object contracts and look for analogies with the object-oriented paradigm. Being some of the most common relationships, we focus on the commitments that aggregation and generalization impose on learning object contracts.