Distance foreign language learning: Promoting face to face interaction using data mining techniques

Abstract

In this paper, we propose the use of data mining methods to promote face to face interaction between members of distance language learning communities. We develop a system that collects data from different Moodle platforms and social networks in order to extract detailed profiles of the members, as well as an estimation of correlation among users. Moreover, we describe an enhancement of the Moodle mobile application that uses beacon indoor positioning technology in order to locate proximate users in public places. We finally show how the application assists a user to start a discussion with another user by finding common interests and other matching characteristics between the users.