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

作者：Munoz Organero Mario^*; Ramirez Gustavo A; Munoz Merino Pedro; Delgado Kloos Carlos

来源：IEEE Transactions on Education, 2010, 53(4): 542-546.

DOI：10.1109/TE.2009.2032168

• ant colony optimization (ACO) techniques
• convergence analysis in e-learning
• educational technology
• higher education
• learning systems
• resource filtering in e-learning
• student experiments

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.

• 出版日期2010-11