Constructing a Data-Driven Model of English Language Teaching with a Multidimensional Corpus

Author:

Chen Dongyan12ORCID

Affiliation:

1. College of International Studies, Beibu Gulf University, Guangxi 535015, China

2. Academy of Language Studies, University of Technology MARA, Negeri Selangor 40450, Malaysia

Abstract

In this study, a multidimensional corpus English teaching model is constructed using the data-driven model. This study uses a data-driven collection of massive amounts of data to generate a multidimensional corpus. The data-driven generation of a multidimensional corpus to build a teaching model is studied, and the principle of data driven, the computational process, and the characteristics of the corpus are analyzed. Due to the deficiency of data-driven modeling without correlating process variables with quality variables, this study adopts an artificial intelligence algorithm and analyzes the basic principle, computational process, and advantages and disadvantages of the method. The model is simulated and verified for multidimensional corpus and English teaching. To address the shortcomings of the AI algorithm, which has a complex computation process and no orthogonal decomposition of the data space, the autoregressive latent structure projection algorithm is designed by integrating the autoregressive idea with the artificial intelligence (AI) algorithm. This algorithm can orthogonally decompose the sample data space and simplify the modeling process. Finally, the algorithm is validated by simulation. To verify the results of the teaching model, the fuzzy C-means clustering algorithm is combined with the autoregressive latent structure projection algorithm in this study. The sample data used in the modeling are divided into categories, and the affiliation function is calculated for each category. The affiliation function is used to calculate the affiliation of the online calculation results for each category, and the final evaluation results are obtained based on the fuzzy comprehensive evaluation method. Finally, taking junior students as an example, the simulation is carried out to verify the effectiveness of the English teaching model. The research results show that the corpus-based English flipped classroom teaching model improves English teaching methods, enhances students’ English proficiency and independent learning ability, and provides a practical basis for English teaching model exploration.

Funder

2021 Guangxi Higher Education Undergraduate Teaching Reform Project

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

Reference18 articles.

1. Fast Transient Stability Batch Assessment Using Cascaded Convolutional Neural Networks

2. Data Driven and Psycholinguistics Motivated Approaches to Hate Speech Detection

3. Writing across the curriculum in ELT training courses: a proposal using data-driven learning in disciplinary assignments;M. Mussetta;International Journal of Teaching and Learning in Higher Education,2018

4. Constrained language use in Finnish: A corpus-driven approach

5. A systematic review of data-driven approaches in player modeling of educational games

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