| 英文摘要 |
The rapid rise of neural machine translation (NMT) applications, driven by advances in artificial intelligence (AI), accessibility and widespread use by students in French departments at Taiwanese universities, as well as in the professional translation sector, has profoundly disrupted the teaching of translation courses. These courses were already fluctuating between language learning and the acquisition of professional translation skills. This new context further complicates the pedagogical approach to translation teaching, calling for a thorough rethinking. This study therefore aims to compare different approaches to translation teaching, to highlight their respective advantages and limitations, while emphasizing the need to develop a guided and pedagogically sound use of NMT. To this end, two types of translation exercises were conducted: one with access to NMT tools and one without, along with the introduction of a post-editing exercise in a Taiwanese university context, inspired by the MTPEAS typology developed by UC Louvain. In light of the emergence of this new AI-driven paradigm, to what extent do traditional translation exercises reveal obsolete characteristics? Moreover, could the broader implementation of post-editing exercises enable an intelligent integration of NMT into translation courses while reducing its drawbacks? |