Jul 2026· European Journal of Education· Vol 61· 1 citation· 56 references
TL;DR
It is confirmed that AI‐driven instruction substantially improved EFL learners' self‐efficacy, self‐regulation and grit, with the most significant gains observed in self‐efficacy.
Abstract
Incorporating AI into language education has shaped new opportunities to increase learners' psychological resources; however, evidence on how AI‐driven instruction influences key traits such as self‐efficacy, self‐regulation and grit remains limited. To address this gap, the present research examined the effect of an Artificial Intelligence (AI) teaching intervention on these constructs among English as a Foreign Language (EFL) learners. To this end, 123 Chinese EFL learners were selected and assigned to experimental and control groups and received the same syllabus content within 10 weeks. The two groups received the same syllabus material, but the experimental group engaged with an AI Chabot that offered adaptive learning support, customized encouragement and immediate feedback. On the contrary, the control group received conventional teacher‐centred teaching through a traditional context. Pre‐ and post‐intervention assessments measured variations in learners' self‐efficacy, self‐regulation and grit. Results from running one‐way Analysis of Covariance (ANCOVA) indicated that the AI Chabot intervention significantly enhanced learners' psychological traits compared to traditional instruction. Indeed, these findings confirm that AI‐driven instruction substantially improved EFL learners' self‐efficacy, self‐regulation and grit, with the most significant gains observed in self‐efficacy. These results suggest that AI‐driven teaching can serve as an effective tool for strengthening learners' psychological competencies in EFL contexts.
The quick progress of technology, namely Artificial Intelligence (AI), within the language teaching sphere has widened the research domain on learners' educational engagement; however, a research gap remains regarding the basic psychological tools specifically the interaction between non‐cognitive traits through whic...
Yi-Peng Chang· European Journal of Educatio...· 0 citations
With the advent of Artificial Intelligence (AI) in the academic context, the traditional learning settings have been changed to advanced instruments that boost the learners' achievement. A critical factor of learners' achievement in AI‐based settings is Psychological Well‐being (PWB). Nevertheless, detecting the effe...
Yi Wei, Xiang Long· European Journal of Educatio...· 0 citations
Willingness to communicate (WTC) is recognised as a vital element in English as a Foreign Language (EFL) learning; however, developing students' WTC in tertiary education is usually a constant challenge. Likewise, improving students' well‐being and motivation is equally significant as these constructs support bette...
Yang-Yang Mao, Hai-Yan Wu, Jia Li· European Journal of Educatio...· 0 citations
The review synthesizes empirical evidence on learner autonomy, self-regulation, and metacognitive development to identify the pedagogical, technical, cultural, and institutional factors influencing implementation in Arab classrooms and concludes that success hinges on pedagogy and cultural appropriation rather than tec...
Abida Ayesha· Arab World English Journal· 0 citations
Introduction This study investigated the effectiveness of an AI-supported e-mentoring model in enhancing self-efficacy and emotional intelligence among EFL pre-service teachers within the Egyptian practicum context. Methods Using a mixed-methods quasi-experimental design, 50 participants were assigned to an experimenta...
Israa Ismael, Xin Luo, Sen Li· Frontiers in Psychology· 0 citations
Artificial intelligence offers new opportunities for Personalized Adaptive Learning (PAL), an approach that tailors instruction to individual students' needs, pace, and learning styles. Making AI a critical enabler of truly responsive and differentiated teaching. Yet its effective implementation depends on teachers' re...