How Can ChatGPT Open Promising Avenues for L2 Development? A Phenomenological Study Involving EFL University Students in Iran

Computers in Human Behavior Reports, Год журнала: 2024, Номер 16, С. 100510 - 100510

Опубликована: Окт. 18, 2024

Язык: Английский

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Fostering Engagement in AI‐Mediate Chinese EFL Classrooms: The Role of Classroom Climate, AI Literacy, and Resilience

European Journal of Education, Год журнала: 2024, Номер unknown

Опубликована: Дек. 13, 2024

ABSTRACT The rise of artificial intelligence (AI) has significantly impacted education, yet few scholars have explored AI‐assisted classrooms, particularly in language education China. Understanding the roles classroom climate, AI literacy, and resilience is essential, as these factors foster positive learning environments enhance student engagement. In this sense, study, grounded Social Cognitive Theory, employs structural equation modelling to investigate influencing engagement Chinese English a Foreign Language (EFL) classrooms. It examines data from 606 university EFL learners explore interactions among variables mediating role resilience. findings indicate that all predict engagement, highlighting importance both environmental cognitive fostering active participation. Furthermore, serves crucial mediator, linking climate literacy This study provides some insights for educators policymakers, emphasising need cultivate supportive environments, promote programs, strengthen students' optimise educational settings.

Язык: Английский

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Poe or Gemini for fostering writing skills in Japanese upper‐intermediate learners: Uncovering the consequences on positive emotions, boredom to write, academic self‐efficacy and writing development

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

Опубликована: Янв. 15, 2025

Abstract The integration of AI‐based platforms, such as Poe and Gemini, into language instruction has garnered increasing attention for their potential to enhance writing skills. Despite this interest, little is known about effects on EFL learners' positive emotions (PEs), academic self‐efficacy boredom in writing. Addressing gap, the present study investigated effectiveness Gemini developing skills explored impact PEs, among learners at upper‐intermediate level. For purpose, a total 519 Japanese were randomly assigned three groups: (1) Poe‐assisted instruction; (2) Gemini‐assisted (3) control group (CG) receiving traditional instruction. employed mixed‐methods design, incorporating both quantitative qualitative data collection. Writing development was assessed through pre‐ post‐tests, while emotions, measured using validated scales. Additionally, gathered interviews analysed coding thematic analysis understand attitudes perceptions. Quantitative ANOVA MANOVA compare outcomes across groups. findings revealed that significantly improved compared CG, with no substantial differences between two platforms. Participants groups reported heightened PEs increased self‐efficacy, alongside reduced during tasks. corroborated these results, highlighting platforms' role fostering greater enthusiasm, engagement, autonomy motivation English learning. concludes by offering range implications different stakeholders.

Язык: Английский

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Language learners’ surface, deep, and organizing approaches to ChatGPT-assisted language learning: What contextual, individual, and ChatGPT-related factors contribute?

Smart Learning Environments, Год журнала: 2025, Номер 12(1)

Опубликована: Фев. 6, 2025

Abstract Researchers have significantly explored language learners' attitudes toward ChatGPT through the lens of technology acceptance models, particularly with its development and integration into computer-assisted learning (CALL). However, further research in this area is necessary to apply a theoretical framework pedagogical-oriented perspective. Therefore, study, researchers utilized students' approaches environment (SAL) extended it by incorporating multilevel perspective that encompasses contextual, individual, ChatGPT-related factors. Accordingly, integrated their syllabus guided learners three universities Ardabil City use during academic year 2023–2024. In end, 214 participants answered study questionnaire. The result partial least squares modeling (PLS-SEM), Importance performance map analysis (IPMA) showed leadership, where university executive provides atmosphere for norms integration, could shape learners’ organizing approach using daily schedule. Additionally, personalization anthropomorphism were among significant factors shaped deep as source meaningful, cross-referenced CALL tool. low feedback reliability, privacy concerns, ChatGPT's perceived value contributed surface minimizing ChaGPT-related factor. On basis these findings, introduces new conceptual artificial intelligence (AILL) suggests leadership should be promoted at macro-contextual level might cover other micro-contextual, personal, factors, including price-value, personalization, motivation, which are important elements CHAGPTALL.

