A study on the development of English reading skills in the MOOC model of English language teaching

This study proposes a personalised intelligent reading resource recommendation method based on MOOC mode. This method uses a deep belief network (DBN) model to extract students’ reading interests and other related data features, and uses the K-means algorithm to classify users’ interests. The model is applied to a personalised recommendation system in the MOOC environment. When the training set accounts for 100%, 75%, 50%, and 25% of the total dataset, the root mean square errors of the recommendation results of the DBN algorithm are 78%, 83%, 88%, and 96%, respectively. During the training process, the convergence speed of the DBN algorithm is significantly faster, with a minimum root mean square error value of 0.805. In the evaluation of recommendation effectiveness under different indicators, DBN performs the best, indicating that the model can adapt to various situations and has great practical application value. Copyright © 2023 Inderscience Enterprises Ltd.