“I feel AI is neither too good nor too bad”: Unveiling Chinese EFL teachers’ perceived emotions in generative AI-Mediated L2 classes

Computers in Human Behavior, Journal Year: 2024, Volume and Issue: 161, P. 108429 - 108429

Published: Aug. 31, 2024

Language: Английский

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A latent growth curve modeling of Chinese EFL learners’ emotional fluctuations in AI-mediated L2 education: is positivity or negativity on the rise?

Innovation in Language Learning and Teaching, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 14

Published: Jan. 1, 2025

The role of artificial intelligence (AI) tools in promoting different aspects second language (L2) education has recently obtained increasing attention. However, there is insufficient evidence about the contribution AI-mediated L2 instruction to English as a foreign (EFL) learners' positive and negative emotions. To address gap, this study conducted latent growth curve modeling (LGCM) analysis find out changes 350 Chinese EFL classroom engagement enjoyment. Two questionnaires were used collect data at points semester that was taught through AI tools. results showed both enjoyment significantly increased learners over time. While grew steadily participants, rate not equal among them. Furthermore, it found student had going-togetherness time, from beginning end course. are discussed implications for adoption classes provided teachers teacher educators.

Language: Английский

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Developing and Validating a Scale of Artificial Intelligence Anxiety Among Chinese EFL Teachers

European Journal of Education, Journal Year: 2025, Volume and Issue: 60(1)

Published: Jan. 7, 2025

ABSTRACT As artificial intelligence (AI) technology continues to advance, its influences across various industries have grown, leading increasing levels of anxiety, including that in education. Nonetheless, terms current knowledge, the literature lacks a valid scale measure AI anxiety among EFL teachers, particularly university teachers. Moreover, underlying dimensions this construct yet be clarified. Against these gaps, study aims develop and validate assess teachers China. We used qualitative interviews quantitative surveys combined identify key In so doing, 251 Chinese completed newly designed scale. The result exploratory factor analyses indicated five 21 items questionnaire. Five were identified: technical proficiency, job displacement, technological support, student experience research development. Next, another 415 participated validating confirmatory analysis demonstrated strong reliability, validity an acceptable model fit. This new provides useful tool for assessing highlights unique challenges they face adapting AI, offering basis future targeted support.

Language: Английский

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Can AI Empower L2 Education? Exploring Its Influence on the Behavioural, Cognitive and Emotional Engagement of EFL Teachers and Language Learners

European Journal of Education, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 8, 2024

ABSTRACT Artificial intelligence (AI) is transforming L2 education, yet its specific impacts on English as a foreign language (EFL) teachers and learners' engagement remain understudied. To address this deficiency, study, grounded in Fredricks, Blumenfeld, Paris's ( Review of Educational Research , 74 109) three‐dimensional model, explored the AI behavioural, cognitive emotional EFL learners through semi‐structured interviews with 24 38 college learners, followed by thematic analysis MAXQDA to uncover effectiveness AI. The study found that behavioural showcased integration tools, highlighting increased frequency use their practical applications enhancing acquisition tasks. Cognitive was marked recognition capacity augment teaching strategies learning processes, although it also surfaced concerns about potential overreliance technology. Emotional reflected complex interplay attitudes, most informants viewing positively but acknowledging job displacement, emotions students well relations between them. concluded while held promise for must consider limitations ethical implications. research provided valuable insights educators, technology developers policymakers, encouraging innovative practices informed decision‐making education.

Language: Английский

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Does the work environment matter in shaping English as a foreign language teachers’ teaching for creativity: A mixed‐methods investigation into the roles of perceived climate, peer group interaction, and supervisory relationship

International Journal of Applied Linguistics, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 24, 2024

Abstract Teachers play a critical role in fostering students’ creativity, especially English as foreign language (EFL) classes, known teaching for creativity (TfC). Despite this, no comprehensive study has explored how the work environment influences EFL teachers’ TfC. Therefore, this investigates various holistic factors affect TfC among Chinese teachers. Drawing on dynamic componential model of employs mixed‐methods approach, combining quantitative data from survey 406 teachers analyzed using partial least squares structural equation modeling Smart PLS 3, and qualitative insights semi‐structured interviews with 20 MAXQDA 2022. The results reveal that perceived climate peer group interaction positively significantly impact TfC, whereas supervisory relationship (SR) does not show significant effects. findings validate these outcomes offer deeper into PC PGI specifically facilitate or impede alongside explanations non‐significant SR. Additionally, analysis identifies another influential factor TfC: teacher–student interaction. These carry theoretical practical implications teacher educators professional development

