inteligencia artificial

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Tipo: artículo

Metodología: estudio empírico

Resumen:

The rapid integration of artificial intelligence (AI) into language education has transformed how learners manage and direct their learning processes. Despite the growing adoption of AI-assisted tools, empirical understanding of their psychological and behavioral impacts remains incomplete. This study investigated how engagement in AI-assisted language learning environments shapes learners’ self-regulation, autonomy, and self-directed learning behaviors. Drawing on self-determination theory and Zimmerman’s model of self-regulated learning, the research employed a quantitative design with data collected from 736 Chinese university students using validated questionnaires measuring AI engagement, self-regulation, self-directed learning, and learner autonomy. Structural equation modeling (SEM) and correlational analyses were conducted...

Enhancing English language learning through moral dilemmas: A comparative study of GPT and human-written stories

Jiaqi Wang, Chengliang Wang, Tong Xiao (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

This study investigates the effects of generative pre-trained transformer (GPT) generated vs. human-written moral dilemma stories on English as a foreign language (EFL) learners’ speaking skills, storytelling ability, and behavioral regulation, framed within the theoretical context of embodied cognition. A total of 120 university students were divided into two groups: the experimental group, which engaged with GPT-generated moral dilemma stories, and the control group, which worked with human-authored moral dilemma stories. Over an 11-week experimental period (including pre-test, 10-week intervention, and post-test), each group was exposed to weekly dilemma stories, followed by speaking assessments using IELTS Part 2 tasks. Analysis of covariance results demonstrated that the GPT group significantly outperformed the control group in...

AI-Assisted Digital Storytelling in EFL Teacher Education: A Qualitative Case Study of Digital and Multimodal Literacy Development

Bessie Mitsikopoulou (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

This qualitative case study explores how English as a foreign language (EFL) student teachers engaged with generative artificial intelligence (GAI) in the collaborative design of digital stories within an advanced undergraduate course in 2024. During the semester, participants critically evaluated and applied various AI applications, such as text-to-image generators, automated video editors and speech synthesis tools, to support different stages of multimodal story production, including script drafting, visual design, audio narration and video editing. Drawing on a corpus of 69 reflective papers (approximately 75,000 words), the study examines how student teachers integrated visual, auditory and textual elements to achieve multimodal cohesion and narrative coherence. The analysis focuses on participants’ practices and strategies for...

Investigating EFL teachers’ use of generative AI to develop reading materials: A practice and perception study

Jieting Jerry Xin (2024)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Generative artificial intelligence (AI) tools have shown great potential for assisting teachers in their teaching routines. However, there is an urgent need for more empirical research to investigate the implementation and effectiveness of these tools. This study aimed to explore how teachers in an English as a foreign language (EFL) context perceived and used a generative AI-based tool, ChatPDF, to develop materials for reading lessons. Data were collected from three EFL teachers’ dialogues with ChatPDF, artefacts (including original and finalized materials), and individual semi-structured interviews. Content analysis was used to analyse the dialogues with ChatPDF through the lens of pedagogical content knowledge. The interviews were analysed thematically, and the artefacts were used for triangulation. The findings show that the...

Bridging language teachers’ AI literacy and AI-induced emotions: A systematic review and a framework for future research

Xiao Xie, Lawrence Jun Zhang, Aaron J Wilson (2026)

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Tipo: artículo

Metodología: revisión bibliográfica

Resumen:

Texto completo

The integration of artificial intelligence (AI) into language education is transforming pedagogical practices. This transformation is influenced by two distinct yet interconnected domains: the cognitive domain, encompassing AI literacy, and the affective domain, involving AI-induced emotions. However, the dynamic interplay between cognition and emotion in this context is a critical yet underexplored area of research. This study presents a systematic review, compliant with PRISMA guidelines, synthesizing findings from the Web of Science, Scopus, and ProQuest databases. The review delineates the specific characteristics of AI literacy and catalogues the range of emotions arising from AI use. To...

