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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The Impact of Artificial Intelligence on Communication Dynamics and Performance in Organizational Leadership

Administrative Sciences, Год журнала: 2025, Номер 15(2), С. 33 - 33

Опубликована: Янв. 23, 2025

This study explores the impact of artificial intelligence (AI)-based technologies on leadership-based organizational communication and employee performance within contemporary workplaces. While prior research has acknowledged AI’s potential in optimizing processes, significant gaps remain understanding its specific influence core dimensions outcomes. addresses these by examining six key elements—informing, message reception, feedback, acceptance, persuasion, reaction—to assess whether AI significantly enhance improving internal efficiency reducing transmission errors, which are crucial for productive interactions. Using a quantitative approach, data were collected via self-administered questionnaire from 203 employees major Romanian food industry company operating globally, including leaders three Eastern European countries. Partial least squares structural equation modeling (PLS-SEM) was employed to analyze relationships between performance. The findings revealed that informing, receiving, accepting messages, along with reaction-provoking, had strong positive effects performance, while feedback persuasion showed moderate impacts. These results emphasize transformative role flow positively influencing behavior, thereby enhancing productivity efficiency. contributes growing body literature situating AI-driven broader context, offering actionable insights managers aiming integrate ethically effectively. Additionally, it offers set recommendations lead process according new actual era digitization, is real benefits both parts. It also provides robust foundation future research, encouraging longitudinal cross-cultural studies further investigate implications diversity, innovation, well-being.

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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