认知
比例(比率)
心理学
验证性因素分析
认知负荷
探索性因素分析
认知心理学
生成语法
度量(数据仓库)
一致性(知识库)
内部一致性
心理测量学
计算机科学
自然语言处理
认知科学
芯(光纤)
人工智能
生成模型
认知模型
结构效度
项目反应理论
项目分析
协议分析
元认知
测试有效性
认知发展
作者
Guangyuan Yao,Liang Fan
标识
DOI:10.3389/fpsyg.2025.1666974
摘要
This study developed and validated the Cognitive Load Scale for AI-assisted L2 Writing (CL-AI-L2W), an instrument designed to measure the unique cognitive demands of human-AI collaborative writing. As generative AI becomes integral to second language (L2) composition, understanding its impact on cognitive processes is critical. Using a mixed-methods approach grounded in cognitive writing theory and human-AI interaction research, an initial item pool was refined through expert feedback and interviews. An Exploratory Factor Analysis ( N = 241) on a 35-item draft scale revealed a four-factor structure. A subsequent Confirmatory Factor Analysis ( N = 305) confirmed this structure with excellent model fit. The final 18-item scale measures four distinct dimensions of cognitive load: (1) Prompt Management, (2) Critical Evaluation, (3) Integrative Synthesis, and (4) Authorial Core Processing. The scale demonstrated excellent internal consistency and strong criterion-related validity through significant correlations with writing anxiety, self-efficacy, and perceived mental effort. As the first validated instrument of its kind, the CL-AI-L2W offers a crucial tool for advancing writing theory and informing pedagogy in AI-enhanced learning environments.
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