Mobile-assisted pronunciation learning with feedback from peers and/or automatic speech recognition: a mixed-methods study

Abstract

Although social networking apps and dictation-based automatic speech recognition (ASR) are now widely available in mobile phones, relatively little is known about whether and how these technological affordances can contribute to EFL pronunciation learning. The purpose of this study is to investigate the effectiveness of feedback from peers and/or ASR in mobile-assisted pronunciation learning. 84 Chinese EFL university students were assigned into three conditions, using WeChat (a multi-purpose mobile app) for autonomous ASR feedback (the Auto-ASR group), peer feedback (the Co-non-ASR group), or peer plus ASR feedback (the Co-ASR group). Quantitative data included the pronunciation pretest, posttest, and delayed posttest, and students’ perception questionnaires, while qualitative data included students’ interviews. The main findings are: (a) all three groups improved their pronunciation, but the Co-non-ASR and the Co-ASR groups outperformed the Auto-ASR group; (b) the three groups showed no significant difference in perception questionnaires; and (c) the interviews revealed some common and unique technical, social/psychological, and educational affordances and concerns about the three mobile-assisted learning conditions.

Keywords:

• Automatic speech recognition
• mixed methods
• mobile-assisted language learning
• peer feedback
• pronunciation

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 The accuracy of ASR was tested and all words in the eight target sentences could be recognized by the app.

2 For instance, the mean comprehensibility scores of the higher-grade students in the pretest were 7.59 (out of 9), 7.60, and 7.56, respectively in the Co-non-ASR, Co-ASR, and Auto-ASR groups.

Additional information

Funding

The study was funded by China Postdoctoral Science Foundation (2020M683165).

Notes on contributors

Yuanjun Dai

Dr. Yuanjun Dai is a post-doctoral fellow at Jinan University and a lecturer at Xinghai Conservatory of Music. He was an academic visitor at University of Birmingham (2015). His research interests include computer-assisted language learning, lexicography and English for specific purposes.

Zhiwei Wu

Dr. Zhiwei Wu is an assistant professor at The Hong Kong Polytechnic University. He was a visiting scholar at Lancaster University (2014) and the Pennsylvania State University (2016-2017). His research interests include multiliteracies, English for specific purposes, and translation studies.