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Mobile application-based phonetic training facilitates Chinese-English learners’ learning of L2

  • Juan Yang
  • , Yangyang Li
  • , Ling Wang*
  • , Bo Sun
  • , Jiajia He
  • , Zhijie Liang
  • , Daifa Wang*
  • *此作品的通讯作者
  • Sichuan Normal University

科研成果: 期刊稿件文章同行评审

摘要

Background: Numerous studies have claimed that high variability phonetic training (HVPT) has significant efficacy in improving learners’ phonological decoding ability. Although mobile learning (ML) based HVPT program integrated with sound instructional design also demonstrated the effectiveness, its reliability and validity need to be further verified. Aims: This study evaluated the training's efficacy in improving Chinese learners' perception and production of English words by comparing learners' brain activation changes and network connectivity changes because of the training. Samples: Participants were 40 undergraduate students. Methods: This study developed a Wechat application to implement a self-regulated high-variability-phonetic-training (HVPT) for 20 university students; employed a modified phonics screening test (MPST) as a benchmark test to assess learners’ phonetic decoding ability before and after the training; designed a quasi-experiment (control/experimental design) for 40 participants; most importantly, this study used a functional near infrared spectroscopy (fNIRS) device to monitor brain activation and networks synchronisation for participants in both groups before and after training. Results: The results showed that learners' performance on 5-phoneme pseudowords was significantly improved. The training inhibited learners’ right fusiform gyrus. A significant correlation was observed between enhanced RMTG and increased testing scores. Conclusion: The transfer effect of Mobile MVPT on long pseudowords is significant, suggesting its efficacy in helping learners apply the phonetic patterns perceived from the training to segmentally analyse new difficult words.

源语言英语
文章编号101967
期刊Learning and Instruction
93
DOI
出版状态已出版 - 10月 2024

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