Design of Distance Information Technology Education Platform Based on Neural Network Algorithm

With the development of Internet and educational informatization, network distance education comes into being and develops continuously. As a new form of education, the great superiority of network distance education is attracting worldwide attention. For distance education, the application of computer network and software technology is crucial to the support of open teaching and management. Learners have certain autonomy in the choice of courses and the use of media, and the learning style, learning progress, time and place can also be decided by learners according to their needs; Moreover, learners mainly use a variety of media teaching materials to study independently, and receive teachers’ learning guidance and necessary face-to-face counseling and other support services remotely through the network. Aiming at the structural characteristics, self-adaptive and self-learning functions of neural network (NN), this paper proposes a modern distance education teaching quality evaluation system based on BP neural algorithm, determines the mathematical model of the system, uses each evaluation index as its input, and takes the teaching effect as its output. The model has convergence speed and network adaptability. The experimental results show that the mathematical model overcomes the complexity of the traditional teaching process of analysis and evaluation, and has the characteristics of convenience, accuracy, reliability and speed, with high identification accuracy.