Outline

Ingegneria Sismica

Ingegneria Sismica

A Big Data-Based Model for Analyzing EFL Learners’ Language Proficiency in English Language Education

Author(s): Qi Wang1, Bing Li2
1Henan University of Animal Husbandry and Economy, Zhengzhou, Henan, 450000, China
2Henan University of Animal Husbandry and Economy, Zhengzhou 450046, China.
Wang, Qi . and Li, Bing. “A Big Data-Based Model for Analyzing EFL Learners’ Language Proficiency in English Language Education.” Ingegneria Sismica Volume 43 Issue 2: 1-18, doi:10.65102/is2026718.

Abstract

The study combines the ADDIE instructional design model with the SPOC blended EFL English teaching model implementation model designed for the characteristics of university English teaching, and conducts teaching practice based on the model. Firstly, data collection on learning behaviors is carried out, including check-in time, live participation, video learning, etc. as well as data collection on EFL learners’ language proficiency. Then Pearson’s correlation and multiple regression model are used to construct a model for analyzing the factors influencing the language proficiency of EFL learners, and finally the study is empirically analyzed. The results show that cell phone becomes the main learning mode of learners and they are more willing to accept learning content in video format. The self-assessed mean value of language awareness dimension was the highest at 3.89, followed by language comprehension dimension with a mean value of 3.84, language expression dimension, and language sense dimension with the lowest self-assessed mean value, and the influencing factors on the language proficiency of EFL learners in descending order of influence were: teacher-student language interaction>language attitude>language learning strategy>language knowledge>parental support.

Keywords
ADDIE model; multiple regression; university English; language proficiency; instructional design

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