Generative Artificial Intelligence-Supported Self-Regulated Learning (GenAI-SRL) in L2 Writing: Scale Development, Validation, and Short-Form Construction
Saved in:
| Title: | Generative Artificial Intelligence-Supported Self-Regulated Learning (GenAI-SRL) in L2 Writing: Scale Development, Validation, and Short-Form Construction |
|---|---|
| Language: | English |
| Authors: | Xiaoqi Wang (ORCID |
| Source: | Metacognition and Learning. 2026 21(1). |
| Availability: | Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/ |
| Peer Reviewed: | Y |
| Page Count: | 27 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Reports - Research Tests/Questionnaires |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Artificial Intelligence, Technology Uses in Education, Writing Instruction, Second Language Instruction, English (Second Language), Foreign Countries, Self Management, Learning Strategies, Test Construction, Test Validity, Test Length, Test Reliability, Psychometrics, College Students |
| Geographic Terms: | China |
| DOI: | 10.1007/s11409-026-09481-1 |
| ISSN: | 1556-1623 1556-1631 |
| Abstract: | The integration of generative artificial intelligence (GenAI) into foreign language writing instruction has brought about human-AI co-regulation, in which textual production arises from learner-algorithm interaction. Investigating how learners regulate their writing processes in GenAI-mediated environments becomes necessary because existing self-regulated learning (SRL) frameworks were developed for human-centered teaching methods. These frameworks may not fully capture the regulatory complexities when GenAI affects text production. We examined SRL within GenAI-supported writing contexts through developing a scale for gauging GenAI-supported SRL in writing (GenAI-SRL) by taking into consideration six regulatory dimensions: cognitive, metacognitive, motivational, affective, social-behavioral, and environmental processes. We recruited two independent samples of Chinese English as a foreign language (EFL) learners. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted with Sample one (N = 305) and Sample two (N = 342), respectively, for scale development and validation. EFA revealed a six-factor structure, which CFA further confirmed alongside satisfactory reliability, convergent validity, discriminant validity, criterion validity, and measurement invariance across gender. Ant Colony Optimization (ACO) yielded a 12-item abbreviated form that retained the psychometric properties of the full-length instrument. The study advances SRL theory within GenAI-mediated writing contexts and provides empirical tools for diagnostic and instructional applications. |
| Abstractor: | As Provided |
| Entry Date: | 20260101 |
| Accession Number: | EJ1514821 |
| Database: | ERIC |
Be the first to leave a comment!
