This paper establishes an index system based on the interactive teaching method and the characteristics of the English and American literature classroom, quantifies the index system as well as the student opinion data using the RBF neural network, and subsequently derives the actual teaching effect of the interactive teaching method for the classroom teachers to adjust their teaching strategies. The focus of this paper is to add a connection from the input layer to the output layer in the RBF neural network and to improve the operating effect of the RBF neural network with nearest neighbor clustering and steepest descent method. After the model design was completed, it was put into practical use in two universities to quantitatively evaluate the teaching effectiveness of the experimental and control classes that adopted the method of this paper. The average test scores of the students in the two classes in the first university differed by 5.2 points, but the probability of significance from the independent samples t-test results of the post-test scores of the two classes was 0.042, which was lower than 0.05. The reading score of the experimental class in the second university after changing the teaching method was 3.4863, which was higher than that of the control class, which was 2.8567. The use of the interactive teaching method in the classroom of English and American Literature can enhance students’ various abilities.