Research on the Effect Evaluation of Personalized University English Teaching Assisted by Generative Artificial Intelligence

Abstract

In light of the problems of homogeneity and a lack of goals in traditional university English teaching, this paper presents the construction of personalised teaching models based on generative artificial intelligence technology. The four types of teaching effects are academic performance, students' motivation to learn, ability and quality of learning, and teaching adaptability. Based on the control teaching
experiment for non-English majors at the university, and through questionnaires and data analysis, it was found that generative AI can meet all
the learning requirements of students accurately and improve their overall English application ability and autonomous study efficiency. There
is a technical bottleneck and a uniform response. Therefore, this paper puts forward optimization directions to provide practical support for the
intelligent and personalised teaching reform of university English.