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Generative Artificial Intelligence-Supported Self-Regulated Learning (GenAI-SRL) in L2 Writing: Scale Development, Validation, and Short-Form Construction

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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 0000-0001-6225-9307), Lawrence Jun Zhang (ORCID 0000-0003-1025-1746), Yanan Zhang (ORCID 0009-0000-7445-2964)
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
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  Data: Generative Artificial Intelligence-Supported Self-Regulated Learning (GenAI-SRL) in L2 Writing: Scale Development, Validation, and Short-Form Construction
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  Data: <searchLink fieldCode="AR" term="%22Xiaoqi+Wang%22">Xiaoqi Wang</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0001-6225-9307">0000-0001-6225-9307</externalLink>)<br /><searchLink fieldCode="AR" term="%22Lawrence+Jun+Zhang%22">Lawrence Jun Zhang</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0003-1025-1746">0000-0003-1025-1746</externalLink>)<br /><searchLink fieldCode="AR" term="%22Yanan+Zhang%22">Yanan Zhang</searchLink> (ORCID <externalLink term="http://orcid.org/0009-0000-7445-2964">0009-0000-7445-2964</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Metacognition+and+Learning%22"><i>Metacognition and Learning</i></searchLink>. 2026 21(1).
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  Data: 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/
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  Data: 27
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  Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink>
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  Data: 10.1007/s11409-026-09481-1
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  Data: 1556-1623<br />1556-1631
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  Data: 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.
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      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Technology Uses in Education
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      – SubjectFull: Writing Instruction
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      – SubjectFull: China
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      – TitleFull: Generative Artificial Intelligence-Supported Self-Regulated Learning (GenAI-SRL) in L2 Writing: Scale Development, Validation, and Short-Form Construction
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