Cognitive load scale for AI-assisted L2 writing: scale development and validation
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 (<i>N</i> = 241) on a 35-item draft scale revealed a four-factor structure. A subsequent Confirmatory Factor Analysis (<i>N</i> = 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.
Authors
- Liang Fan
- Guangyuan Yao (ORCID: https://orcid.org/0009-0000-9123-1696)
Institutions
- Hong Kong Polytechnic University (HK)
- University of Macau (MO)
- Beihang University (CN)
Publication Details
- Journal
- Frontiers in Psychology
- Published
- 2025-10-30
- DOI
- https://doi.org/10.3389/fpsyg.2025.1666974
- Citations
- 1
- Primary Topic
- Second Language Acquisition and Learning
- Type
- article
- Field-Weighted Citation Impact
- 3.44