Applying intelligent personal assistants to develop fluency and comprehensibility, and reduce accentedness in EFL learners: an empirical study of Google Assistant

Considering the contribution of intelligent personal assistant (IPA) platforms to English as a foreign language (EFL) speaking courses and the insufficiency of research in this regard, the current study applied a sequential explanatory mixed-methods approach to explore the impact of Google Assistant, an IPA platform, on EFL learners’ International English Language Testing System (IELTS) speaking test marks and their fluency, comprehensibility, and accentedness. Two intact classes at a language institute were chosen and randomly assigned to an IPA class with 20 EFL learners and a non-IPA class with 23 EFL learners. The IPA learners interactively and individually communicated with Google Assistant by giving commands/requests/questions, and the non-IPA learners communicated the same commands/requests/questions with their peers interactively. The IELTS speaking skill test, the fluency, comprehensibility, and accentedness scales, and an individual semi-structured interview were used to collect the necessary quantitative and qualitative data. One-way between groups analysis of covariance (ANCOVA), applied to analyse the quantitative data, revealed that the IPA and non-IPA speaking instruction developed the EFL learners’ IELTS speaking test marks, fluency, and comprehensibility, and reduced their accentedness. The former (i.e. the IPA instruction) outperformed the latter (i.e. the non-IPA instruction) in developing IELTS speaking test marks and comprehensibility, and reducing accentedness. Thematic analysis, applied to analyse the qualitative data, uncovered several themes and categories that indicated the IPA learners’ positive attitudes and perceptions towards the use of Google Assistant for interactive, one-to-one speaking activities. The findings suggested effective techniques for integrating IPAs into EFL speaking courses to enhance IELTS speaking test marks, fluency, and comprehensibility, and reduce accentedness in EFL learners.

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Publication Details

Journal
Language Teaching Research
Published
2025-02-27
DOI
https://doi.org/10.1177/13621688251317786
Citations
10
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
24.81
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article

Applying intelligent personal assistants to develop fluency and comprehensibility, and reduce accentedness in EFL learners: an empirical study of Google Assistant

Masoud Rahimi, Timothy P. Teo, Jalil Fathi
10 citations
Language Teaching Research
AI in Service Interactions
24.81
article

Applying intelligent personal assistants to develop fluency and comprehensibility, and reduce accentedness in EFL learners: an empirical study of Google Assistant

Masoud Rahimi, Timothy P. Teo, Jalil Fathi
article en
10 citations

Abstract

Considering the contribution of intelligent personal assistant (IPA) platforms to English as a foreign language (EFL) speaking courses and the insufficiency of research in this regard, the current study applied a sequential explanatory mixed-methods approach to explore the impact of Google Assistant, an IPA platform, on EFL learners’ International English Language Testing System (IELTS) speaking test marks and their fluency, comprehensibility, and accentedness. Two intact classes at a language institute were chosen and randomly assigned to an IPA class with 20 EFL learners and a non-IPA class with 23 EFL learners. The IPA learners interactively and individually communicated with Google Assistant by giving commands/requests/questions, and the non-IPA learners communicated the same commands/requests/questions with their peers interactively. The IELTS speaking skill test, the fluency, comprehensibility, and accentedness scales, and an individual semi-structured interview were used to collect the necessary quantitative and qualitative data. One-way between groups analysis of covariance (ANCOVA), applied to analyse the quantitative data, revealed that the IPA and non-IPA speaking instruction developed the EFL learners’ IELTS speaking test marks, fluency, and comprehensibility, and reduced their accentedness. The former (i.e. the IPA instruction) outperformed the latter (i.e. the non-IPA instruction) in developing IELTS speaking test marks and comprehensibility, and reducing accentedness. Thematic analysis, applied to analyse the qualitative data, uncovered several themes and categories that indicated the IPA learners’ positive attitudes and perceptions towards the use of Google Assistant for interactive, one-to-one speaking activities. The findings suggested effective techniques for integrating IPAs into EFL speaking courses to enhance IELTS speaking test marks, fluency, and comprehensibility, and reduce accentedness in EFL learners.

Language Teaching Research
Chinese University of Hong Kong (HK), University of Kurdistan (IR)
Quality Education
Openalex Percentile: Top 1%
AI in Service Interactions
24.81
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