|
Title:
|
A LEARNING WEB RESOURCE RECOMMENDER SYSTEM BASED ON SOCIAL TAGGING |
|
Author(s):
|
Fatima Zahra Lahlou, Driss Bouzidi |
|
ISBN:
|
978-972-8939-71-7 |
|
Editors:
|
Miguel Baptista Nunes and Pedro Isaías |
|
Year:
|
2012 |
|
Edition:
|
Single |
|
Keywords:
|
E-learning, recommender systems, social annotation systems, social tagging, Learning Object Metadata, web usage mining. |
|
Type:
|
Short Paper |
|
First Page:
|
398 |
|
Last Page:
|
402 |
|
Language:
|
English |
|
Cover:
|
|
|
Full Contents:
|
click to dowload 
|
|
Paper Abstract:
|
Social annotation systems allow users to comment and organize resources on the web. The use of these systems in e-learning shows great potential in improving learning quality. In this paper, we first discuss the impact of using these systems for learning purposes, then we suggest an architecture for a learning web resource automatic recommender tool based on social tagging. This tool draws from web resources annotated by learners, and, by implicitly inferring active learners preferences, suggests educational resources that could be of interest to them. |
|
|
|
|
|
|
