基于大型语言模型的聊天机器人对第二语言词汇获取的影响
Zhihui Zhang1, Xiaomeng Huang2
1Rossier School of Education, University of Southern California, 3551 Trousdale Pkwy, Los Angeles, CA, 90089, USA.
Heliyon
|February 9, 2024
概括
由大型语言模型 (LLM) 驱动的AI聊天机器人显著改善了外语词汇的获取和保留. 这些工具增强了对长期学习的接受性和生产性语言技能.
科学领域:
- 教育技术的教育技术
- 应用语言学 应用语言学
- 人工智能的人工智能
背景情况:
- 个性化语言学习 (PLL) 越来越多地整合了人工智能 (AI) 和机器学习 (ML).
- 大型语言模型 (LLM) 显示了自动化和增强教育任务的潜力,特别是在语言学习中.
- 聊天机器人为个人学习者需求提供量身定制的干预措施.
研究的目的:
- 研究基于LLM的AI聊天机器人对外语词汇获取的影响.
- 评估基于LLM的工具在增强接受和生产词汇知识方面的有效性.
- 评估人工智能聊天机器人促进的长期保留和偶然的词汇学习.
主要方法:
- 一项涉及52名外语学生的研究分为两组:一个使用基于LLM的聊天机器人,一个控制组.
- 一个为期八周的学习期,专注于两个群体的目标词汇的获取.
- 治疗后的评估,包括系统的观察和定量测试,以测试接收和生产词汇知识,并进行后续测试.
主要成果:
- 使用人工智能聊天机器人的学生在获得接受性和生产性词汇知识方面取得了显著的改善.
- 基于LLM的聊天机器人被发现可以提高生产性词汇的长期保留.
- 在学习过程中使用AI聊天机器人促进了偶然的词汇学习.
结论:
- 使用LLM的AI聊天机器人是支持第二语言词汇发展的有效工具.
- 教师应该考虑基于LLM的技术在L2词汇教学中的潜力.
- 人工智能工具的战略整合可以提高语言学习成果和词汇保留.
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