Construction of Teaching Quality Evaluation Model of English Flipped Classroom Based on BP Neural Network Algorithm

The English SPOCS(Small Private Online Courses) teaching model has had a profound impact on the reform of higher education. The teaching mode of teaching and learning has been transformed into the inquiry teaching mode of problem-centered, learning first and teaching later, which has been favored by the majority of teachers in China. As a new teaching model, SPOCS involves all the main aspects that should be included in the evaluation index. In this paper, the BPNN evaluation model is trained to evaluate the teaching quality of English SPOCS more scientifically, effectively and objectively, and to provide a reference basis for the reform of English SPOCS teaching and the improvement of teaching quality. Therefore, this paper analyzes the teaching quality of English SPOCS based on BP neural network algorithm, and constructs a teaching quality evaluation model. Finally, the simulation results show that the indicators that have an important impact on the evaluation results are selected and used as the input of BPNN(BP Neural Network). At the same time, the dimensions, levels and weights of the evaluation indicators should be reasonably allocated. The evaluation indicators should be relatively independent, reflecting the characteristics of SPOCS and the actual situation of English teaching in higher vocational colleges.