Chapter 8
Promoting Spanish L2 pragmatic competence in a virtual
environment
The relationship between processes
and instructional
methods
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.
Article outline
- 1.Introduction
- 1.1Developing pragmatic competence
- 1.2Understanding the design principles that promote pragmatic
competence
- 1.3Affordances and call
- 2.Research question
- 3.Method and materials
- 3.1Consciousness-raising Group (CR)
- 3.2Structured Input Group (SI)
- 4.Procedure
- 5.Analysis
- 5.1Principal components analysis
- 5.2Discriminant analysis
- 5.3Predicting pragmatic gains
- 6.Results
- 6.1Positing a VE affordance usage model
- 6.1.1Macro variable: Exploration
- 6.1.2Macro variable: Input
- 6.1.3Macro variable: Time in area
- 6.1.4Model summary
- 6.2Assessing the VE affordance usage model’s explanatory
potential
- 6.3Testing the VE affordance usage model’s potential for
predicting pragmatic gains in a VE
- 7.Discussion and conclusions
-
Notes
-
References