Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

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Teacher corrective feedback (TCF) plays a vital role in second language (L2) learning. Recent studies have examined feedback provided by both human teachers and large language models (LLMs). However, little is known about how students' trust differs toward scaffolded corrective feedback (SCF)—that is, feedback that incrementally progresses from indirect to direct during interaction—when it is provided by an LLM such as ChatGPT versus a language teacher. To address this gap, this study compared the effects of SCF, delivered by language teachers and ChatGPT, on L2 learning outcomes and student trust. Using a mixed-methods design, 40 lower-intermediate Iranian learners of English as a foreign...

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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...

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