An Ant Colony Optimization based Advice Generation for Curriculum Sequencing under Flexible Learning System

Abstract — Curriculum sequencing aims to provide a customized optimal learning path through the curriculum landscape to individual learners since learners have different prior background knowledge, preferences, and goals. Researchers have given considerable attention to flexible curriculum sequencing control to provide adaptable, personalized learning programs. In an adaptive educational system, an optimal learning path aims to maximize a combination of parameters including the learner’s understanding of courseware and the efficiency of learning the courseware. Flexibility in learning offers a learner an autonomy and control over his/her learning process as self-regulated learning. There exist a number of dimensions of flexible learning like class times, course content, location, organizational infrastructure, methods, learning styles, course requirements etc. This paper presents a scheme for advice generation, with the help of ACO, for curriculum sequencing under flexible learning system. The proposed frame work provides flexibility in time by asking the learner his affordability and allows his choice of the subjects to be learned by tracking his learning experiences. On the basis of these parameters, an optimized advice is generated, suggesting the learner, his future course of action, to be targeted towards the achievement of his learning objectives. The proposed system has been found to work satisfactorily with various test cases