• Language Learners' Surface...

Treffer: Language Learners' Surface, Deep, and Organizing Approaches to ChatGPT-Assisted Language Learning: What Contextual, Individual, and ChatGPT-Related Factors Contribute?

Title:
Language Learners' Surface, Deep, and Organizing Approaches to ChatGPT-Assisted Language Learning: What Contextual, Individual, and ChatGPT-Related Factors Contribute?
Language:
English
Authors:
Amir Reza Rahimi (ORCID 0000-0003-4963-3442), Zahra Mosalli (ORCID 0000-0001-6175-2976)
Source:
Smart Learning Environments. 2025 12.
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:
24
Publication Date:
2025
Document Type:
Fachzeitschrift Journal Articles<br />Reports - Research
Education Level:
Higher Education
Postsecondary Education
Descriptors:
Second Language Learning, Second Language Instruction, Artificial Intelligence, Technology Uses in Education, Course Descriptions, Context Effect, Instructional Leadership, Technology Integration, Privacy, Feedback (Response), Computer Assisted Instruction, Reliability, Learning Motivation, Individual Characteristics, Teaching Methods, College Students, Universities, Learning Processes, Student Attitudes, Foreign Countries
Geographic Terms:
Iran
DOI:
10.1186/s40561-025-00368-3
ISSN:
2196-7091
Entry Date:
2025
Accession Number:
EJ1460988
Database:
ERIC

Weitere Informationen

Researchers have significantly explored language learners' attitudes toward ChatGPT through the lens of technology acceptance models, particularly with its development and integration into computer-assisted language learning (CALL). However, further research in this area is necessary to apply a theoretical framework with a pedagogical-oriented perspective. Therefore, in this study, the researchers utilized students' approaches to the learning environment (SAL) and extended it by incorporating a multilevel perspective that encompasses contextual, individual, and ChatGPT-related factors. Accordingly, the researchers integrated ChatGPT into their language syllabus and guided learners in three universities in Ardabil City to use ChatGPT during the academic year 2023-2024. In the end, 214 participants answered the study questionnaire. The result of the partial least squares modeling (PLS-SEM), and Importance performance map analysis (IPMA) showed that ChatGPT leadership, where the university executive provides the atmosphere for the norms of ChatGPT integration, could significantly shape language learners' organizing approach to using it in their daily academic schedule. Additionally, personalization and anthropomorphism were among the significant ChatGPT-related factors that shaped learners' deep approach to using ChatGPT as a source for meaningful, cross-referenced CALL tool. However, low feedback reliability, privacy concerns, and the ChatGPT's perceived value contributed to language learners' surface approach to minimizing its use as a ChaGPT-related factor. On the basis of these findings, the study introduces a new conceptual framework for CALL and artificial intelligence language learning (AILL) and suggests that ChatGPT leadership should be promoted at a macro-contextual level that might cover other micro-contextual, personal, and ChatGPT-related factors, including ChatGPT's price-value, personalization, and language learners' motivation, which are important elements to shape learners' approaches to CHAGPTALL.

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