Multiple parameter cluster analysis in a multiple language learning system

Abstract

In this paper, we present our multiple parameter cluster analysis in our multiple language learning system. Towards this direction, we have used algorithmic approaches residing in the field of machine learning. Multiple parameter cluster analysis is conducted by the k-means clustering algorithm which takes as input seven important users' characteristics in order to initialize the process. The clustering is conducted by k-means clustering algorithm, which takes as input multiple user characteristics. The incorporation of k-means clustering is used to address several barriers posed by the heterogeneous learning audience of educational systems. After determining in which cluster each new student belongs, the system can reason about this specific student, adapting its behavior to the student's needs, performance and preferences.