Combining Auto-Grouping Algorithm with Semantic Social Network Service to Improve Self-Directed Distance Learning

Abstract

Many people need to accumulate or update their structure of knowledge or pursue degrees via distance learning. Although distance learning is a convenient, there exists loneness to some extent among the students in self-directed e-learning systems, because all the students have to study alone. In this paper, two auto-grouping algorithms and semantic web are designed to enhance distance leaning effects. The two auto-grouping algorithms are used to auto-form Social networks among students to help them overcome the loneness, and the semantic web technology is used to organize the related resources to accelerate intelligent search. Auto-grouping algorithms and semantic SNS are integrated into the existing e-learning platform of BUPT. According to the results of learning a course during one semester, the scores of final exam and the feedbacks from the students suggest that semantic SNS and auto-grouping algorithm make a positive impact on the self-directed distance learning.