The development and validation of the artificial intelligence literacy scale for middle school English teachers

Yang Gao, Xiaochen Wang (2026)

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Tipo: artículo

Metodología: estudio empírico

Resumen:

As artificial intelligence (AI) becomes increasingly embedded in education, AI literacy has emerged as a critical competency for teachers across disciplines. However, existing research and assessment tools largely focus on STEM (science, technology, engineering and mathematics) fields, with limited attention given to AI literacy within language education. To address this gap, the present study aimed to develop and validate an AI literacy scale specifically designed for middle school English teachers in China. The scale is based on a four-dimensional framework comprising Awareness, Use, Evaluation, and Ethics. Using sequential design, item analysis and exploratory factor analysis were conducted with a sample of 700 teachers, followed by confirmatory factor analysis with an independent sample of 823 teachers, resulting in a final...

A skill-specific perspective on AI-mediated informal digital learning of English (AI-IDLE): Examining the contributing roles of L2 writing motivation and enjoyment

Minlin Zou, Ali Soyoof, Mark Feng Teng (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Artificial intelligence-mediated informal digital learning of English (AI-IDLE) is emerging as a promising field in computer-assisted language learning (CALL). This study asserts a need to adopt a skill-specific (e.g., writing) perspective to examine the unique challenges and psychological mechanisms associated with second language (L2) writing. Drawing upon the theoretical concepts of L2 writing future selves (i.e., the ideal L2 writing self and the ought-to L2 writing self) and L2 writing enjoyment, this study seeks to investigate the motivational and affective basis of AI-IDLE writing (AI-IDLE-W). We collected questionnaire data from 412 Chinese university students and conducted postsurvey interviews with 12 of them. The quantitative findings demonstrated that both the ideal L2 writing self and the ought-to L2 writing self can...

Dynamic Feedback Mechanisms in Technology-Enhanced Language Learning: Examining Learner Engagement and Second Language Writing Outcomes

Li Sun, Chris Jordan (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: feedback/retroalimentación

Resumen:

This 8-week randomized controlled experiment tested the different effects of adaptive artificial intelligence-based feedback versus static rule-based feedback on learner engagement and the acquisition of second language writing in 216 undergraduate students of English as a foreign language. The respondents were randomly divided into a control group that used standard automated feedback and an artificial intelligence-adaptive feedback group in which the responses were customized according to individual proficiency levels and error patterns. Validated analytical rubrics (intraclass correlation coefficient = 0.89) were used to evaluate the writing quality, and the involvement was assessed through self-reports and system logs weekly. The multilevel analysis of the growth curve revealed that there were high treatment effects, in that the...

Investigating pre-service teachers’ AI literacy for ELL instruction: A mixed-methods study

Ali Kushki, Anne Garcia, Victoria L Lowell (2026)

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Tipo: artículo

Metodología: estudio empírico

Resumen:

Artificial intelligence (AI) has taken the educational field by storm, offering unique affordances for addressing diverse learners’ needs, including those of English language learners (ELLs). Harnessing the pedagogical value of AI, however, largely depends on teachers’ preparedness to integrate the new technology effectively into teaching. Pedagogical integration of AI is especially important for pre-service teachers (PSTs), who often struggle to gain enough technological fluency for teaching ELLs due to limited teaching experience and minimal exposure to field-specific technology experimentation. Given AI’s potential to support differentiated instruction, it is vital for PSTs to learn to use the technology effectively to teach ELLs. Grounded in the technological pedagogical content knowledge framework, this mixed-methods study...

Artificial intelligence-enhanced self-paced learning in English as a foreign language: A nonlinear dynamic and self-determination framework for optimizing postgraduate linguistic proficiency—a mixed-methods randomized controlled trial

Xirui Cai (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

This empirical study examines the effectiveness of artificial intelligence-enhanced personalized language learning interventions—tailored content adaptation, self-paced progression, and targeted weakness intervention—on academic writing proficiency, vocabulary acquisition, and grammatical accuracy among 540 Chinese postgraduate learners of English as a foreign language. Utilizing a pretest–posttest randomized controlled design, participants were assigned to three experimental groups (each receiving a distinct artificial intelligence-driven intervention) or a control group (traditional instruction). Quantitative analyses (multivariate analysis of covariance/analysis of covariance) demonstrated significant improvements across all learning outcomes for artificial intelligence groups compared with controls ( p .001), with the most...