A Teaching Model for university English Translation Based on Markov Chain and Mathematical Multiple Intelligence Theory

The application of digitalization and intelligence-related technologies brings unprecedented opportunities and challenges to the development of university English translation teaching.In response to the current English teaching reform, this paper designs a university English translation teaching model based on mathematical multiple intelligence theory.In order to make this teaching mode better serve students and teachers, a personalized recommendation algorithm based on Markov chain is introduced on the original teaching mode.The research samples are selected, the groups as well as the questionnaires are set, the research hypotheses and methods are given, and the task of formulating the research program is finally completed.With the help of independent samples t-test, the university English translation teaching model of this paper is validated and analyzed.There are significant differences between the two in comprehension (F=2.421,p=0.009<0.01),analytical (F=16.522,p=0.002<0.01),practical (F=6.928,p=0.008<0.05),and reflective (F=8.006,p=0.009<0.01)skills, which indicates that the model of university English translation teaching based on the Markov chain and the Mathematical Multiple Intelligences Theory of University English Translation Teaching Model, which has a more obvious effect on the improvement of students' English translation ability.