人工智能辅助L2写作的认知负载量表:量表的开发和验证
Guangyuan Yao1, Lingxi Fan2,3
1Department of English, University of Macau, Taipa, Macao SAR, China.
Frontiers in psychology
|November 17, 2025
概括
研究人员开发了人工智能辅助L2写作认知负载量表 (CL-AI-L2W),以测量人类-人工智能写作中的认知需求. 这种经过验证的尺度有助于对AI的理解.
科学领域:
- 教育心理学教育心理学
- 应用语言学 应用语言学
- 人与计算机的交互
背景情况:
- 生成性人工智能越来越多地被整合到第二语言 (L2) 写作中.
- 了解与人工智能辅助的L2写作相关的认知负载对于有效的教学和理论发展至关重要.
- 现有的工具并没有专门解决人类-人工智能协作写作的独特认知需求.
研究的目的:
- 开发和验证人工智能辅助L2写作 (CL-AI-L2W) 的认知负载量表.
- 用人工智能工具测量L2作家使用人工智能工具所经历的独特认知负载维度.
- 在AI增强的写作环境中为研究和教育实践提供心理测量健全的工具.
主要方法:
- 一种混合方法的方法,整合了认知写作理论和人类-人工智能交互研究.
- 通过专家反和采访来改进项目库.
- 探索性因子分析 (N=241) 和确认性因子分析 (N=305) 以确定尺度结构和有效性.
主要成果:
- 一个经过验证的18项CL-AI-L2W规模,具有强大的四个因素结构:即时管理,关键评估,整合合成和作者核心处理.
- 该比例表显示出出色的内部一致性和强大的标准相关有效性.
- 在尺度和写作焦虑,自我效能以及感知到的精神努力之间发现了显著的相关性.
结论:
- CL-AI-L2W是第一个测量人工智能辅助L2写作的认知负载的验证仪器.
- 该尺度为评估AI对L2组成的认知影响提供了可靠的工具.
- 结果可以为开发有效的教学策略和AI集成L2写作指令的理论框架提供信息.
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