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Analyzing Convergence in e-Learning Resource Filtering Based on ACO Techniques: A Case Study With Telecommunication Engineering Students | IEEE Journals & Magazine | IEEE Xplore

Analyzing Convergence in e-Learning Resource Filtering Based on ACO Techniques: A Case Study With Telecommunication Engineering Students


Abstract:

The use of swarm intelligence techniques in e-learning scenarios provides a way to combine simple interactions of individual students to solve a more complex problem. Aft...Show More

Abstract:

The use of swarm intelligence techniques in e-learning scenarios provides a way to combine simple interactions of individual students to solve a more complex problem. After getting some data from the interactions of the first students with a central system, the use of these techniques converges to a solution that the rest of the students can successfully use. This paper uses a case study to analyze how fast swarm intelligence techniques converge when applied to solve the problem of e-learning resource filtering. Some modifications to traditional ant colony optimization (ACO) algorithms based on student filtering are also introduced in order to improve convergence.
Published in: IEEE Transactions on Education ( Volume: 53, Issue: 4, November 2010)
Page(s): 542 - 546
Date of Publication: 16 October 2009

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