Parliamentary optimization to build personalized learning paths: case study in web engineering curriculum

• Autores: Luis de Marcos Ortega, Antonio García Cabot, Eva García López, José Amelio Medina Merodio
• Localización: The International journal of engineering education, ISSN-e 0949-149X, Vol. 31, no. 4, 2015, págs. 1092-1105
• Idioma: inglés
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• Resumen

  • In this paper we present a practical application of POA (Parliamentary Optimization Algorithm) for creating personalizedlearning paths in online learning. The objective of building a personalized learning path is to produce a suitable sequence oflearning units for a student to work with. We present and tune the parliamentary metaheuristic for a practical instance ofthe sequencing problem in a web engineering master programme and compare it with standard versions of other wellestablished metaheuristics (PSO and genetic algorithms). Results suggest that permut-POA deals satisfactorily withsequencing problems and it is easy to fine tune, and also that it outperforms the other optimizers.