Applying Ant Colony Optimisation When Choosing an Individual Learning Trajectory

Document Type

Book Chapter

Source of Publication

Lecture Notes in Networks and Systems

Publication Date

7-15-2023

Abstract

The effectiveness of learning depends in many ways on the organization of the educational process. These days, the educational environment is becoming more flexible and responsive to the needs of students. The traditional form of learning is expanding through the use of new approaches and teaching methods, learning systems, and information technology. Individual learning trajectory allows the learner to regulate the order of studying course modules and the pace of mastering the subject material. Decision-making in choosing the learning trajectory can be supported by specialized methods and tools. This paper proposes the use of ant colony optimisation to support decision making on the choice of an individual learning trajectory. #CSOC1120.

ISBN

978-3-031-35316-1, 978-3-031-35317-8

ISSN

2367-3389

Publisher

Springer International Publishing

Volume

723

First Page

587

Last Page

594

Disciplines

Education

Keywords

Ant Colony Optimisation, Individual Learning Trajectory, Algorithm, Graph, Path, E-learning

Indexed in Scopus

no

Open Access

no

Link to Full Text

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