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

Document Type : Original Article

Author

Department of English Language, Faculty of Literature and Humanities

10.22077/ali.2025.9448.1152

Abstract

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.

Keywords



Articles in Press, Accepted Manuscript
Available Online from 31 March 2026
  • Receive Date: 21 May 2025
  • Revise Date: 03 September 2025
  • Accept Date: 15 October 2025