Game-based instruction of pragmatics: Learning request-making through perlocutionary effects

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Using the single-group pre-posttest design, this exploratory study examined whether L2 learners of English can learn a speech act by experiencing perlocutionary effects of the act as feedback (observing their interlocutor's reactions to their choice of speech act expressions). Sixty undergraduate English learners at a university in China played a digital game, developed at the researcher's institution, involving 10 hypothetical request-making interactions that took place on a university campus. For each interaction, participants read a brief scenario description and watched a video that depicts that scenario. After watching the video, they were presented with four options of request-making expressions and asked to select the most desirable expression directed to the speaker in each video. Each option was linked to specific reactions depicted by speakers in the videos (perlocutionary effects). After choosing a response, participants were shown a reaction video designed to give feedback on the appropriateness of their selected response. Recognition and production tests were used for pre, post, and delayed posttests to assess participants’ knowledge of targeted request-making forms. Results revealed a significant gain from the pre to immediate posttest in both modalities, but the gain was not retained at delayed posttest. The effect from game-based instruction appeared larger in the production (Cohen's d = 0.83) than in the recognition test (d = 0.45). Participants’ game performance significantly correlated with their test scores.

Original languageEnglish (US)
Pages (from-to)1-18
Number of pages18
JournalLanguage Learning and Technology
Volume27
Issue number1
StatePublished - 2023

Keywords

  • Digital Game
  • Implicit Feedback
  • Pragmatics
  • Speech Acts

ASJC Scopus subject areas

  • Education
  • Language and Linguistics
  • Linguistics and Language
  • Computer Science Applications

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