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Evolutionary computation approaches to the Curriculum Sequencing problem

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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.

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Notes

  1. http://www.ariadne-eu.org/.

  2. http://www.edutella.org/edutella/edutella.shtml.

  3. http://www.adlnet.gov.

  4. http://www.imsglobal.org.

Abbreviations

AACS:

Attribute-based Ant Colony System

ACO:

Ant Colony Optimization

CS:

Curriculum Sequencing problem

CSP:

Constraint Satisfaction Problem

DYLPA:

Dynamic Learning Path Advisor

EA:

Evolutionary Algorithm

EC:

Evolutionary Computing

ES:

Evolution Strategies

GA:

Genetic Algorithm

GP:

Genetic Programming

HMA:

Hierarchical Memetic Algorithm

IMS:

Instructional Management Systems

LO:

Learning object

LOM:

Learning Object Metadata

LR:

Learning resource

MA:

Memetic Algorithms

PC2PSO:

Personalized e-Course Composition approach based on Particle Swarm Optimization algorithm

PSO:

Particle Swarm Optimization

SACS:

Style-based ACO system

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The authors wish to thank the anonymous reviewers who offered valuable comments, provided detailed suggestions and spotted errors that resulted in improving the content of this paper.

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Correspondence to Sarab Al-Muhaideb.

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Al-Muhaideb, S., Menai, M.E.B. Evolutionary computation approaches to the Curriculum Sequencing problem. Nat Comput 10, 891–920 (2011). https://doi.org/10.1007/s11047-010-9246-5

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