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Swarm intelligence in e-learning: a learning object sequencing agent based on competencies
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Genetic And Evolutionary Computation Conference archive
Proceedings of the 10th annual conference on Genetic and evolutionary computation table of contents
Atlanta, GA, USA
SESSION: Ant colony optimization, swarm intelligence, and artificial immune systems papers table of contents
Pages 17-24  
Year of Publication: 2008
ISBN:978-1-60558-130-9
Authors
Luis de Marcos  University of Alcala, Alcala de Henares, Spain
José-Javier Martínez  University of Alcala, Alcala de Henares, Spain
Jose-Antonio Gutierrez  University of Alcala, Alcala de Henares, Spain
Sponsors
ACM: Association for Computing Machinery
SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
Publisher
ACM  New York, NY, USA
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ABSTRACT

In e-learning initiatives content creators are usually required to arrange a set of learning resources in order to present them in a comprehensive way to the learner. Course materials are usually divided into reusable chunks called Learning Objects (LOs) and the ordered set of LOs is called sequence, so the process is called LO sequencing. In this paper an intelligent agent that performs the LO sequencing process is presented. Metadata and competencies are used to define relations between LOs so that the sequencing problem can be characterized as a Constraint Satisfaction Problem (CSP) and artificial intelligent techniques can be used to solve it. A Particle Swarm Optimization (PSO) agent is proposed, built, tuned and tested. Results show that the agent succeeds in solving the problem and that it handles reasonably combinatorial explosion inherent to this kind of problems.


REFERENCES

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Collaborative Colleagues:
Luis de Marcos: colleagues
José-Javier Martínez: colleagues
Jose-Antonio Gutierrez: colleagues