Web-based intonation training helps improve ESL and EFL Chinese students' oral speech

语调(语言学) 普通话 计算机科学 积极倾听 发音 语言学 流利 心理学 质量(理念) 压力(语言学) 数学教育 语音识别 沟通 哲学 认识论
作者
Yan Jiang,Dorothy M. Chun
出处
期刊:Computer Assisted Language Learning [Routledge]
卷期号:36 (3): 457-485 被引量:24
标识
DOI:10.1080/09588221.2021.1931342
摘要

This paper examines whether a web-based training on English discourse intonation leads to better spontaneous speech quality for Mandarin Chinese speakers who reside in the U.S. and in China. The four-week fully online training consisted of meta-instruction videos as well as listening and speaking activities, including instant visual pitch contour feedback and individualized evaluation. The students gave a one-minute spontaneous speech on a given topic at the beginning and the end of the study via videoconferencing. Four native English speakers judged the students' speech comprehensibility, fluidity, accent, confidence and attractiveness, in addition to their intonation performance. Two-way ANCOVA test results show that the experimental group made statistically significant improvement in their speech comprehensibility and speaking confidence. In contrast, the control group did not show improvement. The participants' residence in the U.S. or in China did not affect the training effects. There was not an interaction between the participants' residence and the training. The web-based training, visualization and CMC technology provided an effective scaffolding experience and benefited both EFL and ESL students equally. This study also explores Chinese students' challenges with specific intonation features based on both the raters' judgments and the learners' self-evaluations. The results suggest they have more difficulties with thought groups and prominence than with tone choices. While the trainees gave high ratings to all the activities, they preferred individualized evaluation from the researcher to self-created visual feedback using Praat. The findings have implications for Chinese L1-specific intonation instruction and developing web-based computer assisted pronunciation training systems.
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