Challenges in context-aware mobile language learning: the MASELTOV approach

Mark Gaved; Patrick Luley; Sofoklis Efremidis; Iakovos Georgiou; Agnes Kukulska-Hulme; Ann Jones; Eileen Scanlon;

Open Access

English

doi: 10.1007/978-3-319-13416-1_34

Published: 01 Nov 2014

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Abstract

Smartphones, as highly portable networked computing devices with embedded sensors including GPS receivers, are ideal platforms to support context-aware language learning. They can enable learning when the user is en-gaged in everyday activities while out and about, complementing formal language classes. A significant challenge, however, has been the practical implementation of services that can accurately identify and make use of context, particularly location, to offer meaningful language learning recommendations to users. In this paper we review a range of approaches to identifying context to support mobile language learning. We consider how dynamically changing aspects of context may influence the quality of recommendations presented to a user. We introduce the MASELTOV project’s use of context awareness combined with a rules-based recommendation engine to present suitable learning content to recent immigrants in urban areas; a group that may benefit from contextual support and can use the city as a learning environment.

Subjects by Vocabulary

Microsoft Academic Graph classification: Context awareness Context (language use) Recommender system Multimedia computer.software_genre computer Language acquisition Global Positioning System business.industry business Learning environment Computer science Quality (business) media_common.quotation_subject media_common Formal language

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