Applying Ant Colony Optimisation When Choosing an Individual Learning Trajectory
Source of Publication
Lecture Notes in Networks and Systems
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.
Springer International Publishing
Ant Colony Optimisation, Individual Learning Trajectory, Algorithm, Graph, Path, E-learning
Deetjen-Ruiz, Rukiya; Ikonnikov, Oleg; Azizam, Shahzool Hazimin; García, Darío Salguero; Gavilán, Juan Carlos Orosco; Otcheskiy, Ivan; and Tsarev, Roman, "Applying Ant Colony Optimisation When Choosing an Individual Learning Trajectory" (2023). All Works. 5916.
Indexed in Scopus