| Sumario: | Background: The rapid advancement of artificial intelligence (AI) is reshaping language education, with AI‐assisted language learning (AILL) offering new opportunities for personalised support and interactive engagement. However, it remains underexplored how English as a Foreign Language (EFL) learners perceive and engage with AI tools in specific learning contexts, particularly in translation tasks. Objectives: This study explores Chinese EFL learners' perceptions and practices in AI‐assisted translation tasks, with a particular focus on the interplay between perceptions and practices, as well as the factors shaping this engagement. Methods: The study was conducted at a provincial "Double First‐Class" university in China and involved third‐year English majors enroled in the compulsory course Advanced English, where students completed authentic Chinese‐English and English‐Chinese translation tasks using AI tools, including ChatGPT, DeepL and Wenxin Yiyan. Data were collcted from six participants through learning journals completed over one academic semester and post‐course semi‐structured interviews. Results and Conclusion: The findings suggest that participants in this study tended to express generally positive orientations toward AI tools, particularly in terms of enhancing translation efficiency and providing access to diverse linguistic resources, while also identifying limitations related to cultural contextualisation, fluency and the accuracy of specialised terminology. Learners appeared to follow an emergent three‐stage pattern of engagement consisting of draft generation, multi‐tool cross‐validation and manual optimisation, reflecting a critical and strategic rather than uncritical use of AI. This process was mediated by factors including language proficiency, task complexity and the technological features of the employed AI tools. The study contributes to current understandings of AILL by offering qualitative insights into how learner agency is reconfigured in AI‐mediated translation tasks and by highlighting translation as a productive context for examining both the opportunities and constraints of AI integration. The findings also provide pedagogical implications for supporting more critical, reflective and context‐sensitive uses of AI in language learning environments. Highlights: What is currently known about this topic? ○AI tools are increasingly used in language education to support personalised, efficient and interactive learning experiences.○Previous studies have shown that learners often perceive AILL positively since AI tools can provide immediate feedback, language support and flexible learning opportunities.○Existing research has also identified concerns related to the accuracy, reliability and ethical implications of AI‐generated language outputs.○Most prior studies have focused on general language skills, such as writing, speaking or vocabulary learning, with relatively limited attention paid to translation‐based tasks.○The Technology Acceptance Model (TAM) and AI literacy perspectives suggest that learners' engagement with AI is influenced by perceived usefulness, ease of use and critical evaluative abilities.What does this paper add? ○This study provides qualitative evidence of how Chinese EFL learners perceive and use AI tools specifically in translation tasks.○The findings show that learners' perceptions and practices are dynamically interconnected rather than separate dimensions of AI engagement.○The study identifies an emergent three‐stage pattern of AI engagement in translation tasks: draft generation, multi‐tool cross‐validation, and manual optimisation.○The research highlights that learners do not simply accept AI outputs passively; instead, they engage in varying degrees of verification, evaluation and adaptation.○The study indicates that language proficiency, task complexity and technological features shape learners' critical engagement with AI tools.○Translation tasks are shown to be a productive context for examining the opportunities and limitations of AI‐assisted language learning as they foreground issues of meaning, culture and specialised knowledge.Implications for practice and/or policy ○Language educators should integrate AI literacy into language teaching, helping students develop skills for evaluating, verifying and critically adapting AI‐generated outputs.○Teachers should guide learners to use AI strategically rather than relying on it uncritically, particularly in translation and meaning‐focused tasks.○Pedagogical support should be differentiated according to learners' language proficiency and critical evaluation abilities○Translation activities can be used as effective pedagogical spaces for fostering reflective and context‐sensitive AI engagement
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