The concept of learning objects has been applied in the e-learning field to promote the accessibility, reusability, and interoperability of learning content. Learning Object Metadata (LOM) was developed to achieve these goals by describing learning objects in order to provide meaningful metadata. Unfortunately, the conventional LOM lacks the computer interpretability needed to support knowledge representation when searching for finding relevant learning objects. This study addresses this issue by defining a Multi-layered Semantic LOM Framework (MSLF) for integrating Semantic Web technologies into LOM. The proposed MSLF is used to develop LOFinder, an intelligent LOM shell that provides an alternative approach to enhancing the knowledge representations. To test its feasibility, this study implemented a java-based prototype of LOFinder that enables intelligent discovery of learning objects. (Contains 4 tables and 10 figures.)