Luis de Marcos Ortega , Roberto Barchino Plata , J. J. Martínez, J. A. Gutiérrez
In e-learning initiatives, sequencing problem concern the arranging of a particular learning unit's set in a suitable order for a particularlearner. Sequencing is usually performed by instructors who create a general-public ordered series rather than learner personalizedsequences. This paper proposes an innovative intelligent technique for learning object automated sequencing using particle swarms. E-Learning standards are upheld in order to ensure interoperability. Competencies are used to define relations between learning objectswithin a sequence, so that the sequencing problem turns into a permutation problem and artificial intelligent techniques can be used tosolve it. Particle Swarm Optimization (PSO) is one such technique and it has proved to perform well for solving a wide variety ofproblems. An implementation of PSO for the learning object sequencing problem is presented and its performance in a real scenario isdiscussed.
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