Evolutionary computation approaches to the Curriculum Sequencing problem

Abstract

Within the field of e-Learning, a learning path represents a match between a learner profile and his preferences from one side, and the learning content presentation and the pedagogical requirements from the other side. The Curriculum Sequencing problem (CS) concerns the dynamic generation of a personal optimal learning path for a learner. This problem has gained an increased research interest in the last decade, as it is not possible to have a single learning path that suits every learner in the widely heterogeneous e-Learning environment. Since this problem is NP-hard, heuristics and meta-heuristics are usually used to approximate its solutions, in particular Evolutionary Computation approaches (EC). In this paper, a review of recent developments in the application of EC approaches to the CS problem is presented. A classification of these approaches is provided with emphasis on the tools necessary for facilitating learning content reusability and automated sequencing.