Navigating elementary EFL speaking skills with generative AI chatbots: Exploring individual and paired interactions

IF 8.9 1区 教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Education Pub Date : 2024-07-09 DOI:10.1016/j.compedu.2024.105112
Tzu-Yu Tai , Howard Hao-Jan Chen
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Abstract

Generative artificial intelligence (GAI) and automatic speech recognition (ASR) have ushered in promising tools for foreign language learning, notably GAI chatbots. This study investigated the impact of GAI chatbots on elementary school English as a foreign language (EFL) learners' speaking skills, focusing on two interaction configurations—individual and paired. Eighty-five elementary school EFL learners participated in a three-week summer program, engaging in daily 45-min interactions with CoolE Bot. The participants were randomly assigned to three groups: (1) individual interaction with CoolE Bot (I-Bot group), (2) paired interaction with CoolE Bot (P-Bot group), and (3) interaction with teachers and peers in a conventional English classroom (No-Bot group). In each class, participants in the Bot group received worksheets with a topic, prompts, and vocabulary to guide their interactions with CoolE Bot, while those in the No-Bot group also received worksheets for comparable activities. Quantitative (English-speaking tests) and qualitative data (semi-structured interviews) were collected and analyzed. Results revealed that the I-Bot and P-Bot groups' post-test speaking skills were significantly higher than those of the No-Bot group. CoolE Bot significantly improved the speaking skills of EFL learners. Both individual and paired interactions with CoolE Bot demonstrated positive effects, with no significant differences between groups. Interviews highlight CoolE Bot's adeptness in coherent interaction, charismatic conversational style with a human-like voice, diverse topic discussions tailored to learners' interests, and supportive functions. The participants found GAI chatbot-assisted EFL speaking enjoyable, motivating, and engaging appreciating its cartoonish, human-like characters, conversational style, and voice. Additionally, CoolE Bot fostered rapport and a supportive environment enhancing learners' confidence and reducing anxiety regarding EFL speaking. Individual interactions encourage personalized engagement and self-directed learning, whereas paired interactions involve social dynamics, shared learning experiences, and mutual resolution of language challenges.

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用生成式人工智能聊天机器人指导初等教育口语技能:探索个体和配对互动
生成人工智能(GAI)和自动语音识别(ASR)为外语学习带来了前景广阔的工具,特别是GAI聊天机器人。本研究调查了 GAI 聊天机器人对小学英语作为外语(EFL)学习者口语技能的影响,重点关注两种互动配置--单独互动和配对互动。85 名小学英语作为外语(EFL)学习者参加了为期三周的暑期项目,每天与 CoolE Bot 进行 45 分钟的互动。参与者被随机分配到三组:(1) 与酷易机器人单独互动(I-Bot 组);(2) 与酷易机器人配对互动(P-Bot 组);(3) 在传统英语课堂上与教师和同学互动(No-Bot 组)。在每节课上,Bot 组的参与者都会收到包含主题、提示和词汇的工作表,用于指导他们与 CoolE Bot 的互动,而 No-Bot 组的参与者也会收到用于类似活动的工作表。我们收集并分析了定量数据(英语测试)和定性数据(半结构式访谈)。结果显示,I-Bot 组和 P-Bot 组在测试后的口语水平明显高于无 Bot 组。CoolE Bot 极大地提高了 EFL 学习者的口语水平。与 CoolE Bot 的个人互动和配对互动都显示出积极的效果,组间差异不明显。访谈突出强调了 CoolE Bot 擅长连贯的互动、具有人类声音魅力的对话风格、针对学习者兴趣的多样化话题讨论以及支持功能。参与者认为,GAI 聊天机器人辅助的 EFL 口语令人愉悦、充满动力、引人入胜,并对其卡通化的人类角色、对话风格和声音表示赞赏。此外,CoolE Bot 还培养了默契和支持性环境,增强了学习者的信心,减少了他们对 EFL 口语的焦虑。个人互动鼓励个性化参与和自主学习,而配对互动则涉及社会动态、共享学习经验和共同解决语言难题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computers & Education
Computers & Education 工程技术-计算机:跨学科应用
CiteScore
27.10
自引率
5.80%
发文量
204
审稿时长
42 days
期刊介绍: Computers & Education seeks to advance understanding of how digital technology can improve education by publishing high-quality research that expands both theory and practice. The journal welcomes research papers exploring the pedagogical applications of digital technology, with a focus broad enough to appeal to the wider education community.
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