Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

June 3, 2024


Pages


DOI

Article

A Study of the Utility of Artificial Translation in English Reading Comprehension

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Authors

Shiyun Wang Affiliation:
English Department, Tongling University, Tongling, Anhui, 244000, China.


Abstract

Human translation always has an incomparable role in the process of English learning, especially in the promotion of English reading comprehension. This paper centers on the research problem of selecting suitable research objects, combining questionnaire surveys and test methods to obtain relevant data on artificial translation and English reading comprehension. Then, it analyzes the correlation between the dimensions of artificial translation and the effect on English reading comprehension, constructs the multiple regression model of artificial intelligence on English reading comprehension, and proposes the corresponding significance test method. The results show that the correlation coefficients between the five dimensions of human translation and English reading comprehension scores are, in descending order: accuracy (0.824) > completeness (0.636) > fitness (0.579) > fluency (0.485) > consistency (0.372), which are all significantly positively correlated with English reading scores. The regression results showed that the level of manual translation dimension explained 26.7% of the variation in reading achievement. Among the human translation dimensions, accuracy, completeness, and consistency have significant positive effects on English reading comprehension. The study suggests that human translation accuracy, completeness, and consistency can be optimized to improve English reading comprehension.


Keywords

Significance test, Regression analysis, Correlation analysis, English reading, 68T05


Citation

Wang, S. (2024). A study of the utility of artificial translation in english reading comprehension. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-1329

Published by: Engineering Journals

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