Competence Visualisation: Making Sense of Data from 21st Century Technologies in Language Learning

Susan Bull, Barbara Wasson

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)147-165
Issue number2
Early online date8 Apr 2016
Publication statusPublished - May 2016


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