Knowledge-Network-Based Translation Learning and Learners’ Perception

In today’s digitalized society, online platforms undoubtedly play a significant part in assisting translation education. Whereas it is the development of the core competence of the translation learners that can truly prompt the bright future of translation field. Hence this paper begins with an overview of a corpus-assisted and knowledge-network-based online translation learning platform, and then presents the application of it in practical translation (self-) learning and pays special focus on the perception of the learners of the system. By analyzing the data collected from the questionnaire survey, the paper aims to, from learners’ perceptions of the system, further focus on the feedback of learners, and then explore whether the knowledge-network-based approach plays a more efficient part in the development of translation learning and if so, how as well as the potential improvement of the system to cater to the emerging needs of the users, thus aid users in developing more efficient mode in translation learning.