Scheduled System Maintenance on May 29th, 2015:
IEEE Xplore will be upgraded between 11:00 AM and 10:00 PM EDT. During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

The research on personalized distance learning system based on ACO algorithm

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Hui Xie ; Coll. of Electron. Eng., Naval Univ. of Eng., Wuhan, China ; Zhi-gang Zhang ; Cheng-hua Yan ; Feng Nie

Personalized services is an effective means to improve the quality of distance learning, as the learning materials and teaching methodology can be tailored toward each learner's interest and knowledge to make teaching and learning more effective. This paper introduces the artificial intelligence idea of ant colony optimization to the design of distance learning systems. The emphasis is given on how to track the learners' interest based on ant colony optimization algorithm. By recording the click frequency and the staying time of the knowledge point, the proposed approach achieves a timely learner's interest tracking, thus dynamically provides suitable personalized learning recommendations to different types of learners.

Published in:

Industrial Mechatronics and Automation, 2009. ICIMA 2009. International Conference on

Date of Conference:

15-16 May 2009