No abstract

No abstract

No abstract

No abstract

Purpose -The broader adoption of the internet along with web-based systems has defined a new way of exchanging information. That advance added by the multiplication of mobile devices has required systems to be even more flexible and personalized. Maybe because of that, the traditional teaching-controlled learning style has given up space to a new way of learning, which is more flexible and adequate to the learners needs. The purpose of this research is to go further into the semantic modeling of adaptive web based learning systems. Particularly, the paper focuses on those learning systems that consider in their definition the awareness of student's context in order to properly react to the student needs. Design/methodology/approach -In this paper the authors introduce a semantic model of the student context in terms of an ontology network. This semantic model is explored in order to detect the "current situation" of students when they are navigating into e-learning environments. The final objective is to enrich the adaptation functionality of e-learning environments, being able to evaluate context data from personal profile, learning domain and technological situation. Findings -In order to evaluate the semantic model defined, examples of detected situations are shown in accordance to specific e-learning scenarios. Originality/value -The paper covers definition of a flexible and modularized model by using ontology networks, which can be easily modified to incorporate new knowledge data, aiding the modeling of concepts from different learning environments.

This paper presents a multi-agent model for resouree aIloeation planning in a manufaeturing environment. This model eonsiders the temporal and synehronism aspeets involved in the aIloeation proeess. The main eontributions ofthis work are: (i) the definition of a formal strategy for resouree aIloeation supported through a multi-agent system that would be able to reduee the eomplexity of the model eonsidering real-time events that potentially affeet the aIloeation, (ii) the definition of a hierarehieal multi-agent arehiteeture with eapaeity to support this strategy.

No abstract

No abstract