
Effective College English Teaching Based on Teacher-student Interactive Model
Author(s) -
Hui Fang,
Hongmei Shi,
Jiuzhou Zhang,
Marimuthu Karuppiah
Publication year - 2023
Publication title -
acm transactions on asian and low-resource language information processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.239
H-Index - 14
eISSN - 2375-4702
pISSN - 2375-4699
DOI - 10.1145/3486676
Subject(s) - memorization , computer science , mathematics education , process (computing) , coaching , flexibility (engineering) , troubleshooting , excellence , psychology , statistics , mathematics , political science , law , psychotherapist , operating system
English has become an utterly crucial device to take part in global verbal exchange and competition. It is essential to enhance English teaching's flexibility to meet the desires to improve the market economy. Therefore, powerful coaching strategies and language identification are considered challenging factors in existing methods. The proposed model includes hypothesized relationships among college students' conception of learning English, their perceptions of the study room environment, and their approaches to learning. They are examined using the Pre- Trained Teacher -Student Fixed Interactive Model (PTSFIM). This model proposes a new way to develop the teaching process providing the baseline of record excellence towards a strategic performance control framework for an institute. The traditional strategies emphasize the benefits of the interactive approach and accentuate their effectiveness through Structural Multivariate Equation (SME) analysis in enhancing students' innovative thinking, research, and reasoning abilities. The reciprocal instructional analysis optimizes students' models to memorize for a longer duration. The evaluation of the study's outcomes suggests that interactive learning can assist college students that predict different results in participating inside the speech system and gain the best knowledge. The simulation analysis is performed based on accuracy, performance, and efficiency proves the reliability of the proposed framework