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

Luis de Marcos Ortega , Antonio García Cabot , Eva García López , José Amelio Medina Merodio

• 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.