Learning needs for special needs learners: A graph based adaptive approach for content sequencing

Abstract

This paper considers a graph based adaptive approach for sequencing of learning objects for Special Needs Learners (SNL) in customized manner. The proposed algorithm traverses the nodes of the graph containing learning content topics in effective manner. This approach ensures not only customized learning for special needs learners, but also imparts some level of intelligence in the process of learning. The SNL goes through the necessary nodes on the graph form the first node of the learning module (priority based) to the last learning module considering the priorities and needs of the learners and obtains the optimal solution for the SNL. The algorithm is designed in such a way that the learning process and outcome are inline with the predefined curriculum. The curriculum is a tailor made collaboration of various independent and reusable learning modules as per the personalized requirements and the learning ability of the SNL. The paper also proposes the parameters that would contribute for the personalized learning of the SNL.