Genetic Algorithm-based Curriculum Sequencing Model For Personalised E-Learning System

Abstract

Personalised learning is a way of organising the learning content and to be accessed by the individual learner in a manner that is suitable to learner's requirements. There are existing related works on personalised e-learning systems that focused on learner's preference without considering the difficulty level and the relationship degree that exists between various course concepts. Hence, these affect the learning ability and the overall performance of learners. This research paper presents a genetic algorithm-based curriculum sequencing model in a personalised e-learning environment. It helps learners to identify the difficulty level of each of the curriculum or course concepts and the relationship degree that exists between the course concepts in order to provide an optimal personalised learning pattern to learners based on curriculum sequencing to improve the learning performance of the learners. The result of the implementation showed that the genetic algorithm is suitable to generate the optimal learning path using the values of difficulty level and relationship degree of course concepts. Furthermore, the system classified the learners into three different understanding levels of the course concepts such as partially, moderately and highly successful.