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The effects of pre-task planning on EFL learners’ oral performance in a 3D multi-user virtual environment
Published online by Cambridge University Press: 18 February 2020
Abstract
Prior research on pre-task planning examines its effects on the quality of second language (L2) learners’ planned output. Planning mitigates the cognitive overload placed upon L2 learners’ oral performance, thus improving language production. Despite the pedagogical benefits, studies on pre-task planning on L2 learners’ oral output are conducted mostly in a lab or class setting. Whether or not similar effects of pre-task planning can be evidenced in three-dimensional (3D) multi-user virtual environments (MUVEs), such as Second Life (SL), is still less explored. Hence, this study investigates whether pre-task planning could enhance the quality and quantity of English as a foreign language (EFL) learners’ task-oriented, voice-based outcomes in SL. Nine EFL learners worldwide participated in this 10-session virtual class. Data were collected through students’ oral presentations in performing real-life simulated tasks related to their home cultures and interests. Yuan and Ellis’s (2003) framework of T-units measures was adopted to analyze their linguistic performance measured by complexity and accuracy. Results indicated that EFL learners showed statistically significant improvement on grammatical complexity on the levels of syntactic complexity and variety (but not on lexical variety) and on linguistic accuracy across all measured levels (error-free clauses/T-units/verb forms). It is suggested that pre-task planning can be seeded in task-based instruction either in a classroom-based or 3D MUVE setting to optimize the quality of learners’ linguistic performance. Tasks that are real-world oriented and targeting learners’ cultural repertoires and world knowledge also positively impact their virtual learning experiences. These significant implications add new research and pedagogical dimensions to the field of computer-assisted language learning.
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- © European Association for Computer Assisted Language Learning 2020
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