Exploration of the Cultivation of Post-editing Ability of Chinese College Student Translators in the Digital Age

With advancements in technology, large models such as GPT possess powerful text generation and semantic understanding capabilities following training. They have demonstrated remarkable flexibility and accuracy in the field of machine translation. In this context, the workflow and model of translation have changed. Post-editing in the context of machine translation is a very important part of the translation process, and it has been a topic of interest in recent research. Many studies have shown that the popularization of large language models has put forward new requirements for translators, especially student translators. This paper analyzes the continuous changes in translation technology in the context of the digital age and explores the construction of a training model suitable to improve student translators' post-editing ability. Based on constructivist theory and the PACTE translation model, this paper employs a hybrid