The last decade has seen the scope of digital library usage extend from data warehousing and other common library services to building quality collections of electronic resources and providing web-based information retrieval mechanisms for distributed learning. This is clear from the number of ongoing research initiatives aiming to provide dynamic learning environments. A major task in providing learning environments is to define a resource model (learning object). The flexibility of the learning object model determines the quality of the learning environment. Further, dynamic environments can be realized by changing the contents and structure of the learning object, i.e. make it mutable. Most existing models are immutable after creation and require the library to support operations that help in creating these environments. This leaves the learning object at the mercy of the parent library's functionality. This thesis work is an extension of an existing model and allows a learning object to function independent of the operational constraints of a digital library by equipping learning objects with software components called methods that influence their operation and structure even after being deployed. It provides a reference implementation of an aggregate, intelligent, self-sufficient, object-oriented, platform-independent learning object model, which is conformant to popular digital library standards. It also presents a Java-based development tool for creating and modifying smart objects. It is capable of performing content aggregation, metadata harvesting and user repository maintenance operations, in addition to supporting the addition/removal of methods to a smart object. The current smart object implementation and the development tool have been deployed successfully on two platforms (Windows and Linux) where their operation was found to be satisfactory. / Master of Science