Digital innovations in L2 motivation: harnessing the power of the Ideal L2 Self

Adolphs, Svenja, Clark, Leigh, Dörnyei, Zoltán, Glover, Tony, Henry, Alastair, Muir, Christine, Sánchez-Lozano, Enrique and Valstar, Michel (2018) Digital innovations in L2 motivation: harnessing the power of the Ideal L2 Self. System . ISSN 0346-251X

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Abstract

Sustained motivation is crucial to learning a second language (L2), and one way to support this can be through the mental visualisation of ideal L2 selves (Dörnyei & Kubanyiova, 2014). This paper reports on an exploratory study which investigated the possibility of using technology to create representations of language learners’ ideal L2 selves digitally. Nine Chinese learners of L2 English were invited to three semi-structured interviews to discuss their ideal L2 selves and their future language goals, as well as their opinions on several different technological approaches to representing their ideal L2 selves. Three approaches were shown to participants: (a) 2D and 3D animations, (b) Facial Overlay, and (c) Facial Mask. Within these, several iterations were also included (e.g. with/without background or context). Results indicate that 3D animation currently offers the best approach in terms of realism and animation of facial features, and improvements to Facial Overlay could lead to beneficial results in the future. Approaches using the 2D animations and the Facial Mask approach appeared to have little future potential. The descriptive details of learners’ ideal L2 selves also provide preliminary directions for the development of content that might be included in future technology-based interventions.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/947658
Keywords: motivation ; ideal self ; digital animation ; avatar ; computer-assisted language learning
Schools/Departments: University of Nottingham, UK > Faculty of Arts > School of English
University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number: https://doi.org/10.1016/j.system.2018.07.014
Depositing User: Eprints, Support
Date Deposited: 26 Jul 2018 13:42
Last Modified: 04 May 2020 19:47
URI: https://eprints.nottingham.ac.uk/id/eprint/53166

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