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A Comparative Study of Online and Offline Teaching Modes of Accounting Courses Based on Convolutional Neural Networks

At present, the accounting teaching in many colleges and universities is mainly based on traditional classroom lectures. In the course of teaching, teachers often use single-filled, instilled, and one-to-one explanations for knowledge transfer. Although this method can enable students to understand and master the content of the textbook, it cannot apply the learned theories to practice well. Therefore, starting from the convolutional neural network(CNN), this article uses big data to conduct a comparative study of online and offline accounting teaching. The purpose is to compare the strength and weakness of online and offline teaching(OOT). This article mainly uses investigation method, data method and comparative method to conduct in-depth research on students' attitudes towards OOT, (CNN)s and OOT modes. The survey results show that 68% of students accept both OOT modes. The time flexibility of online teaching cannot be compared with offline teaching, but the interactivity of online teaching cannot be compared with offline teaching.