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Editorial

Published online by Cambridge University Press:  08 April 2016

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Abstract

Type
Editorial
Copyright
Copyright © European Association for Computer Assisted Language Learning 2016 

This issue of ReCALL is a reflection of the growing strength of two areas that have been enjoying increasing popularity in our field: Web 2.0 technologies for language learning, and data-driven learning (DDL). While certainly not new in CALL, these areas continue to be the main topic of a very large volume of submissions, making it at times difficult for authors to get their paper accepted for publication. The papers in this issue are exemplars of what editors and reviewers normally look for in a manuscript: original studies whose findings bring new insights that can potentially transform the way we teach and learn languages in the 21st century, or new research paradigms or instruments that can consolidate our existing teaching and research methodologies.

The first three articles in this issue focus on Web 2.0 technologies and language learning, and highlight the need for supporting learners as they engage in online language learning activities. All three suggest valuable directions for both our pedagogical practice and research agenda. More specifically, Liu, Wang and Tai use flow theory and the strategic motivation framework to study young learners’ engagement and motivation during Web 2.0 digital storytelling activities. They demonstrate that while motivation and engagement are dynamic and often cyclical, digital storytelling can enhance language development. Next, Gabaudan’s paper argues that online journals and blogging, combined with formative feedback, can support higher education students while abroad under the European Erasmus programme. Finally, Bull and Wasson present the Next-TELL open learner model, which gets data from a wide range of technologies, including Facebook, Second Life, and MALL, with a view to offering visualisations of language learning competences that can be used to support teachers and learners.

The next three articles investigate the impact of data-driven learning on language development in three very different contexts and languages. Karras focuses on learners of English from an international secondary school in Vietnam, and Wong and Lee on Mandarin speakers learning Cantonese, while Vyatkina looks at low-proficiency learners of German from a university in the United States. Karras’s findings suggest that using DDL in conjunction with online dictionaries leads to improved and sustained vocabulary acquisition. Similar results are found by Wong and Lee in their study of the use of parallel corpora (Mandarin-Cantonese). Finally, Vyatkina’s study shows that the use of concordances was more effective than traditional rule-based activities for teaching German verb-preposition collocation.

This issue concludes with the presentation and discussion of a new scale that can be used to measure learners’ attitudes toward DDL, developed by Mizumoto, Chujo and Yokota. Not only do these authors propose a new instrument that will no doubt be of use to many researchers they also provide us with a solid methodology to develop similar scales in other areas.