Optimizing Learning Object Sequencing in E-Learning Systems Using Human Behaviour-Based Particle Swarm Optimization
Abstract
The distinctive requirements, educational attainment, and learning response of the learners are the critical key issues in the e-learning system. This goal is achieved by identifying the students' diverse assessments of their identity and capabilities and assigning them appropriate learning materials, as indicated by these highlights. The present paper introduces an efficient learning system that optimizes the sequencing of Learning Objects (LOs) in an e-learning system. Learning Objects (LOs) are educational materials typically divided into components. The procedure is performed by sequencing the learning objects of pupils or learners, and the sequence represents the organized arrangement of LOs. The sequencing problem can be considered a Constraint Satisfaction Problem (CSP) due to the utilization of the competency to characterize the correlation among LOs. The Human Behavior-based Particle Swarm Optimization (HPSO) algorithm can be employed to solve the problem using a swarm intelligence scheme. Results indicate that the algorithm is more effective in resolving the matter.
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