Using AR filters in L2 pronunciation training: practice, perfection, and willingness to share

Abstract

Traditional L2 pronunciation teaching puts too much emphasis on explicit phonological knowledge (‘knowing that’) rather than on procedural knowledge (‘knowing how’). The advancement of mobile-assisted language learning (MALL) offers new opportunities for L2 learners to proceduralize their declarative articulatory knowledge into production skills more efficiently through systematic practice. Within the framework of skill acquisition theory, and using a mixed-methods design including production tests, articulatory awareness quizzes, and a semi-structured interview, this study aims to investigate the effectiveness of using an augmented reality (AR) filter app during pronunciation practice to improve Chinese L2 students’ segmental production and articulatory awareness of the targeted English consonants (dark/É«/,/ð/and/θ/), and their attitudes towards this application. The experimental results indicate that the app with AR technology, facial detection technology, and digital zoom technology played a positive role in promoting students’ segmental production and raising their articulatory awareness. The interview results show that the AR filter helped to alleviate the learners’ speaking anxiety and embarrassment related to interacting with the teacher for corrective feedback, and encouraged daily practice by providing more fun. Combining all the qualitative and quantitative results, we conclude that an AR filter app can offer academic, psychological, and social support for L2 pronunciation skill learning.

Keywords:

• AR filter
• L2 pronunciation training
• mobile-assisted language learning
• articulatory awareness
• skill acquisition

Acknowledgments

We are indebted to the research participants who generously shared their ideas and experiences with us. We would also like to thank the anonymous reviewers for comments on an earlier version of this paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the [College Students’ Innovative Entrepreneurial Training Plan Program] under grant [2021120142].

Notes on contributors

Jingjing Zhu

Jingjing Zhu is a student at School of Foreign Studies, Shanghai University of Finance and Economics, the People’s Republic of China. Her research interests include phonetics and the use of mobile technologies in L2 pronunciation learning and teaching.

Xi Zhang

Xi Zhang is a student at School of Foreign Studies, Shanghai University of Finance and Economics, the People’s Republic of China. Her research focuses on statistical analysis and computer-assisted language learning.

Jian Li

Jian Li is an associate professor at School of Foreign Studies, Shanghai University of Finance and Economics, the People’s Republic of China. She conducts research on the effects of mobile-assisted technology (e.g., digital zoom, games, AR, online videoconference) on L2 pronunciation learning and teaching. She is a member of Pronunciation Teaching and Phonetic Research Council of China Association for Comparative Studies of English and Chinese.