Multiple language learning: Creating user models through Voronoi iteration

Learning foreign languages during the last decade is highly supported by computer systems and their corresponding software applications. However, in the fast and demanding pace of modern life, it is quite common finding people who learn to speak not only one but many foreign languages at the same time. Tutoring systems that support this kind of more demanding electronic teaching need to incorporate intelligence and also adaptation to the needs of their users. Both the creation and the successful incorporation of these user models into a tutoring system are accomplished through the implementation of the Voronoi iteration. In this way, users’ characteristics define data points in Euclidean space and are grouped into a given number of categories using k-means clustering. A basic aim of this work is to utilize pre-stored information about past users in order to help future users learn more successfully and more efficiently. Keywords-student modeling; stereotypes; machine learning for user modeling; k-means algorithm; language learning; intelligent