Nanchang Institute of Technology, Jiangxi 330099, China
With the deepening and development of world education reform, the theory of multiple intelligences has been increasingly accepted and recognized by international and domestic educators with its outstanding advantages and positive effects. Quality education has been implemented in our country for many years, and domestic education reforms have also made some achievements. This article mainly introduces BP neural network(BPNN) and hill climbing algorithm(HCA). Based on the big data, this paper uses artificial intelligence(AI) to detect college English(CE) teaching and establishes a mathematical model of potential pre- and post-test. The mountain climbing algorithm is used to solve the problem, and it also identifies the status quo of AI in CE teaching, and corrects model parameters through past data to improve teaching quality. The results found that the BPNN and the HCA have increased the effect of college English teaching by 33%, and increased students' interest in learning English. However, our country's artificial intelligence has not been established in CE teaching, so that the use of AI cannot be fully carried out.
Big Data, Artificial Intelligence, College English Teaching, BP Neural Network, Hill Climbing Algorithm
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