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

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4 Author(s)
Munoz-Organero, M. ; Carlos III Univ. of Madrid, Leganes, Spain ; Ramirez, G.A. ; Merino, P.M. ; Kloos, C.D.

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.

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Education, IEEE Transactions on  (Volume:53 ,  Issue: 4 )