The use of computer-delivered structured tasks in pragmatic instruction: An exploratory study

Abstract

This study examines the effect of oral practice via computer-delivered structured tasks (CASTs) with native speaker (NS) models and open-ended tasks without NS input (i.e., learner-leaner role-plays) on pragmatic development of second language learners. While prior studies have indicated that structured tasks afford more opportunities for focus on form (FonF) than open-ended tasks (Lee and VanPatten 2003;Lyster 2004;Ranta and Lyster 2007;Skehan and Foster 1999; Tavakoli and Foster 2011), differences between these tasks in pragmatic instruction (PI) have not been examined. Additionally, the effect of practice has been widely examined with regard to oral development, but much less so for pragmatics (e.g., Li 2013; Takimoto 2012a). In this study, one group of ESL learners practiced request speech acts via CASTs, and another group did so via learner-learner open role-plays. Qualitative analysis of participants' output during practice suggests that rehearsal via CASTs promotes FonF and incorporation of NS models into learners' speech, while rehearsal via role-plays results in more creative, but often pragmatically inappropriate, language and content. Additionally, role-plays, but not CASTs, appear to be conducive to humorous language play, metapragmatic discussions, and extended turns similar to those in naturalistic interactions. The study offers insights regarding task types in PI.

Refining pragmatically-appropriate oral communication via computer-simulated conversations

“…Studies examining structured practice of pragmatic routines found that learners could focus on both linguistic form and the content of their responses (Sydorenko, 2015;Sydorenko & Tuason, 2016). We thus categorized changes made into two categories: form or content.…”

“…First, responses to an interlocutor in a particular situation can be practiced an unlimited number of times: oral rehearsal alone, without any feedback, can lead to improvements in fluency, accuracy, and complexity (see Ellis, 2009). Second, as previous research indicates (Sydorenko, 2015;Sydorenko & Tuason, 2016), language learners can incorporate model input from expert speakers into their production, and do so simultaneously during their interaction with expert speakers. Thus, it was envisioned that similar input incorporation may take place as learners use SimCon.…”

“…The postulated learning mechanism at play is that learners notice gaps in their production as compared to that of more expert interlocutors (Gass & Mackey, 2015). During repeated practice, learners may notice gaps in their communicative inventory on their own (Sydorenko, 2015;Sydorenko & Tuason, 2016), but feedback in the form of positive or negative consequences and ideas for possible next actions available in SimCon may draw learners' attention to additional gaps (see Methodology section for more details). The need for feedback during contextualized oral practice is explained by Lyster and Sato (2013) as follows: 'repeated practice with feedback at propitious moments promotes the acceleration of meaningful learning rather than the acquisition of mechanical skill (Anderson, Greeno, Kline, & Neves, 1981: 206) and thereby contributes to automatization ' (p. 72).…”

“…Cohen, 2005;Mart ınez-Flor & Us o-Juan, 2006;Olshtain & Cohen, 1991). Of these, the practice component, and in particular oral practice, has received the least attention in research studies (Taguchi & Sykes, 2013; see Sydorenko, 2015, for a review). The current study contributes to this limited knowledge base and supports the argument that opportunities for oral practice of pragmatics facilitate achieving automatized and fluent production (DeKeyser, 2007;Segalowitz, 2003).…”

Discussing with a computer to practice a foreign language: research synthesis and conceptual framework of dialogue-based CALL

“…A recent study, comparing an oral role playing activity (between a learner and a native speaker) with an application letting the students answer orally after a video prompt, also provides an interesting insight: the dialogue-based CALL users were paying stronger attention to form, even with spoken interactions (Sydorenko, 2015). The researcher observed more signs of uptake in the computer program, as learners were incorporating sequences and strategies from the input into their speech, and accuracy was improving across iterations.…”