Язык: Английский

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Tracing interpersonal emotion regulation, behavioural emotion regulation strategies, hopelessness and vocabulary retention within Bing vs. ChatGPT environments

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

Опубликована: Фев. 11, 2025

Abstract Despite the growing integration of artificial intelligence (AI) in language education, limited research has explored its impact on emotional regulation and vocabulary retention, particularly English as a foreign (EFL) contexts. This study addressed this gap by comparing effects Bing ChatGPT environments interpersonal emotion (IER), behavioural strategies (BERS), hopelessness retention among 458 upper‐intermediate Chinese EFL learners. Participants were divided into three groups: Bing, control group (CG) receiving traditional instruction. Both AI‐supported groups engaged with identical content tasks their respective platforms, while CG followed conventional curriculum. A mixed‐methods design was employed, incorporating quantitative pre‐ post‐tests qualitative semi‐structured interviews. The one‐way ANOVA results revealed that both AI significantly outperformed across all measures, no statistical difference between groups. learners conditions reported reduced improved IER BERS, alongside notable retention. In agreement results, findings highlighted engaging supportive nature environments, which led to IER, BERS These suggest integrating tools like classrooms can enhance well‐being acquisition, offering valuable pedagogical insights for educators seeking leverage technology

Язык: Английский

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Unboxing the intersections between self‐esteem and academic mindfulness with test emotions, psychological wellness and academic achievement in artificial intelligence‐supported learning environments: Evidence from English as a foreign language learners

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

Опубликована: Фев. 22, 2025

Abstract The integration of artificial intelligence (AI) into language education is rapidly transforming English as a foreign (EFL) learning environments, presenting both opportunities and challenges. While AI‐supported tools offer potential benefits, they can also trigger complex test‐related emotions that may impact learners’ psychological academic well‐being. Therefore, understanding the interplay between internal resources like self‐esteem mindfulness, alongside these emotions, becomes crucial. This study investigated correlations mindfulness with test well‐being achievement among EFL learners in contexts China. To meet this purpose, quantitative approach was employed, using data collected from sample 305 university students (155 males 150 females) China selected through stratified random sampling. analysis conducted via confirmatory factor structural equation modelling SMART PLS software. results indicated were strong predictors wellness achievement. Higher levels linked to higher These findings stress necessity incorporating socio‐emotional skills AI‐enhanced learning, considering students’ when deploying AI designing interventions address emotional challenges within environments.

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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Uncurtaining windows of motivation, enjoyment, critical thinking, and autonomy in AI-integrated education: Duolingo Vs. ChatGPT

Learning and Motivation, Год журнала: 2025, Номер 89, С. 102100 - 102100

Опубликована: Фев. 1, 2025

Язык: Английский

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Investigating the Role of AI Tools in Enhancing Translation Skills, Emotional Experiences, and Motivation in L2 Learning

European Journal of Education, Год журнала: 2024, Номер unknown

Опубликована: Дек. 5, 2024

ABSTRACT The integration of artificial intelligence (AI) in L2 teaching and learning is poised to revolutionise educational practices by enhancing both instructional methods language development for learners. This study employed a mixed‐methods design comprehensively examine the impact AI tools, machine translation systems, traditional approaches on students' accuracy, emotions, motivation. A total forty‐nine undergraduate English majors were divided into three groups: Group (AIG; N = 16) using group (MTG; 20) (TG; 13) manual methods. Participants completed four tasks with varying levels linguistic complexity, their performance was evaluated quantitative metrics such as meaning retention, grammatical correctness, fluency, naturalness. Additionally, semi‐structured interviews conducted gather qualitative insights participants' emotional motivational experiences. Quantitative data analysis included Kruskal‐Wallis test assess differences amongst groups, revealing that AIG students achieved highest accuracy. Qualitative thematic interview indicated emotions curiosity, anxiety, excitement prevalent across all groups. While tools fostered motivation MTG, some participants expressed concerns about over‐reliance technology leading reduced engagement. These findings highlight AI's dual role accuracy shaping dynamics learners, suggesting its should be balanced optimise outcomes.

Язык: Английский

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