SA  >> Vol. 7 No. 1 (February 2018)

    基于结构方程模型的大学生时间管理对学业影响的相关性分析
    Analysis about Influence of College Students’ Time Management on Academic Based on Structural Equation Modeling

  • 全文下载: PDF(890KB) HTML   XML   PP.25-31   DOI: 10.12677/SA.2018.71004  
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作者:  

李文文,范佳玮,贺煜超,薛建勇,董亚辉,施三支:长春理工大学理学院,吉林 长春

关键词:
结构方程模型相关性分析时间管理大学生学业Structural Equation Model Correlation Analysis Time Management College Students Academic

摘要:

结构方程模型是一种分析建立、统计预测多变量因果关系的数学分析方法。本文从心理学的角度出发,将学业设为学习能力、创造性思维、语言表达能力、交流合作能力四个维度,将时间设为时间价值感、时间监控观和时间效能感三个维度。对长春市四所高校的学生发放700份调查问卷,使用SPSS统计软件进行问卷信度分析,得到问卷信度为0.893,表明信度良好。用AMOS软件建立模型系数估计统计量以及结构方程模型路径图,得到所有项路径系数的P值都在0.05的显著性水平以下,表明大学生时间管理和学业水平存在显著正相关,并据此建立了相关的结构方程。研究结果显示,好的时间管理不仅可以提高学生的学习绩效,还可以为促进人格的进一步社会化奠定良好的基础。

The structural equation model is a mathematical analysis method to establish and statistically predict the causality of multivariate variables. From the perspective of psychology, this article sets the academic as the four dimensions of learning ability, creative thinking, verbal expression ability and communication and cooperation ability, setting time as the three dimensions of time value, time monitoring and time efficacy. 700 questionnaires were distributed to students in four colleges and universities in Changchun, and the questionnaire reliability was analyzed by using SPSS statistical software. The reliability of the questionnaire was 0.893, indicating good reliability. Using the AMOS software to establish the model coefficient estimation statistic and the structural equation model path map, the P values of all the path coefficients are all below the significance level of 0.05, indicating that there is a significant positive correlation between the time management and the academic level of undergraduates and the related structural equa-tions are established. The results show that good time management can not only improve stu-dents' learning performance, but also lay a good foundation for further socialization of person-ality.

文章引用:
李文文, 范佳玮, 贺煜超, 薛建勇, 董亚辉, 施三支. 基于结构方程模型的大学生时间管理对学业影响的相关性分析[J]. 统计学与应用, 2018, 7(1): 25-31. https://doi.org/10.12677/SA.2018.71004

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