Teaching reform and innovative application of modern graphic design under machine learning

Abstract

With the development of information technology, machine learning is increasingly widely used in the field of education. Modern graphic design teaching is faced with such problems as inflexible traditional teaching mode and insufficient personalized resources. This study discusses the application of machine learning in the teaching reform of graphic design, and improves the teaching efficiency and students’ learning effect through technologies such as constitutional neural network and long short-term memory network. Through the data-driven personalized teaching path combined with the project-driven practical teaching method, the research results show that the indicators such as course participation, assignment completion rate, classroom interaction, learning satisfaction and design efficiency have improved. The research also puts forward suggestions to optimize the teaching evaluation system, strengthen teacher training, integrate and share teaching resources, etc., so as to improve the teaching quality and students’ comprehensive ability.