scale-development
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- PaperAssessing Writing14 Jul 2026
Development and evaluation of a student feedback agency scale
Jiaxian Ye, Lawrence Jun Zhang, Helen R. Dixon
Developed and validated a Student Feedback Agency Scale (SFAS) with 23 items across six components, using PCA and CFA on samples of Chinese postgraduate students. The scale shows good psychometric properties and invariance across gender, academic level, and discipline.
Original abstract
Feedback agency is a key concept in enhancing student writing performance. While growing attention has been paid to student feedback agency, existing research remains largely theoretical and qualitative. As a result, there is a lack of psychometrically supported instruments to measure this construct. To address this gap, the present two-phase study aimed to develop and evaluate a Student Feedback Agency Scale (SFAS), drawing on social cognitive theory. In the development stage, Principal Component Analysis (PCA) was conducted on a sample of 235 Chinese international postgraduate students. The results yielded a 23-item SFAS comprising six components: Action Taking, Goal Setting, Processing, Generating, Self-efficacy, and Seeking. Using an independent sample of 349 participants from the same population, Confirmatory Factor Analysis (CFA) was conducted in the evaluation stage. The results supported a good model fit (RMSEA = .055, IFI = .923, TLI = .908, and CFI = .922). Multi-group CFAs further confirmed the structural invariance across gender, academic level, and discipline. Overall, the findings provide psychometric evidence to support the interpretation and use of the SFAS scores to measure student agency in writing feedback processes. Based on these results, the factor structure and subscales of the SFAS are discussed, and implications are outlined.
- PaperJournal of Second Language Writing30 Jun 2026
Measuring self-regulation in student-GenAI collaborative revision of second language writing: Scale development and validation
Ting Zhao, Yan Ding, Zhongbin Hu, Limin Su et al.
The study develops and validates a scale for measuring self-regulation in second language writing when students collaboratively revise with generative AI. It focuses on the metacognitive and regulatory processes involved in human-AI interaction during revision.