How Ai Agents Transform Reflective Practices: A Three-Semester Comparative Study in Socially Shared Regulation of Learning DOI

Yumin Zheng,

Fengjiao Tu,

Fengfang Shu

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

An AI Chatbot for EFL Writing: Students’ Usage Tendencies, Writing Performance, and Perceptions DOI

Thi-Ngoc-Anh Duong,

Hsiu‐Ling Chen

Journal of Educational Computing Research, Год журнала: 2025, Номер unknown

Опубликована: Янв. 10, 2025

Writing plays a crucial role in the development of English as Foreign Language (EFL) learners’ language; however, it remains challenging skill for them to acquire. This study investigated how EFL students at high school Northern Vietnam engaged with Assistant Bot (WAB), an artificial intelligence (AI) chatbot designed support their writing practice home. Focusing on students’ usage patterns, performance, and perceptions, research included 47 participants, categorized into higher lower proficiency levels. The mixed-method approach was employed, chat logs, timed-writing tests, questionnaires, semi-structured interviews. findings indicated differences between two levels various stages, despite similarities focus specific aspects. Lower-level learners predominantly utilized during Planning stage generate vocabulary brainstorm ideas, while higher-level mainly used Translating elaborate ideas refine language diverse coherent expression. significantly enhanced performance across all aspects: content, organization, vocabulary, use, mechanics, both Students perceived useful easy-to-use tool.

Язык: Английский

Процитировано

0

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

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

Опубликована: Янв. 31, 2025

Abstract 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

Процитировано

0

Parental acceptance of novel children's medical syringes and their influencing factors DOI Creative Commons
Shanhong Luo, Peng Yang

Frontiers in Psychology, Год журнала: 2025, Номер 16

Опубликована: Март 11, 2025

Background With the rising global demand for medical syringes among children, unsuitability of traditional may negatively affect their physical and mental health. Methods This study integrates extended Technology Acceptance Model (TAM) to survey 455 child guardians on 10 variables influencing attitudes toward pediatric syringes. Results indicate that aesthetic preferences users significantly influence price value sensitivity purchasing decisions children's guardians. Furthermore, product's function shape users' behavioral intentions. anxiety time error reduction emerge as key factors perceived risks. Conclusions offers product designers crucial insights into products, aims enhance development iteration efficiency, promotes more accurate innovation, decision-making, communication. Additionally, it proposes new recommendations ethical marketing strategies.

Язык: Английский

Процитировано

0

Exploring ChatGPT as a virtual tutor: A multi-dimensional analysis of large language models in academic support DOI
Abdullah Al-Abri

Education and Information Technologies, Год журнала: 2025, Номер unknown

Опубликована: Март 12, 2025

Язык: Английский

Процитировано

0

Examining the Effect of Artificial Intelligence in Relation to Students’ Academic Achievement in Classroom: A Meta-Analysis DOI Creative Commons
Liu Dong, Xiuxiu Tang,

Xiyu Wang

и другие.

Computers and Education Artificial Intelligence, Год журнала: 2025, Номер unknown, С. 100400 - 100400

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

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

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

Опубликована: Фев. 11, 2025

Abstract 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

Процитировано

0

How Ai Agents Transform Reflective Practices: A Three-Semester Comparative Study in Socially Shared Regulation of Learning DOI

Yumin Zheng,

Fengjiao Tu,

Fengfang Shu

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0