Language: Английский

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From Excitement to Anxiety: Exploring English as a Foreign Language Learners' Emotional Experiences in the Artificial Intelligence‐Powered Classrooms

European Journal of Education, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 31, 2024

ABSTRACT The use of artificial intelligence (AI) technologies in second/foreign language education has recently gained a bulk attention. However, the emotional experiences English as foreign (EFL) learners AI‐mediated classes have been ignored. To fill this gap, present qualitative study examined 34 Chinese EFL students' perceptions AI‐induced emotions and regulation strategies. A semi‐structured interview narrative frame were used to collect data. gathered data thematically analysed through latest version MAXQDA software (v. 2023). findings revealed that students had mostly experienced positive ‘motivation’, ‘excitement’, ‘engagement’ ‘confidence’. On negative side, they reported experiencing ‘frustration’, ‘anxiety’ ‘stress’ more frequently their classes. Furthermore, indicated participants six strategies, namely ‘seeking help from others’, ‘shifting attention’, ‘cognitive change’, ‘persistent practice’, ‘staying positive’ ‘suppression’ regulate emotions. are discussed implications provided for educators understand aspect AI injection into L2 education.

Language: Английский

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AI‐Mediated Communication in EFL Classrooms: The Role of Technical and Pedagogical Stimuli and the Mediating Effects of AI Literacy and Enjoyment

European Journal of Education, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 23, 2024

ABSTRACT This study leverages the Stimulus‐Organism‐Response (S‐O‐R) framework to investigate effects of teacher and technical support (TCHS) on learners' willingness communicate (WTC) in artificial intelligence (AI)‐enhanced English as a foreign language (EFL) contexts, considering mediating literacy (AIL) enjoyment (FLE). A quantitative survey encompassing 637 non‐English major university students across four institutions was conducted. Structural equation modelling (SEM) results demonstrated that (TEAS) exerts direct influence WTC, whereas TCHS does not. The also revealed AIL FLE significantly mediate relationship between learners’ WTC. findings underscore pivotal role cognitive affective factors, emphasising substantial impact TEAS value nurturing languages. research offers strategic implications for educational practitioners policymakers, advocating integration innovative technologies fostering sustainable growth education.

Language: Английский

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The role of STEM teachers' emotional intelligence and psychological well-being in predicting their artificial intelligence literacy

Acta Psychologica, Journal Year: 2025, Volume and Issue: 253, P. 104708 - 104708

Published: Jan. 14, 2025

Language: Английский

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Modelling College Students' Acceptance to Use Generative Artificial Intelligence for Second Language Learning: A Theory of Planned Behaviour Perspective

European Journal of Education, Journal Year: 2025, Volume and Issue: 60(1)

Published: Jan. 17, 2025

ABSTRACT The benefits of Generative Artificial Intelligence (GenAI) in enhancing second language (L2) learning are well established. However, these advantages can only be realised if learners willing to adopt the technology. This study, grounded Theory Planned Behaviour (TPB), investigated factors influencing behavioural intention use GenAI among 337 Chinese college L2 using five validated scales. A Structural Equation Modelling (SEM) approach with Amos 24 yielded several key findings. Notably, demographic encompassing gender and age did not significantly affect TPB components. Subjective norm attitude were found have a positive significant impact on intention, while perceived control demonstrate effect. Furthermore, literacy emerged as predictor both directly indirectly through its influence attitude. Collectively, variables accounted for 51.6% variance intention. study also discusses theoretical pedagogical implications offers suggestions future research.

Language: Английский

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Design and Psychometric Evaluation of the Artificial Intelligence Acceptance and Usage in Research Creativity Scale Among Faculty Members: Insights From the Network Analysis Perspective

European Journal of Education, Journal Year: 2025, Volume and Issue: 60(1)

Published: Jan. 27, 2025

ABSTRACT The acceptance of artificial intelligence (AI) in academic settings, particularly the context research creativity, is a growing area interest. This study aimed to design and validate AI Acceptance Research Creativity Scale (AIA&RCS) among faculty members. exploratory mixed‐method was conducted 720 A literature review participant interviews were qualitative phase generate develop items. In quantitative phase, face validity, content construct convergent validity reliability (internal consistency stability) used. Exploratory factor analysis (EFA) indicated 4‐factor model scale with ‘perceived usefulness effectiveness creativity’, ‘ethical issues research’, ‘trusted capabilities’ ‘willingness use AI’ accounting for 51.6% variance. arrangement verified by confirmatory (CFA), fit indices that at suitable levels. Then, network took into account four‐factor structure AIA&RCS further. Similarly, graph (EGA) configuration AIA&RCS. 25‐item well‐suited measuring innovation because its psychometrics.

Language: Английский

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