A Report On The Simulated E-C Consecutive Interpreting Of An Online Lecture Is Education AI-ready?

Nowadays,with the accelerating development of artificial intelligence,the application of AI in education has been attracting wide attention from both the academia and the society.As the world learns to emerge stronger from the COVID-19 pandemic,there is a greater emphasis on how knowledge can be delivered efficiently through digital solutions and how teachers may leverage emerging technologies such as AI to achieve optimal outcomes for students.This English-Chinese simulation practice report is based on an online lecture Is Education AI-ready? delivered by Rose Luckin,a professor of Learner Centre Design at the UCL Knowledge Lab.This lecture is characterized by the scientific terminologies,complex sentences and the speaker’s fast speaking speed.The main problem of this simulated practice is lacking accuracy in delivery which is reflected in information loss,information redundancy,and illogical interpretation.Through relevant literature reading and theoretical research,the interpreter explores some feasible approaches,like addition,omission and generalization,sentence restructuring and simplification of notes to improve the accuracy of her delivery under the guidance of Danica Seleskovitch’s theory,namely,the Interpretive Theory.The Interpretive Theory divides the whole interpretation into three stages,which include comprehension,de-verbalization and re-expression.The core of the Interpretive Theory is de-verbalization,namely,to get out of the linguistic shell.This report is mainly focused on the analyzing of de-verbalization.In the end,it is found that,in English-Chinese consecutive interpreting,the Interpretive Theory plays a significant guiding role in finding solutions to improve accuracy of the delivery.