Study on College English Online Teaching Model in Mixed Context Based on Genetic Algorithm and Neural Network Algorithm

• Published in: Discrete dynamics in nature and society Vol. 2021; pp. 1 - 10
• Main Author: Ma, Xiaoxia
• Format: Journal Article
• Language: English
• Published: New York Hindawi 03.12.2021; John Wiley & Sons, Inc; Wiley
• Subjects: Algorithms; Artificial intelligence; Big Data; CAI; Classrooms; Colleges & universities; Computer assisted instruction; Education; Educational evaluation; Educational technology; Errors; Feedback; Genetic algorithms; Information technology; Learning; Methods; Neural networks; Questionnaires; Reliability analysis; Students; Study and teaching; Teachers; Teaching; Visualization; Web sites; United Kingdom; China
• ISSN: 1026-0226; 1607-887X; 1607-887X
• DOI: 10.1155/2021/8901469

College English classroom teaching evaluation is an important basis for understanding teaching level and improving teaching quality. The traditional college English classroom teaching evaluation is mainly carried out through questionnaires and scales, but this method is time-consuming and laborious, inevitably introduces subjective errors, and reduces the accuracy and credibility of the evaluation results. In recent years, the rise and development of wisdom education not only provides a more convenient and efficient modern education form but also brings new ideas for classroom teaching evaluation. A subjective and objective fusion statistical evaluation model based on multidirectional genetic variation method and optimized neural network is proposed. The algorithm avoids subjective errors and improves the accuracy and reliability of the evaluation results, and a comprehensive evaluation model is constructed. Finally, according to different evaluation indexes, a systematic visualization scheme is designed to generate students’ classroom learning evaluation report and teachers' classroom teaching evaluation report, respectively, and visualize them on the web.