Context-Aware Mobile Language Learning

The rapid proliferation of mobile devices and its wide integration into people's daily life have enabled a wide range of applications that benefit from users’ context to deliver more personalized services. In this regard, teaching and learning systems have also evolved, and yet, many of these approaches have migrated to the mobile world in order to improve user experience by delivering information relevant to the individual's context. In this paper we present a context-aware mobile language learning application, focused on providing language support to users living in foreign countries. It suggests context-relevant vocabulary, considering usage context attributes such as user's gender, geolocation, and native language. The application architecture is composed by three components which are able to dynamically acquire and analyze the usage context to provide the corresponding information based on a domain knowledge. Our proof of concept was distributed among 27 users, and we analyzed their interactions with the application during a period of two months. Initial results demonstrate that the 37% of the users showed strong interest to use this kind of app, revealing a high usage potential in realistic scenarios.