With the development of the big data era and the opening of translation majors in colleges and universities, translation teaching is gradually receiving attention. However, there are still many problems in the training of translators in colleges and universities in terms of teachers, teaching time and teaching mode. In the context of the era of big data, this article uses questionnaires and data analysis, starting from the PACTE translation ability model, combined with constructivist learning theory, blended learning theory, and instructional design theory to analyze the problems of undergraduate translation ability. This article conducts a questionnaire survey on the 2018 students of XX University’s a major, and analyzes their English scores. Students’ bilingual ability is weak, and it is difficult to consider translation under the influence of context in the translation process; their strategic ability is not ideal, and they lack the ability to solve problems when they encounter specific translation problems. The English performance of the experimental class students who have undergone English translation teaching for one semester is significantly better than the control class students who have not received English translation teaching. Teachers can combine teaching theories to design English translation teaching and cultivate students’ awareness of comparative analysis in English learning. Teachers can cultivate students’ English thinking ability, promote them to master English better, and help them improve their English application ability.
Personalized Teaching Model of College English Based on Big Data