AI-powered personalized learning: Enhancing self-efficacy, motivation, and digital literacy in adult education through expectancy-value theory DOI
Wenwen Lyu,

Zarina Abdul Salam

Learning and Motivation, Journal Year: 2025, Volume and Issue: 90, P. 102129 - 102129

Published: April 15, 2025

Language: Английский

Modeling the relationship between online L2 motivational self-system and EFL learners’ virtual exchange self-regulations: the mediator and moderator roles of L2 grit DOI Creative Commons
Amir Reza Rahimi, Ana Sevilla‐Pavón

ReCALL, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 20

Published: Feb. 3, 2025

Abstract While previous studies in computer-assisted language learning have extensively explored sociolinguistic factors, such as cultural competence, important psycholinguistic factors online L2 motivational self-system, grit, and self-regulation relation to virtual exchange (VE) remained widely unexplored. To address this gap, a study was conducted with 92 Spanish English foreign learners who exchanged culture Cypriot Irish students responded questionnaires adapted for the context, part of SOCIEMOVE (Socioemotional Skills Through Virtual Exchange) Project. The partial least squares structural equation modeling approach showed that set positive personal goals future evaluate their current progress VE can regulate it. Interestingly, sign authenticity gap found since learners’ motivation learn higher compared contexts, resulting more effort consistency interest setting goals, evaluating progress, asking help from others. Furthermore, grit moderated mediated correlation between self-regulation, indicating success requires long-term perseverance interest. Accordingly, new conceptual framework developed. In addition, one main implications is teachers employ should focus on needs they wish achieve when exchanging information rather than only focusing accomplishments based course syllabus.

Language: Английский

Citations

1

Language learners’ surface, deep, and organizing approaches to ChatGPT-assisted language learning: What contextual, individual, and ChatGPT-related factors contribute? DOI Creative Commons
Amir Reza Rahimi, Zahra Mosalli

Smart Learning Environments, Journal Year: 2025, Volume and Issue: 12(1)

Published: Feb. 6, 2025

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

Language: Английский

Citations

0

Toward the Language MOOC (LMOOC’s) low dropout rate: The control-value theory of persistency in LMOOC (CVTPLMOOC) DOI Creative Commons
Amir Reza Rahimi, Babak Daneshvar Ghorbani

Computers in Human Behavior Reports, Journal Year: 2025, Volume and Issue: 17, P. 100593 - 100593

Published: Feb. 8, 2025

Language: Английский

Citations

0

Empowering creativity and engagement: The impact of generative artificial intelligence usage on Chines EFL students' language learning experience DOI

Abdul Khalique Khoso,

Wang Hong-gang,

Mansoor Ali Darazi

et al.

Computers in Human Behavior Reports, Journal Year: 2025, Volume and Issue: 18, P. 100627 - 100627

Published: March 10, 2025

Language: Английский

Citations

0

Towards a holistic integration of AI in EFL education: A mixed method empirical study DOI Creative Commons
Lihang Guan, John Chi‐Kin Lee, Yue Zhang

et al.

Computers and Education Artificial Intelligence, Journal Year: 2025, Volume and Issue: unknown, P. 100384 - 100384

Published: March 1, 2025

Language: Английский

Citations

0

The role of design thinking skills in artificial-intelligence language learning (DEAILL) in shaping language learners’ L2 grit: the mediator and moderator role of artificial intelligence L2 motivational self-system DOI
Amir Reza Rahimi, Ana Sevilla‐Pavón

Computer Assisted Language Learning, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 49

Published: April 9, 2025

Language: Английский

Citations

0

AI‐assisted learning environments in China: Exploring the intersections of emotion regulation strategies, grit tendencies, self‐compassion, L2 learning experiences and academic demotivation DOI Open Access
Shihai Zhang

British Educational Research Journal, Journal Year: 2025, Volume and Issue: unknown

Published: March 15, 2025

Abstract The increasing integration of artificial intelligence (AI) in education has led to a surge interest AI‐assisted learning environments. These environments offer various advantages, yet deeper understanding their effects on key student‐related constructs the English as foreign language (EFL) context is essential. This study aimed fill this gap by investigating relationships between emotion regulation strategies, grit, self‐compassion, L2 experiences and academic demotivation among Chinese EFL learners AI‐supported settings. A quantitative research design was employed, with 219 students participating through purposive sampling. Data were collected using validated questionnaires measuring five target analysed structural equation modelling. Results revealed that strategies positively associated negatively demotivation. Similarly, grit tendencies demonstrated positive correlations negative Self‐compassion similar patterns, associations findings important pedagogical implications for educators developers AI‐powered platforms China. By influence regulation, self‐compassion learners' motivation, can implement foster these attributes.

Language: Английский

Citations

0

AI-powered personalized learning: Enhancing self-efficacy, motivation, and digital literacy in adult education through expectancy-value theory DOI
Wenwen Lyu,

Zarina Abdul Salam

Learning and Motivation, Journal Year: 2025, Volume and Issue: 90, P. 102129 - 102129

Published: April 15, 2025

Language: Английский

Citations

0