Adaptive Learning Portal Architecture for E-Learner

Adaptive Learning Portal Architecture for E-Learner

Teachers usually have a personal understanding of what“good teaching”means from their experience and domain knowledge background in education, lots of them create learning resources（LR） and put on the web for learners or students to study. In fact, most of student can not find the suitable LR （e.g. learning materials, or learning assets, or learning packages） from webs, In this paper, we based on ontology and fuzzy technology to propose an architecture for adaptive and re-usability in personalized web-based E-Education Portal, help learners fetch the LR from ontology LR repositories according by the learner characteristics/attribute （e.g. domain knowledge background and Kolb's [11]“Learning Style”）, and we also interested in exploiting the semantic relationships that characterize theses LRs, so we redefine two“relation”attributes from Dublin Core [10] metadata schema call“Pre_Relation”and“Succ_Relation”for enhance LR relations in order to recommend the relative LRs for learner further reference.