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    A Study on the Mediating Effect of Psychological Capital and Self-efficacy on Learning Stress and Academic Achievement in Mathematics Module Class among Logistics Major Students in China

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    https://www.riss.kr/link?id=T17348397

    • 저자
    • 발행사항

      영암 : 세한대학교 대학원, 2025

    • 학위논문사항

      학위논문(박사) -- 세한대학교 대학원 , 교육학과 , 2025. 2

    • 발행연도

      2025

    • 작성언어

      영어

    • 주제어
    • 발행국(도시)

      전라남도

    • 형태사항

      ; 26 cm

    • 일반주기명

      지도교수: 고 흥

    • UCI식별코드

      I804:46014-200000937049

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    In the era of big data, the logistics industry is undergoing profound changes. The digitalization construction not only brings new operating modes and business opportunities to the logistics industry, but also poses new challenges to the professional skills of logistics personnel. The mathematics-related courses in university logistics majors bear an important task of logistics digitalization. Therefore, universitys and universities in logistics majors also face new requirements in cultivating students in mathematics-related courses. The academic achievement sense of logistics majors in mathematics-related courses directly affects their learning motivation and even employment. Therefore, it is necessary to pay special attention to the academic achievement of logistics majors in mathematics-related courses. This study aims to explore the current situation and role relationship between learning stress, psychological capital, and self-efficacy in mathematics-related course modules of logistics majors, and to investigate the mediating effects of psychological capital and self-efficacy. The study takes logistics majors at 7 universities in Zhejiang Province in June 2024 as the research object, distributes the questionnaires on learning stress, psychological capital, and academic achievement to collect the final data of logistics majors in mathematics-related course modules. The data is analyzed using SPSS 25.0 statistical software for descriptive statistics, one-way ANOVA, correlation analysis, and regression analysis. The AMOS 24.0 software is used to establish structural equation models and mediating effects, including the mediating effects of psychological capital and self-efficacy. The research results are as follows: First, there are significant population variables in terms of gender, major choice, being an only child, and place of origin in the logistics majors' academic achievement in mathematics-related course modules. Second, the learning stress in mathematics-related course modules has a negative impact on the academic achievement of logistics majors. Third, the learning stress in mathematics-related course modules has a negative impact on psychological capital of logistics majors. Fourth, the learning stress in mathematics-related course modules has a negative impact on self-efficacy of logistics majors. Fifth, psychological capital has a positive impact on the academic achievement of logistics majors in mathematics-related course modules. Sixth, self-efficacy has a positive impact on the academic achievement of logistics students in learning mathematics modules. Seventh, psychological capital has a significant mediating effect between learning stress and academic achievement of logistics major students in learning mathematics course modules. Eighth, self-efficacy has a significant mediating effect between learning stress and academic achievement of logistics major university students in learning mathematics course modules. Based on the findings, this study makes the following educational recommendations: Reducing learning stress in mathematics courses for logistics majors can enhance psychological capital, self-efficacy, and academic achievement. Learning stress negatively impacts academic performance but can be mitigated by improving psychological resources and offering timely support. Universities should guide students in managing stress, fostering a positive learning environment, and promoting mental health to improve academic outcomes. Keywords: University students majoring in logistics, Mathematics courses, Learning stress, Academic achievement, Psychological capital, Self-efficacy
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    In the era of big data, the logistics industry is undergoing profound changes. The digitalization construction not only brings new operating modes and business opportunities to the logistics industry, but also poses new challenges to the professional ...

    In the era of big data, the logistics industry is undergoing profound changes. The digitalization construction not only brings new operating modes and business opportunities to the logistics industry, but also poses new challenges to the professional skills of logistics personnel. The mathematics-related courses in university logistics majors bear an important task of logistics digitalization. Therefore, universitys and universities in logistics majors also face new requirements in cultivating students in mathematics-related courses. The academic achievement sense of logistics majors in mathematics-related courses directly affects their learning motivation and even employment. Therefore, it is necessary to pay special attention to the academic achievement of logistics majors in mathematics-related courses. This study aims to explore the current situation and role relationship between learning stress, psychological capital, and self-efficacy in mathematics-related course modules of logistics majors, and to investigate the mediating effects of psychological capital and self-efficacy. The study takes logistics majors at 7 universities in Zhejiang Province in June 2024 as the research object, distributes the questionnaires on learning stress, psychological capital, and academic achievement to collect the final data of logistics majors in mathematics-related course modules. The data is analyzed using SPSS 25.0 statistical software for descriptive statistics, one-way ANOVA, correlation analysis, and regression analysis. The AMOS 24.0 software is used to establish structural equation models and mediating effects, including the mediating effects of psychological capital and self-efficacy. The research results are as follows: First, there are significant population variables in terms of gender, major choice, being an only child, and place of origin in the logistics majors' academic achievement in mathematics-related course modules. Second, the learning stress in mathematics-related course modules has a negative impact on the academic achievement of logistics majors. Third, the learning stress in mathematics-related course modules has a negative impact on psychological capital of logistics majors. Fourth, the learning stress in mathematics-related course modules has a negative impact on self-efficacy of logistics majors. Fifth, psychological capital has a positive impact on the academic achievement of logistics majors in mathematics-related course modules. Sixth, self-efficacy has a positive impact on the academic achievement of logistics students in learning mathematics modules. Seventh, psychological capital has a significant mediating effect between learning stress and academic achievement of logistics major students in learning mathematics course modules. Eighth, self-efficacy has a significant mediating effect between learning stress and academic achievement of logistics major university students in learning mathematics course modules. Based on the findings, this study makes the following educational recommendations: Reducing learning stress in mathematics courses for logistics majors can enhance psychological capital, self-efficacy, and academic achievement. Learning stress negatively impacts academic performance but can be mitigated by improving psychological resources and offering timely support. Universities should guide students in managing stress, fostering a positive learning environment, and promoting mental health to improve academic outcomes. Keywords: University students majoring in logistics, Mathematics courses, Learning stress, Academic achievement, Psychological capital, Self-efficacy

