Closed-Loop Automation with Python in Translation Technology Teaching – The Acquisition of a Meta-technology Competence Through Project-Based Learning

This paper proposes a project-based approach to teach and improve modern translator’s skills in translation technology. Based on a three-level classification [2, 12, 14] of translation tools, it discusses the motivators and inhibitors of adopting current state-of-the-art translation technologies into a translator’s workflow and the existing loopholes in workflow automation. Several translation scenarios in English-Chinese language pair are explored, such as Chinese term extracting, large-scale corpus building, mass process of structured language data, etc. It presents the initial finding that a high-level of workflow automation cannot be achieved with mere adoption of commercially available tools, and some ready-made tools have shortcomings like steep learning curve, high deployment cost, and hidden regulatory risks, etc. Against this background, the paper turns away from the traditional tool-centered teaching and sets out to explore a meta-technology solution. Challenges and opportunities of introducing a digital “machine tool” technology, namely the programming languages, into the training of translators are discussed. The paper demonstrates how a translation-project-based Python course can be designed and carried out to help translation students working in English-Chinese language pair. The whole demonstration constructs a closed loop automation for a modern translator’s workflow.