Integrating AI-Driven Emotional Intelligence in Language Learning Platforms to Improve English Speaking Skills through Real-Time Adaptive Feedback

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Янв. 31, 2025

This groundbreaking study introduces the first-ever integration of emotional intelligence (EI) with artificial in English-speaking instruction through an emotionally adaptive language learning system. Through a mixed-method design, research examined this innovative approach’s impact on speaking proficiency among 40 high school students (aged 15-18) from Varamin County, Iran. The experimental group (n=20) engaged novel “Amazon Alexa-Speak” Speaking Assessment System, featuring AI-driven EI-based real-time feedback; contrast, control received conventional over six sessions following pretest to ensure homogeneity. employed concurrent mixed method collecting quantitative data System and researcher-made perception questionnaire; qualitative came classroom observation checklists semi-structured interviews (n=20), focusing state monitoring anxiety reduction patterns. Statistical analyses revealed significant positive correlation between EI performance (p < 0.05, η2 = 0.42), showing substantially enhanced (F(1,38) 24.63, p 0.05). system’s detection algorithm demonstrated 94% accuracy identifying responding learners’ affective states. presents paradigm shift education technology by introducing first system that simultaneously addresses cognitive aspects acquisition. findings have implications for global market, particularly addressing barriers learning. technology’s scalability cross-cultural applicability make it potentially transformative solution worldwide, opening new avenues intelligent educational development.

Язык: Английский

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Intersections between cognitive‐emotion regulation, critical thinking and academic resilience with academic motivation and autonomy in EFL learners: Contributions of AI‐mediated learning environments

British Educational Research Journal, Год журнала: 2025, Номер unknown

Опубликована: Фев. 24, 2025

Abstract The rapid and pervasive integration of artificial intelligence (AI) technologies into education presents both unprecedented opportunities significant challenges. While AI‐powered tools offer personalised learning experiences access to vast knowledge repositories, their successful implementation hinges on a nuanced understanding how learners' psychological cognitive processes interact within these dynamic environments. This study delved the intricate interplay between cognitive‐emotion regulation, critical thinking, academic resilience, motivation autonomy in cohort English as foreign language (EFL) learners engaged AI‐mediated learning. For this, sample 302 EFL was recruited using stratified random sampling method. data were analysed structural equation modelling confirmatory factor analysis through SMART PLS software. Findings revealed that there correlation regulation among Moreover, results showed thinking existed. Additionally, outcomes indicated resilience significantly correlated with autonomy. These findings underscored by cultivating ability effectively manage emotions, engage inquiry exercise autonomy, educators can empower them navigate complexities AI‐integrated environments, achieve success develop essential skills for lifelong digital age.

Язык: Английский

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

British Educational Research Journal, Год журнала: 2025, Номер unknown

Опубликована: Март 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.

Язык: Английский

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Beyond Voice Recognition: Integrating Alexa’s Emotional Intelligence and ChatGPT’s Language Processing for EFL Learners’ Development and Anxiety Reduction - A Comparative Analysis

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Фев. 11, 2025

This groundbreaking study investigates the integration of Amazon Alexa, an emotionally intelligent AI platform, into English language teaching through adaptive learning system. Using a mixed-methods design, examined impact this innovative platform on speaking skills 40 high school students (aged 16–18) from Varamin County, Iran. The experimental group (n = 20) engaged with Alexa's which provides AI-driven real-time feedback based emotional intelligence (EI); in contrast, control received instruction using ChatGPT-3.5 over eight sessions following pre-test to ensure homogeneity. employed concurrent mixed methods quantitative data collected researcher-developed Speaking Assessment System and Perception Questionnaire; qualitative were derived classroom observation checklists semi-structured interviews 15), focusing state monitoring anxiety reduction patterns. Statistical analyses revealed significant positive correlation between EI-based performance (p < 0.05, η2 0.42), showing significantly improved (F(1,38) 24.63, p 0.05). detection capabilities demonstrated 94% accuracy identifying responding learners' states. represents paradigm shift technology, leveraging address cognitive aspects acquisition simultaneously. findings have implications for global market, particularly addressing barriers learning. platform's scalability cross-cultural applicability make it potentially transformative solution worldwide, opening up new avenues development educational technology.

Язык: Английский

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