GenAI时代翻译专业智慧学习共同体促进翻译工具能力提升机制研究

Research on the Mechanism of Smart Learning Community in Enhancing Translation Instrumental Competence in the GenAI Era for Translation Majors

摘要: 生成式人工智能(GenAI)的崛起正以前所未有的深度与广度重塑各行各业，翻译领域首当其冲。如何在AI洪流冲击下提升学生翻译工具能力，实现人机共生，是外语教学面临的迫切问题。本文研究人机共生范式下智慧学习共同体(Smart Learning Community, SLC)促进学生翻译工具能力提升机制。通过制定面向GenAI时代的多维度翻译工具能力描述性量表，整合传统工具技能与新兴AI素养、数字素养及数据素养，重塑智慧学习共同体中的主体角色，阐明“人–机–人”反思型互动机制，设计了一套以能力为导向、具有优先级和难度梯度的核心内容模块，并对当前主流AI赋能翻译平台(如YiCAT、Phrase、Smartcat、MemoQ)进行了比较分析，评估其在教学应用中的优劣，旨在为翻译专业教育提供一套系统化的、能够应对未来挑战的人机协同能力培养方案，以适应现代语言服务行业的需求。

Abstract: The rise of Generative Artificial Intelligence (GenAI) is reshaping industries across the board with unprecedented depth and breadth, with the translation field bearing the brunt of this transformation. It has become an urgent issue facing foreign language teaching to enhance students’ translation instrumental competence and achieve human-machine symbiosis under the impact of the AI wave. This study investigates the mechanism by which Smart Learning Community (SLC) enhances students’ translation instrumental competence under the human-machine symbiosis paradigm. By constructing a multi-dimensional descriptive scale for translation instrumental competence oriented towards the GenAI era, this research integrates traditional instrumental skills with emerging AI literacy, digital literacy, and data literacy, reshapes the subject roles in SLC elucidates the “human-machine-human” reflective interaction mechanism, designs a set of capability-oriented core content modules with priority and difficulty gradients, and conducts a comparative analysis of current mainstream AI-enabled translation platforms (such as YiCAT, Phrase, Smartcat, MemoQ), evaluating their advantages and disadvantages in pedagogical applications, aiming to provide translation education with a systematic human-machine collaborative competence development program capable of addressing future challenges and adapting to the demands of the modern language service industry.