AI环境下基于工作场所学习的递进式笔译教学工作坊实践探索

Exploration and Practice of Progressive Translation Workshop Model Based on Workplace Learning in the AI Era

AI环境下,翻译活动的内涵和外延获得了极大的丰富和拓展,了解新时代翻译教学中教与学变迁的过程,是重构翻译教学新模式的重要理据。文章基于重构的智能翻译教学新生态系统,探索基于工作场所学习的递进式翻译工作坊教学模式,尝试借鉴大数据时代的机器翻译流程,重点探讨AI环境下该教学模式在翻译教学中的应用研究,旨在提高学习者的译者能力。为期一个学期的教学实验对被试者的译者能力进行对比分析,结果显示通过在工作场所里的观摩中自我累积学习、经验中同化顺应学习、合作中拓展参与学习,被试者的译者能力得到了明显的提高,并且努力向"观摩—边缘性参与—充分参与"的方向转变,为学习者之后的职业发展提供了一定的启迪。

In the AI era,the concept of translation has been greatly enriched and expanded. Howto develop an intelligent newmodel of translation teaching with AI technology is a key issue for translation teaching researchers. This paper first reconstructs the intelligent translation teaching ecosystem after examining the changes in the process of teaching and learning in the newera,and then presents the "progressive"translation workshop model in the light of the workplace learning. This teaching model draws on the machine translation and big data technology and takes full advantage of selfaccumulative learning through"observation",assimilation and adaptive learning through "experience"and extended participation through "cooperation " in the workplace,aiming to improve translation learners’ ability. A teaching experiment was conducted for a semester to verify the feasibility of the model,providing ideas and reference for other similar teaching practices. In this experiment,questionnaire survey,interviewand proficiency test were carried out and the data were collected and analyzed to examine the effect of the teaching model. The results of the experiment showthat the "progressive " translation workshop model has remarkable effects in improving teaching effectiveness, and promoting the translation learners’ ability, winning high recognition among students. The results of the proficiency tests showthat the average score of the experimental students on the pre-test was significantly higher than that of post-test,including translation skills, fidelity and fluency, creativity of translation and grammar accuracy at the micro level. The results of the questionnaire survey and interviews showthat the vast majority of students were in favor of the"Introductory Workshop"in the model. For students who were not able to accept or understand the tasks of the workshop in a short period of time,especially after teachers’ demonstration of the process of completing the whole project, the model solved the problem and supported computer-assisted translation in the AI environment,which provided a framework for translation norms. The study has the following enlightenment. First of all, the first step to implement smart translation teaching is to create a smart translation teaching environment, in which the deep integration of AI technology and machine translation can greatly improve efficiency and accuracy of translation and a sound teaching ecosystem can facilitate effective learning. Secondly,it is necessary to build a high-quality translation workshop with an emphasis on learning content, learning motivation and interaction, in which the participants strive to change in the direction of "observation "—"peripheral participation"—"full participation",so that the students’ translation theoretical knowledge and translator competence can be acquired and improved.Finally, the age of AI necessitates the updating and improving of teachers’ knowledge structure. Teachers must integrate translation teaching methods with educational technology and translation technology to achieve AI-TPACK,with an ongoing comprehension of translation content,pedagogy and AI technology.