Optimization of College English Teaching Plan under the Background of Micro-Video and Big Data

Abstract

English education has gained greater popularity due to the demands of international economy as well as international politics. College English education is also a part of national English education. However, the English education mode in colleges and universities has certain defects, and it still adopts traditional English education methods to impart knowledge to college students. This limits the interest of college students in learning English. The class hours and assessment mode of English education in colleges and universities limit the time for English learning in colleges and universities, which is also one of the reasons for the disadvantages of college English. Today, with the development of information technology, college English education should consider more technological elements to improve quality of English education in colleges and universities. Micro-video technology is a kind of video with interactive and real-time characteristics, which can be free from geographical restrictions. There are also many English education videos in the micro-video technology, which has a richer background of English knowledge and local customs. This research uses micro-video technology to assist English class level in universities. This research also considers big data theory to extract relevant features in micro-video technology to improve level of college English education. The research results show that micro-video technology can improve learning interest of English students in colleges and universities. CNN and LSTM methods can better predict student grades, student performance characteristics, and teacher performance characteristics. The hybrid CNN-LSTM algorithm has higher accuracy in predicting relevant features of college English teaching compared to the single CNN method. This also shows that the micro-video technology has great temporal characteristics in English teaching. This is a friendly study for improving the quality of English teaching.