Enhancing online language learning as a tool to boost employability

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© 2017 Sol Escobar, Susanne Krauß.


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Abstract

Online learning is a very flexible way to build and improve language knowledge alongside other work and/or study commitments whilst at the same time encouraging autonomous learning, time management, self-motivation and other skills relevant to employability. Learning on your own, however, can also be daunting. Therefore, the Languages for All (LfA) team at the University of Essex have incorporated an innovative blend of tutor support with flexible tailored lessons and bespoke assessments in addition to the Rosetta Stone® Advantage (RSA) programme which is used as the main platform. This combination has contributed to a steep increase in retention and pass rates, placing our modules in an advantageous position. The article presents an innovative (and easily replicable) module structure and − supported by students’ voices − shows how learning a language can contribute to enhancing employability.

Keywords: online language learning, employability, eLearning, language learning software, technology enhanced learning, IWLP, independent learning.

References

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Gallagher-Brett, A. (2004). Seven hundred reasons for studying languages. LLAS. https://www.llas.ac.uk/sites/default/files/nodes/6063/700_reasons.pdf

Higher Education Academy. (2016). Framework for embedding employability in higher education. https://www.heacademy.ac.uk/enhancement/frameworks/framework-embedding-employability-higher-education

Quality Assurance Agency. (2012) Enterprise and entrepreneurship education: guidance for UK higher education providers. http://www.qaa.ac.uk/en/Publications/Documents/enterprise-entrepreneurship-guidance.pdf

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Escobar, Sol; Krauß, Susanne. (2017). Enhancing online language learning as a tool to boost employability. In Carmen Álvarez-Mayo, Angela Gallagher-Brett, Franck Michel (Eds), Innovative language teaching and learning at university: enhancing employability (pp. 127-135). Research-publishing.net. https://doi.org/10.14705/rpnet.2017.innoconf2016.662

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