DEVELOPMENT OF GENETIC ALGORITHM-BASED CURRICULUM SEQUENCING MODEL IN PERSONALISED E-LEARNING ENVIRONMENT

Abstract

Personalised learning allows individual learner to be taught and assessed in ways that are appropriate and comfortable for that learner. Some existing works on personalised e learning have dealt with learner’s preference without considering the difficulty level of the course concepts, other works failed to show the degree of relationship that exists between the various course concepts. Hence, these affect the learning ability and the overall performance of learners. This research presents a genetic algorithm-based curriculum sequencing model in personalised e-learning environment. It helps learners to identify the difficulty level of each of the curriculum or course concepts and the relationship degrees that exist between the course concepts in order to provide an optimal personalised learning pattern to learners based on curriculum sequencing. Course contents are developed and preliminary questions (called pretest for each learning concepts) are prepared by a group of experienced lecturers in that particular course. The pretest is administered to the individual learners and some course concepts experts. The respective responses are collected and analyzed in order to determine the difficulty parameters of the course concepts and the degrees of relationship between course concepts. Both the difficulty parameter of course concepts and the degrees of relationship between course concepts are considered for the genetic algorithm in order to generate the personalised learning path for learners to improve the learning performance of the learners. The implementation result showed that the system categorised learners into three different levels: partially successful, moderately successful and highly successful in each of the course concepts in the following ratio 10.5%:31.6%:57.9% in concept1, 0%:36.8%:63.2% in concept 2, 10.5%:26.3%:63.2% in concept 3, 15.8%:15.8%:68.4% in concept 4 and 5.3%:26.3%:68.4% in concept 5. The system was implemented using the following tools; VISUAL STUDIO 2010, Asp.net- an interface design tool that makes use of HTML, C# programming language to code the design and Microsoft Structured Query Language (MSQL) server 2005 as the backend database.