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    목차 (Table of Contents)

    • I. Introduction1
    • 1. Research Necessity and Purpose 1
    • 2. Research Questions8
    • 3. Definition of Terms 9
    • 1) Learning Stress9
    • I. Introduction1
    • 1. Research Necessity and Purpose 1
    • 2. Research Questions8
    • 3. Definition of Terms 9
    • 1) Learning Stress9
    • 2) Academic Achievement10
    • 3) Psychological Capital 10
    • 4) Self-efficacy 11
    • Ⅱ. Theoretical Background 12
    • 1. Mathematics Course in Logistics Major 12
    • 1) Concept of Logistics Education12
    • 2) Characteristic of Logistics Education 15
    • 2. Learning Stress 26
    • 1) The Concept of Learning Stress26
    • 2) Measurement of Learning Stress 28
    • 3) Prior Research of Learning Stress 29
    • 3. Academic Achievement32
    • 1) The Concept of Academic Achievement 32
    • 2) Measurement of Academic Achievement35
    • 3) Prior Research of Academic Achievement 38
    • 4. Psychological Capital 40
    • 1) Concept of Psychological Capital40
    • 2) Measurement of Psychological Capital 43
    • 3) Prior Research on Psychological Capital 45
    • 5. Self-efficacy 48
    • 1) Concept of Self-efficacy 48
    • 2) Measurement of Self-efficacy 50
    • 3) Prior Research on Self-efficacy 52
    • 6. Relationship between Variables55
    • 1) The Relationship between Learning Stress and Academic
    • Achievement 55
    • 2) The Relationship between Learning Stress and Psychological
    • Capital57
    • 3) The Relationship between Learning Stress and Self-efficacy 59
    • 4) The Relationship between Psychological Capital and Academic
    • Achievement 62
    • 5) The Relationship between Self-efficacy and Academic
    • Achievement 64
    • 6) The Relationship between Learning Stress, Academic
    • Achievement and Psychological Capital66
    • 7) The Relationship between Learning Stress, Academic
    • Achievement and Self-efficacy67
    • 8) The Relationship between Learning Stress, Academic
    • Achievement, Psychological Capital and Self-efficacy69
    • Ⅲ. Research Methods 73
    • 1. Research Models and Assumptions 73
    • 1) Research Models 73
    • 2) Research Hypotheses74
    • 2. Research Subjects75
    • 3. Research Tools 77
    • 1) Learning Stress Scale 78
    • 2) Academic Achievement Scale81
    • 3) Psychological Capital Scale 84
    • 4) Self-efficacy Scale 88
    • 4. Research Process 91
    • 1) Preliminary Research91
    • 2) Formal Research93
    • 5. Data Analysis 94
    • IV. Research Results 97
    • 1. Descriptive Statistical 97
    • 2. Demographic Differences in Variables 98
    • 1) Differential Analysis of Learning Stress 99
    • 2) Differential Analysis of Psychological Capital 103
    • 3) Differential Analysis of Self-efficacy 107
    • 4) Differential Analysis of Academic Achievement111
    • 3. Correlation Analysis among Variables115
    • 4. Regression Analysis among Variables118
    • 1) The Impact of Learning Stress on Academic Achievement ·118
    • 2) The Impact of Learning Stress on Psychological Capital 120
    • 3) The Impact of Learning Stress on Self-efficacy 122
    • 4) The Impact of Psychological Capital on Academic
    • Achievement 123
    • 5) The Impact of Self-efficacy on Academic Achievement125
    • 5. Mediating Effect 127
    • 1) Model Construction and Model Fitting 127
    • 2) Path Analysis128
    • 3) Mediating Effects Test Results130
    • 6. Results of Research Hypothesis Testing 132
    • V. Conclusion133
    • 1. Conclusion and Discussion133
    • 2. Suggestion and Limitations 140
    • References148
    • Appendix172
    • 국문초록 175
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