Research on Blended Teaching Evaluation Model of College English Based on Entropy Method and BP Neural Network

With the advent of Educational Informatization 2.0, the teaching mode of education combined with information technology has been widely adopted in college English teaching and learning nationwide. In response to reforms in educational informatization, a comprehensive evaluation model with a combination of 5G, big data, information mining, and neural networks came into existence. Currently, research on blended teaching evaluation based on AHP approach has been made with relatively desirable results. Yet, since AHP approach has its limitations in the subjective evaluation process, this article aims to assess the learning effectiveness through subjective and objective angles based on AHP and Entropy method, thus calculating the weighted values of each index scientifically and appropriately. Finally, the BP neural network is adopted to train the input data until the error value can be minimized to the expected results. The simulation results show that this evaluation model can be objectively, accurately and efficiently used to assess the learning effectiveness of college English blended teaching.