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.