Adaptive content sequencing for e-learning courses using ant colony optimization

Abstract

Learners often get overwhelmed by the availability of large volumes of learning content in web-based educational systems. This content is presented to the learners either statically or with numerous hyper-links for navigation. The choice of content varies according to the requirements. Hence a static sequence of contents cannot satiate different learners enrolled in a course. Sequencing content according to the learners' needs is the objective of designing adaptive systems. Ant Colony Optimization (ACO) is an evolutionary technique that takes into account the dynamic nature of the problem and employs collective intelligence to provide optimized solutions. An ACO based algorithm Adaptive Content Sequencing in eLearning (ACSeL) is proposed in this paper that evaluates the level of a learner and recommends appropriate concepts to him/her. It is sensitive to the changes in learning behaviours of each learner and fine-tunes its strategies to recommend the next concept accordingly. The behaviours of past learners are captured and utilized to recommend content to prospective learners. © 2012 Springer India Pvt. Ltd.