The Optimization and Three-Dimensional Survey of the Reform Path of English Education System in Higher Vocational Colleges Driven by Information Technology in the New Era

Abstract

Artificial intelligence (AI) technology has advanced quickly along with the growth of mobile information, altering every aspect of our lives. Meanwhile, the concept of smart education gained popularity, but there hasn't been a thorough debate on how to go towards smart classrooms combined with artificial intelligence. This article focuses on use of AI in college English smart classrooms in order to support intelligent evolution of education. This research propose novel technique in classroom designing based on English teaching model using machine learning model. Input is collected as classroom design data and processed for noise removal and normalization. This input features are extracted and classified using active contour fuzzy model with recurrent Gaussian perceptron neural networks (ACF_RGPNN). The experimental analysis for classroom design analysis is carried out in terms of prediction prediction Accuracy, precision, NSE, AUC, recall. With an average score that was 2.8 points higher than control class's, overall level of English was likewise superior. The proposed method achieved prediction accuracy, precision, recall, and NSE of 96%, 85%, 66%, and 52% respectively.