Interactive Event: From a Virtual Village to an Open Learner Model with Next-TELL

Bull, Susan; Kickmeier-Rust, Michael D.; Meissl-Egghart, Gerhilde; Johnson, Matthew; Wasson, Barbara; Alotaibi, Mohammad; Hansen, Cecilie

doi:10.1007/978-3-642-39112-5_152

Cited by 2 publications

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“…OLMs and independent OLMs have been developed for a variety of language contexts. Examples include: overviews of the extent of understanding English grammar items (Zapata-Rivera, Hansen, Shute, Underwood & Bauer, 2007); pronunciation (Demmans Epp & McCalla, 2011); learning technical terminology (Dimitrova, 2003); historical text comprehension (Grigoriadou, Tsaganou & Cavoura, 2003); prompting noticing (Shahrour & Bull, 2009) and awareness (Xu & Bull, 2010) in language learning; and as a means to bring together information on student competences drawn from a variety of classroom activities (Bull, Wasson, Kickmeier-Rust, Johnson, Moe, Hansen, Meissl-Egghart & Hammermueller, 2012). Similar approaches in the foreign or second language domain are reflected in performance reports, for example, as described by Heift (2005).…”

Section: Open Learner Models For Learners and Teachersmentioning

confidence: 99%

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

Bull

Wasson

2016

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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.

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Section: Open Learner Models For Learners and Teachersmentioning

confidence: 99%

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

Bull

Wasson

2016

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“…The connecting tool could be any piece of educational software or, indeed, any software used for educational purposes (see Bull et al, 2013b for an example). This allows other systems to contribute evidence to the learner model and to read the learner model.…”

Section: Summary and Discussionmentioning

confidence: 99%

Measuring and Visualizing Learning in the Information-Rich Classroom

Reimann

Bull²,

Kickmeier-Rust

et al. 2015

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Integrated information systems are increasingly used in schools, and the advent of the technology-rich classroom requires a new degree of ongoing classroom assessment. Able to track web searches, resources used, task completion time, and a variety of other classroom behaviors, technology-rich classrooms offer a wealth of potential information about teaching and learning. This information can be used to track student progress in languages, STEM, and in 21st Century skills, for instance. However, despite these changes, there has been little change in the kind of data made available to teachers, administrators, students, and parents.Measuring and Visualizing Learning in the Information-Rich Classroom collects research on the implementation of classroom assessment techniques in technology-enhanced learning environments. Building on research conducted by a multinational and multidisciplinary team of learning technology experts, and specialists from around the globe, this book addresses these discrepancies. With contributions from major researchers in education technology, testing and assessment, and education psychology, this book contributes to a holistic approach for building the information infrastructure of the 21st Century school.

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Interactive Event: From a Virtual Village to an Open Learner Model with Next-TELL

Cited by 2 publications

References 2 publications

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

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

Measuring and Visualizing Learning in the Information-Rich Classroom

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Interactive Event: From a Virtual Village to an Open Learner Model with Next-TELL

Cited by 2 publications

References 2 publications

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

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

Measuring and Visualizing Learning in the Information-Rich Classroom

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Product

Resources

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

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