Journal of Universal Computer Science (May 2021)

Mobile Open Social Learning for Languages (MOSL4L)

  • Timothy Read,
  • Agnes Kukulska-Hulme,
  • Elena Barcena,
  • John Traxler

DOI
https://doi.org/10.3897/jucs.67701
Journal volume & issue
Vol. 27, no. 5
pp. 425 – 436

Abstract

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An extensive literature exists on how to help students learn languages. The learning process is particularly challenging since it combines different types of knowledge and skills into a dual process of comprehension and production, using both oral and written modalities. Networked technology has led to the emergence of different types of learning that can be applied to languages. In this article three of these types are highlighted as being particularly useful for language learning, as can be seen by their impact in the literature, namely mobile, open and social learning. After an analysis of each one, a proposal is made to combine them into a single framework called Mobile Open Social Learning for Languages (or MOSL4L). It is subsequently characterized using Activity Theory and some suggestions are made for establishing a rubric that could enable language learning scenarios to be analyzed in terms of the constituent parts that define their nature and enable the causal relations with learning to be highlighted.

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