Exploring the English Teaching Model Based on College Students' Participation in Natural Environment Integration

Exploring the English Teaching Model Based on College Students' Participation in Natural Environment Integration

Dan Zhao, Ji Li, Yanping Wang
DOI: 10.4018/IJWLTT.333710
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Abstract

In ELT, how to assess and evaluate students' natural factors by labeling and classifying them has become a key issue. Based on this, this paper makes an in-depth study on the application of natural environment incorporation algorithm based on deep learning in English teaching. First, this paper briefly explains the background and development direction of the current applications in ELT, and categorizes, summarizes, and analyzes them, focusing on the characteristics, problems, and issues of each study itself, and dissecting their limitations. Secondly, the environmental integration technologies in English teaching are categorized, and an intelligent and smart teaching assessment scheme is proposed, combined with the assessment of English teaching mode. Finally, the paper also conducts an experimental validation. The results of the study show that applying English assessment methods to learners of different English levels to their categorized English teaching can improve the quality of English teaching.
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Introduction

The reform of college English teaching has increasingly emphasized all-around development and lifelong education. In the context of China’s “Internet Plus” plan, students’ learning channels and resources are more diversified. College English teaching inside and outside the classroom is undergoing new changes. Multi-modal teaching, flipping the classroom, and creating a “golden class” and “ideological and political curriculum” all emphasize the importance of classroom construction. However, some educational imbalances remain, such as the physical distance between teachers and students, the imbalance between professional learning and language learning, the imbalance between in-class teaching and extracurricular learning, and the disparity between training objectives and teaching effects. In the current reality of reduced college English class hours, it is increasingly important to enhance the efficiency of classroom teaching. Classroom teaching is the primary form of educational work and the key to improving teaching quality. Innovative classroom teaching entails creating classroom situations, effectively managing the core elements and significance of the classroom, and endowing classroom teaching with real significance and educational value. However, the current “listening, speaking and writing” method has become the “weakness” of the English classroom (Rai et al., 2021). This critical issue must be addressed to improve the quality of English teaching (Duan et al., 2021). However, although many English teaching models have emerged, most education systems are not tailored to the characteristics of each student and their specific situation, thus limiting their creative and hands-on development and preventing them from fully utilizing their potential to learn English (Yu et al., 2023). In this context, this paper proposes a new English teaching system based on a natural environment integration algorithm to encourage college students’ participation.

The paper consists of four parts. Part 1 briefly describes several types of deep learning algorithms widely used in current English language teaching (ELT) models and briefly introduces recent developments in the field. Part 2 briefly discusses the similarities and differences between English language education at home and abroad, pointing out that the contextualization approach can be applied to the English classroom but cannot be replicated precisely. Part 3 proposes a new integrated learning approach through an in-depth analysis of English and combines natural integration techniques and multiple educational elements to form a new learning system. Part 4 uses an experimental study to practice and evaluate the constructed English classroom and teaching system. The paper’s contribution involves using an environment-based integration algorithm to analyze the relevant characteristics of the selected major teaching factors combined with the natural environment fusion technique to summarize the characteristics of different environmental factors and reclassify them using the attention mechanism to eliminate interference and obtain more helpful information. On this basis, the characteristics of various ELT factors in conjunction with relevant environmental theories are summarized into corresponding algorithms, improving classroom teaching and allowing students to grasp the key points more effectively.

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