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Heydarnejad, Tahereh. (1405). Beyond Whiteboard EFL Classrooms: Uncurtaining the Links between AI Self-efficacy, AI Cognitive-emotion Regulation, AI-assisted L2 Learning Attitude, and AI Psychological Flow in Higher Education. , (), -. doi: 10.22077/ali.2025.9448.1152
Tahereh Heydarnejad. "Beyond Whiteboard EFL Classrooms: Uncurtaining the Links between AI Self-efficacy, AI Cognitive-emotion Regulation, AI-assisted L2 Learning Attitude, and AI Psychological Flow in Higher Education". , , , 1405, -. doi: 10.22077/ali.2025.9448.1152
Heydarnejad, Tahereh. (1405). 'Beyond Whiteboard EFL Classrooms: Uncurtaining the Links between AI Self-efficacy, AI Cognitive-emotion Regulation, AI-assisted L2 Learning Attitude, and AI Psychological Flow in Higher Education', , (), pp. -. doi: 10.22077/ali.2025.9448.1152
Heydarnejad, Tahereh. Beyond Whiteboard EFL Classrooms: Uncurtaining the Links between AI Self-efficacy, AI Cognitive-emotion Regulation, AI-assisted L2 Learning Attitude, and AI Psychological Flow in Higher Education. , 1405; (): -. doi: 10.22077/ali.2025.9448.1152

Beyond Whiteboard EFL Classrooms: Uncurtaining the Links between AI Self-efficacy, AI Cognitive-emotion Regulation, AI-assisted L2 Learning Attitude, and AI Psychological Flow in Higher Education

Applied Linguistics Inquiry
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 11 فروردین 1405
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22077/ali.2025.9448.1152
نویسنده
Tahereh Heydarnejad*
Department of English Language, Faculty of Literature and Humanities
چکیده
The incorporation of artificial intelligence (AI) in English as a Foreign Language (EFL) instruction has led to a closer look at how it affects the experiences and outcomes of learners in this field. This study looks at how psychological flow, AI cognitive-emotion regulation, AI-assisted second language (L2) learning attitudes, and AI self-efficacy are related among 318 university students. By applying Structural Equation Modeling (SEM) via AMOS, the study explains how these variables cooperate in order to make the language learning experiences better. The results suggest that a more favorable attitude toward AI-assisted L2 learning is cultivated as a result of the positive impact of higher levels of AI self-efficacy on cognitive-emotion regulation. Additionally, a robust correlation was observed between these attitudes and the experience of psychological flow, indicating that the integration of AI can substantially improve student engagement and overall learning outcomes. The findings also emphasize the importance of cognitive-emotional processes in influencing students' perspectives on AI tools, demonstrating that emotional modulation strategies can alleviate feelings of apprehension and uncertainty, thereby fostering a more optimistic learning environment. Furthermore, the implications of these discoveries for curriculum development and teaching practices are addressed, offering educators valuable insights on how to effectively utilize AI technology.
کلیدواژه‌ها
AI Self-efficacy؛ AI Cognitive-emotion Regulation؛ AI-assisted L2 Learning Attitude؛ AI Psychological Flow؛ Higher Education
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