Wireless Network Access and Emotion Recognition of Online English Translation Teaching System from the Perspective of Artificial Intelligence

Abstract

The research is aimed at verifying the application effect of the online automatic evaluation system in English translation teaching and at understanding the satisfaction of students with different feedback methods. The research uses three classes of human resource management majors in Xi’an Technological University as the research object and uses questionnaire survey and comparative experiment methods to compare and analyse the three feedback methods: teacher feedback, online automatic feedback, and teacher feedback combined with online automatic feedback. The research answers the following three questions: (1) will the three feedback methods affect students’ English translation performance? (2) Which of the three feedback methods will improve students’ English performance better? (3) What about students’ satisfaction with current feedback methods? The research results show that the significance value between the control group (CG) and the experimental group 1 (EG1) is 0.029, that between CG and the experimental group 2 (EG2) is 0.432, and that between EG1 and EG2 is 0.001. There are obvious differences in the posttest scores of the three groups of students. EG2 has the largest average posttest score, which is 9.8182; there is no obvious difference in posttest translation scores between CG and EG2. It indicates that “teacher feedback + online automatic feedback” and teacher feedback have the equivalent effect on improving students’ translation. The results of the questionnaire survey show that students have the highest degree of recognition of “teacher feedback + online automatic feedback.” The research is helpful for teachers to better understand the shortcomings in the translation teaching process, so that they can take effective measures against these problems in the follow-up teaching process to improve their teaching effect.