Research on the Internal Relationships in Undergraduates' Online Learning Competence Based on Structural Equation Modeling

Shurui LIU; Haonan ZHANG; Zhenting YANG; Kunjie MA; Zhenhui SUN; Yingying ZOU; Zhihong YANG

doi:10.12259/j.issn.2095-610X.S20250518

Volume 46 Issue 5

May 2025

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Article Navigation > Journal of Kunming Medical University > 2025 > 46(5): 149-156

Shurui LIU, Haonan ZHANG, Zhenting YANG, Kunjie MA, Zhenhui SUN, Yingying ZOU, Zhihong YANG. Research on the Internal Relationships in Undergraduates' Online Learning Competence Based on Structural Equation Modeling[J]. Journal of Kunming Medical University, 2025, 46(5): 149-156. doi: 10.12259/j.issn.2095-610X.S20250518

Citation:

Shurui LIU, Haonan ZHANG, Zhenting YANG, Kunjie MA, Zhenhui SUN, Yingying ZOU, Zhihong YANG. Research on the Internal Relationships in Undergraduates' Online Learning Competence Based on Structural Equation Modeling[J]. Journal of Kunming Medical University, 2025, 46(5): 149-156. doi: 10.12259/j.issn.2095-610X.S20250518

Citation:

Shurui LIU, Haonan ZHANG, Zhenting YANG, Kunjie MA, Zhenhui SUN, Yingying ZOU, Zhihong YANG. Research on the Internal Relationships in Undergraduates' Online Learning Competence Based on Structural Equation Modeling[J]. Journal of Kunming Medical University, 2025, 46(5): 149-156. doi: 10.12259/j.issn.2095-610X.S20250518

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Research on the Internal Relationships in Undergraduates' Online Learning Competence Based on Structural Equation Modeling

doi: 10.12259/j.issn.2095-610X.S20250518

1.
First School of Clinical Medicine，Kunming Medical University，Kunming Yunnan 650032
2.
School of Basic Medical Sciences，Kunming Medical University，Kunming Yunnan 650500，China

Received Date: 2025-02-20
Publish Date: 2025-05-30

Abstract

Abstract

Objective To explore the interaction mechanisms among different dimensions of online learning competence in undergraduates, providing scientific evidence for optimizing software design and online education strategies. Methods A cross-sectional study was conducted with 347 undergraduates from Kunming Medical University via an online questionnaire in October 2024. Reliability testing and exploratory factor analysis were performed using SPSS 26.0, while structural equation modeling was constructed with Amos 24.0. Results Driving force directly and positively influenced regulatory force （β = 0.778, P < 0.001） and reciprocal force （β = 0.302, P = 0.003）, but had no significant direct effect on adaptive force （β = 0.131, P = 0.182）. Regulatory force and reciprocal force both exerted direct positive effects on adaptive force （β = 0.262, P = 0.022; β = 0.410, P < 0.001）. The indirect effect of driving force on adaptive force accounted for 78.1% of the total effect （P = 0.007）, with regulatory force showing a significant mediating role （β = 0.178, P = 0.023）, while reciprocal force alone did not （β = 0.108, P = 0.060）. A chain mediating effect （driving force→regulatory force→reciprocal force→adaptive force） was confirmed （β = 0.124, P = 0.004）. Conclusion Driving force serves as the core of online learning competence, and adaptive capacity is enhanced through regulatory and reciprocal forces. To promote knowledge internalization and adaptability, it is required to optimize feedback mechanisms and deepen interactive designs in online learning platforms.
- Structural equation modeling,
- Online learning ability,
- Mediation effect,
- Undergraduate,
- Internal relationships

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References(25)

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