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A Correlative Study of the Influence of Higher Vocational Students’ Learning Behavior on English Effective Learning

Volume 14, Number 5, May 2018, pp. 937-944
DOI: 10.23940/ijpe.18.05.p12.937944

Lei Chena, Xia Liua, and Qinghui Zhub

aSanya Aviation and Tourism College, Sanya, 572000, China
bCollege of Foreign Languages, Hainan University, Haikou, 570228, China

(Submitted on January 18, 2018; Revised on March 5, 2018; Accepted on April 15, 2018)


This study aims to explore the correlation between learning behavior and English effective learning. 1,758 answers to a questionnaire designed from the perspective of learning behavior are analyzed. The influence of English effective learning is summarized as constructive learning and destructive learning. Using SPSS to analyze the data and model a construction, we study the correlation between learning behavior and the main influencing factors, including constructive learning, destructive learning, mutual influence, learning burnout and employment pressure. The structural model results show that the alpha coefficients are above 0.6, and the corresponding variables load factor values are above 0.3, which proves that the questionnaire is valid and reliable. Correlation analysis is used to explore the impact of the major variables, indicating that significant correlations exist among the major variables. The regression analysis shows that constructive learning can significantly predict the learning behavior, while the destructive behavior can significantly negatively predict the learning behavior. The mutual influence cannot significantly predict the learning behavior. Through a structural equation model fitting analysis, the influence of classmates can significantly predict the learning behavior and employment pressure can significantly negatively predict the learning burnout. Furthermore, learning behavior plays an intermediary role in constructive learning, destructive learning and learning burnout. This study may provide reference for higher vocational English teaching reform from the data analysis.


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