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Competence visualisation: Making sense of data from 21st-century technologies in language learning

Published online by Cambridge University Press:  08 April 2016

Susan Bull  and
Barbara Wasson
Susan Bull
Affiliation:
Institute of Education, University College London, UK (email: [email protected])
Barbara Wasson
Affiliation:
University of Bergen, Norway (email: [email protected])
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Abstract

This paper introduces an open learner model approach to learning analytics to combine the variety of data available from the range of applications and technologies in language learning, for visualisation of language learning competences to learners and teachers in the European language context. Specific examples are provided as illustrations (Facebook, Second Life and mobile assisted language learning (MALL)), though the approach is a general one. We describe the Next-TELL open learner model as an exemplar that can encompass a range of data from a variety of technologies and activities, and as a competence-focussed visual analytics tool that can be readily used inside and outside the classroom.

The Next-TELL open learner model offers several visualisations for learners and teachers to explore the learner’s current competences, which can be selected according to user preferences or the purpose of viewing the learning data. The selection of visualisations means that the open learner model is appropriate for school, university and other learning contexts. Viewing this data can help students to reflect on and monitor their learning, and can support teachers’ decision-making during classroom activities or later, in their planning of subsequent sessions. As an example, we outline the use of the Next-TELL open learner model in a school in Norway.

Keywords

Open learner model21st-century technologieslanguage learning competencesvisual learning analytics
Type
Regular papers
Information
ReCALL , Volume 28 , Issue 2 , May 2016 , pp. 147 - 165
Copyright
Copyright © European Association for Computer Assisted Language Learning 2016 

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