5P Simulated Interpreting Teaching Based on Deep Learning
There is a pressing need in society for interpreters who can quickly adapt to social changes and possess the ability to serve national strategies. However,traditional interpreting education lacks training in authentic scenarios,and students' interpreting learning rarely delves into practical aspects,making it difficult for them to adapt to and navigate real and complex interpreting environments. To address this issue,the simulated interpreting project has been implemented and explored in interpreting courses. This project,supported by deep learning theory and connected to real social service scenarios,creates interpreting workplace contexts and proposes a 5P practical project-based teaching model for interpreting,which includes"Presupposing,Preparing,Performing,Packaging and Perfecting". By analyzing students' interpreting performance data and feedback,it is found that this project can help to enhance students' practical interpreting abilities,demonstrating a deepened understanding throughout the process and outcomes of their interpreting learning. This research provides empirical evidences and academic exploration for the application of deep learning in the field of interpreting and offers a foundation for innovative development in interpreting education.
interpreting educationdeep learningsimulated practice5P model
NETL
NSTL
万方数据
