Sun Weina
School of Foreign Languages, Changchun Institute of Technology, Changchun, China.
Front Psychol. 2023 Aug 16;14:1210187. doi: 10.3389/fpsyg.2023.1210187. eCollection 2023.
This study employed an explanatory sequential design to examine the impact of utilizing automatic speech recognition technology (ASR) with peer correction on the improvement of second language (L2) pronunciation and speaking skills among English as a Foreign Language (EFL) learners. The aim was to assess whether this approach could be an effective tool for enhancing L2 pronunciation and speaking abilities in comparison to traditional teacher-led feedback and instruction.
A total of 61 intermediate-level Chinese EFL learners were randomly assigned to either a control group (CG) or an experimental group (EG). The CG received conventional teacher-led feedback and instruction, while the EG used ASR technology with peer correction. Data collection involved read-aloud tasks, spontaneous conversations, and IELTS speaking tests to evaluate L2 pronunciation and speaking skills. Additionally, semi-structured interviews were conducted with a subset of the participants to explore their perceptions of the ASR technology and its impact on their language learning experience.
The quantitative analysis of the collected data demonstrated that the EG outperformed the CG in all measures of L2 pronunciation, including accentedness and comprehensibility. Furthermore, the EG exhibited significant improvements in global speaking skill compared to the CG. The qualitative analysis of the interviews revealed that the majority of the participants in the EG found the ASR technology to be beneficial in enhancing their L2 pronunciation and speaking abilities.
The results of this study suggest that the utilization of ASR technology with peer correction can be a potent approach in enhancing L2 pronunciation and speaking skills among EFL learners. The improved performance of the EG compared to the CG in pronunciation and speaking tasks demonstrates the potential of incorporating ASR technology into language learning environments. Additionally, the positive feedback from the participants in the EG underscores the value of using ASR technology as a supportive tool in language learning classrooms.
本研究采用解释性序列设计,以考察利用自动语音识别技术(ASR)并结合同伴纠错对提高作为外语的英语(EFL)学习者的第二语言(L2)发音和口语技能的影响。目的是评估与传统的教师主导反馈和教学相比,这种方法是否可以成为提高L2发音和口语能力的有效工具。
总共61名中级汉语EFL学习者被随机分配到对照组(CG)或实验组(EG)。CG接受传统的教师主导反馈和教学,而EG使用ASR技术并结合同伴纠错。数据收集包括朗读任务、自发对话和雅思口语测试,以评估L2发音和口语技能。此外,还对一部分参与者进行了半结构化访谈,以探讨他们对ASR技术的看法及其对他们语言学习体验的影响。
对收集到的数据进行的定量分析表明,在L2发音的所有指标上,包括口音和可理解性方面,EG的表现均优于CG。此外,与CG相比,EG在整体口语技能方面有显著提高。访谈的定性分析表明,EG中的大多数参与者发现ASR技术有助于提高他们的L2发音和口语能力。
本研究结果表明,利用ASR技术并结合同伴纠错可以成为提高EFL学习者L2发音和口语技能的有效方法。与CG相比,EG在发音和口语任务中的表现有所改善,这表明将ASR技术纳入语言学习环境具有潜力。此外,EG中参与者的积极反馈强调了在语言学习课堂中使用ASR技术作为辅助工具的价值。