Affiliation:
1. Northern Arizona University
Abstract
Virtual Environments (VE) can mimic the myriad dimensions that native speakers take into account in authentic social interactions and are one of the instructional conditions (e.g., methodological approaches, learning affordances) that can be used to promote pragmatic competence. The present study employs big-data techniques to provide a parsimonious and quantifiable model of affordance usage in VEs fostering L2 Spanish learners’ pragmatic abilities. We employ data-reduction analyses to synthesize tracking data that recorded learners’ use of software features within consciousness-raising and structured-input, both involving task-based language teaching (TBLT). The analysis suggests that three macro variables can significantly classify different learning conditions: (i) movement through the VE, (ii) type of interaction with affordances providing input, (iii) time on task.
Publisher
John Benjamins Publishing Company
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