There has been many efforts in the research community to create reusable learning objects with rich metadata specification. Even with this effort, there is still a gap in the document representation of learning objects and its contents semantics. This gap makes difficult to create individual plans made to explore the learning curve and necessities of each student when consuming digital learning objects. In this paper we present a novel approach based on the hyperknowledge conceptual model to improve the understanding, reasoning and visualization of the professors about the learning process of his or her students. This approach helps professors to make queries that identify student behaviors over time. It also allows recommendation systems to be developed exploiting good user practices and past behavior patterns to suggest better ways for students to browse educational content.

The web has become an important medium for access to information and users increasingly depend on it for their routine activities. Hence, the demand for higher quality services has grown strong and overload control has become a key problem to be addressed in web servers. This paper analyzes the implementation of a fuzzy admission controller in a QoS-enabled web server architecture and compares its results to traditional approaches. Our fuzzy controller allows better system performance tuning and contributes to smaller and more stable response times regarding http request processing. The fuzzy approach also provides added flexibility to system administration, as different associative matrices can be used, thus customizing the web server to different workload profiles.

The current best-effort service model used on the Internet treats all requests uniformly, both in the network and at the application level. However, sometimes it is desirable to provide different classes or levels of service in order to satisfy the needs of different users and applications. In this paper, we propose an architecture for the provision of differentiated services at the Web server level. The architecture is verified by means of a simulation model and real Web server traces are used as workload. Two priority-based algorithms are implemented in the architecture aiming at service differentiation. The adaptive algorithm, an innovative solution at the application domain, allows the tuning of the priority level provided and determines how strict the use of priorities would be. The system can then adapt itself to various workloads, an essential feature in a highly dynamic environment such as the Web.