Reimagining Translation Education: Fostering Student Engagement With AI Technologies in Cultural Translation Assessment
DOI:
https://doi.org/10.17507/jltr.1605.07Keywords:
translation education, AI, assessment, pedagogyAbstract
This study challenges the “either-or” dichotomy in attitudes toward AI translation and explores strategies to foster critical engagement with AI tools among students enrolled in translation modules. Drawing on questionnaire responses from students at Xi’an Jiaotong-Liverpool University, the research investigates the issue: learners’ experiences with AI-integrated assessment practices and pathways to harmonizing AI translation with pedagogical goals. Findings indicate that while students recognize AI’s efficacy in generating coherent outputs for standardized text types (e.g., technical or informational content), they emphasize the irreplaceable role of human intervention in culture- and literature-specific translations. Participants highlight the necessity of translators’ subjective creativity to preserve aesthetic nuances and contextual implications, particularly when conveying source-text subtleties. The study further identifies systemic implications for translation education: as AI models advance, curriculum design, assessment frameworks, and institutional policies must evolve holistically to meaningfully integrate AI tools. A systematic-thinking approach is proposed, advocating coordinated efforts across programmatic, departmental, and national regulatory levels to redefine learning outcomes, adapt syllabi, and develop future assessments that ethically leverage AI’s capabilities without undermining translational artistry.
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