Influence of continuous learning on the academic research ability of Chinese university teachers

This study investigates the influence of continuous learning on the academic research abilities of university teachers in China, focusing on the dimensions of learning frequency, learning modes, and resource input. Drawing upon Self-Determination Theory and Social Cognitive Theory, the research employs a quantitative design, utilizing stratified random sampling to survey 322 teachers across eastern, central, and western regions of China. Results indicate that continuous learning behaviors significantly predict academic competence, with higher learning frequency, collaborative learning modes, and greater resource investment positively associated with increased research output. Multiple regression analysis demonstrates that these three variables collectively explain 38.6% of the variance in academic competence. Findings further reveal disparities across regions and disciplines, highlighting resource imbalances between eastern and western institutions. The study provides both theoretical insights and practical strategies for improving teacher development, such as differentiated resource allocation, optimization of blended learning models, and flexible time management systems. Overall, the research underscores the critical role of continuous learning in strengthening academic capacity and offers evidence-based recommendations for enhancing professional development policies in higher education.

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Publication Details

Journal
International Journal of Innovative Research and Scientific Studies
Published
2025-09-26
DOI
https://doi.org/10.53894/ijirss.v8i6.10274
Primary Topic
Educational Innovations and Challenges
Type
article
Field-Weighted Citation Impact
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article

Influence of continuous learning on the academic research ability of Chinese university teachers

Y. Liu, Yan Zhu, Jun Tan, Shiou Yih Lee et al.
International Journal of Innovative Research and Scientific Studies
Educational Innovations and Challenges
article

Influence of continuous learning on the academic research ability of Chinese university teachers

Y. Liu, Yan Zhu, Jun Tan, Shiou Yih Lee, Yang Liu
article en

Abstract

This study investigates the influence of continuous learning on the academic research abilities of university teachers in China, focusing on the dimensions of learning frequency, learning modes, and resource input. Drawing upon Self-Determination Theory and Social Cognitive Theory, the research employs a quantitative design, utilizing stratified random sampling to survey 322 teachers across eastern, central, and western regions of China. Results indicate that continuous learning behaviors significantly predict academic competence, with higher learning frequency, collaborative learning modes, and greater resource investment positively associated with increased research output. Multiple regression analysis demonstrates that these three variables collectively explain 38.6% of the variance in academic competence. Findings further reveal disparities across regions and disciplines, highlighting resource imbalances between eastern and western institutions. The study provides both theoretical insights and practical strategies for improving teacher development, such as differentiated resource allocation, optimization of blended learning models, and flexible time management systems. Overall, the research underscores the critical role of continuous learning in strengthening academic capacity and offers evidence-based recommendations for enhancing professional development policies in higher education.

International Journal of Innovative Research and Scientific StudiesVol. 8(6)
INTI International University (MY), Northwestern Polytechnical University (CN), Shinawatra University (TH)
Openalex Percentile: Top 61%
Educational Innovations and Challenges
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Influence of continuous learning on the academic research ability of Chinese university teachers — Y. Liu, Yan Zhu, et al. · International Journal of Innovative Research and Scientific Studies (2025) | TGRS Research Map | TGRS