A New Podium in Semantic Web Based E-Learning for Student Evaluation

Abstract

The Semantic Web is not a separate Web but an extension of the current one, in which information is given well-defined meaning, better enabling computers and people to work in cooperation. E-learning is network-enabled transfer of skills and knowledge. E-learning refers to using electronic application and processes to learn. E-learning applications and processes include web-based learning, computer-based learning, virtual classrooms and digital collaboration. E-learning offer obvious advantages for learners by making access to educational resources very fast, just-in- time and relevance, at any time or place. The Semantic Web technology has enabled by a set of suitable agents, which seems to be powerful enough to satisfy the e-learning requirements like fast, just- in-time and relevant learning. A new class of approach inspired by multi agent system and semantic web has been developed that can solve various problem of feedback between student and tutor. It includes personal agents of students and course tutors. Agents of students and tutors don't communicate directly. They send ontological information to informational agent that analyses them and returns the results to students and tutor. In this paper we derive a new approach, by building reference ontology and student domain ontology of physical layer and apply ontology comparison algorithm on them for evaluation of student. Comparison algorithm compares reference ontology and student ontology. By comparing reference ontology and student domain ontology student mistake can be analyzed. Analysis of student mistakes allows proposing them personalized recommendations.