Learning and Motivation, Journal Year: 2025, Volume and Issue: 90, P. 102129 - 102129
Published: April 15, 2025
Language: Английский
Learning and Motivation, Journal Year: 2025, Volume and Issue: 90, P. 102129 - 102129
Published: April 15, 2025
Language: Английский
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
1Smart 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
0Computers in Human Behavior Reports, Journal Year: 2025, Volume and Issue: 17, P. 100593 - 100593
Published: Feb. 8, 2025
Language: Английский
Citations
0Computers in Human Behavior Reports, Journal Year: 2025, Volume and Issue: 18, P. 100627 - 100627
Published: March 10, 2025
Language: Английский
Citations
0Computers and Education Artificial Intelligence, Journal Year: 2025, Volume and Issue: unknown, P. 100384 - 100384
Published: March 1, 2025
Language: Английский
Citations
0Computer Assisted Language Learning, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 49
Published: April 9, 2025
Language: Английский
Citations
0British 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
0Learning and Motivation, Journal Year: 2025, Volume and Issue: 90, P. 102129 - 102129
Published: April 15, 2025
Language: Английский
Citations
0