Learning objects retrieval from contextual analysis of user preferences to enhance e-learning personalization

The need to adapt the system’s behavior to user preferences is a reality in many fields of knowledge. Specifically in the e-learning area it is very important to be aware of learner differences so that scenarios can be composed that are tailored to the student’s best learning conditions and aptitudes. This paper proposes a mechanism to retrieve learning objects based on the analysis of user preference data garnered from contextual information about student interactions. This mechanism is performed by a component of a system architecture that builds an e-learning scenario dynamically, according to the student’s classification in a specific learning profile. The purpose of the architecture is to personalize e-learning scenarios by presenting the student with several learning objects