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Journal of library and information science in agriculture

   

Factors Influencing Academic Researchers,Academic Resilience Based on Information Ecology Theory

CUI Xiaoxu   

  1. Peking University School of International Studies Library, Beijing 100871
  • Received:2026-07-09

Abstract:

[Purpose/Significance] As higher education and scientific research scale continue to expand globally, competition among universities in these fields has become increasingly intense and complex. Throughout their research careers, contemporary university researchers are confronted with a series of pervasive academic dilemmas, including persistent research bottlenecks in project exploration, rigorous and standardized academic assessment systems, insufficient scientific research resources, and overlapping academic work pressure. These adverse factors can easily trigger academic anxiety, research burnout, and passive research attitudes, which greatly hinder the sustainable development of individual academic careers and restrict the high-quality progress of university scientific research projects. Academic resilience, as a core psychological and behavioral ability that enables researchers to cope with academic setbacks, resist academic risks and recover from academic predicaments, has become a key variable to solve the above practical problems. Nevertheless, existing domestic and foreign studies mostly focus on the influencing factors of academic burnout, academic pressure and research performance of university researchers, while systematic research on the formation mechanism and driving path of academic resilience is relatively scarce and fragmented. Most previous studies lack a holistic theoretical framework and ignore the interactive influence of multiple environmental and individual factors on academic resilience, failing to fully explain how external academic environments transform into internal resilience motivation of researchers. [Method/Process] Against this background, this study takes university researchers as the research object, and systematically explores the formative mechanism of their academic resilience based on information ecology theory. This research fills the theoretical gap in the interdisciplinary research of information ecology and academic psychology, improves the theoretical system of academic resilience research in the field of higher education, and provides a new analytical perspective for understanding the adaptive behavior of scientific researchers under complex academic environments. In practice, the research conclusions can effectively alleviate the problem of academic burnout among university researchers, help resolve practical academic predicaments, promote the construction of a positive, healthy and sustainable academic ecology, and provide important practical support for stabilizing the team of university scientific researchers and improving the overall efficiency of university scientific research. [Results/Conclusions] The empirical test results effectively verify the core research hypotheses of this study and draw valuable research conclusions. Firstly, individual subjective factors are the core driving factors of academic resilience of university researchers. Specifically, positive academic emotions and scientific academic cognition can significantly and positively predict the level of academic resilience, which means researchers with positive research emotions and clear academic cognition are more capable of coping with academic setbacks. Secondly, different from traditional cognitive views, external environmental factors such as academic evaluation mechanism and academic pressure do not have a direct significant impact on academic resilience. However, these two factors play a positive indirect role in improving academic resilience through complete mediation effects. A standardized and reasonable academic evaluation mechanism can optimize researchers' academic cognition level, while moderate academic pressure can stimulate positive academic emotions of researchers, and ultimately jointly promote the improvement of academic resilience. Based on the above conclusions, this study puts forward targeted and operable practical optimization suggestions for university scientific research management and talent training, including strengthening humanistic care for scientific researchers, establishing a long-term mechanism to resolve negative academic emotions, optimizing the scientific and standardized academic evaluation system, and guiding the rational regulation of academic pressure. In terms of research limitations, this study only adopts cross-sectional questionnaire data, which cannot reflect the dynamic evolution process of academic resilience of researchers in different career stages. In addition, this study does not discuss the heterogeneity of research disciplines and academic titles, and the regulatory effect of other potential variables is not included in the model. Future research can adopt longitudinal tracking research methods to explore the dynamic development law of academic resilience, and introduce regulatory variables such as disciplinary differences and research experience to refine the research model, so as to form a more comprehensive and in-depth theoretical system of academic resilience of university researchers.

Key words: academic resilience, university researchers, influencing factors Academic sentiment, information ecology theory

CLC Number: 

  • G251

Fig.1

Research model of influencing factors of academic resilience among university researchers"

Table 1

Descriptive statistics of survey samples"

属性 指标 人数/人 比例/% 属性 指标 人数/人 比例/%
性别 男 203 51.39 学历 本科及以下 11 2.78
女 192 48.61 硕士 138 34.94
年龄 25~35岁 120 30.37 博士 246 62.28
36~45岁 189 47.85 职称 无 12 3.03
46~60岁 86 21.78 初级 34 8.61
学科 人文学科 92 23.29 中级 86 21.77
社会学科 187 47.34 副高级 197 49.87
自然学科 116 29.37 正高级 78 19.75

Table 2

Reliability analysis results of the scales"

变量 Cronbach's α 测度项 因子载荷 CR AVE
学术情感 0.824 ACE_1 0.832 0.868 0.688
ACE_2 0.813
ACE_3 0.844
学术认知 0.851 ACC_1 0.853 0.817 0.694
ACC_2 0.842
ACC_3 0.803
学术信息过载 0.864 AIO_1 0.848 0.877 0.704
AIO_2 0.857
AIO_3 0.811
技术示能 0.803 TAE_1 0.863 0.879 0.709
TAE_2 0.824
TAE_3 0.839
学术评价 0.822 AET_1 0.847 0.857 0.667
AET_2 0.816
AET_3 0.785
学术压力 0.842 APS_1 0.852 0.872 0.695
APS_2 0.836
APS_3 0.812
学术韧性 0.912 ARE_1 0.874 0.887 0.726
ARE_2 0.852
ARE_3 0.829

Table 3

Discriminant validity of measurement scales"

变量 ACE ACC AIO TAE AET APS ARE
ACE 0.829
ACC 0.578 0.833
AIO 0.270 0.476 0.839
TAE 0.532 0.335 0.211 0.842
AET 0.414 0.600 0.123 0.233 0.817
APS 0.655 0.338 0.215 0.252 0.215 0.837
ARE 0.467 0.378 0.583 0.287 0.316 0.438 0.852

Table 4

Model fit indices"

指标 CMIN/DF(<3) CFI(>0.9) GFI(>0.9) TLI(>0.9) RMSEA(<0.08)
数据结果 1.684 0.965 0.953 0.951 0.047

Table 5

Path coefficients and hypothesis testing results"

假设 路径关系 标准化系数 S.E. C.R. p值 验证结果
H1 ACE→ARE 0.358 0.075 3.128 *** 支持
H2 ACC→ARE 0.473 0.070 3.628 *** 支持
H3 AIO→ACE -0.186 0.071 3.144 *** 支持
H4 TAE→ACC 0.285 0.060 2.712 ** 支持
H5 AET→ACE 0.294 0.064 2.922 ** 支持
H6 AET→ARE 0.219 0.061 3.270 0.165 不支持
H7 APS→ACC -0.327 0.061 3.660 *** 支持
H8 APS→ARE 0.268 0.051 2.887 0.127 不支持

Fig.2

Empirical results of the research model for academic resilience influencing factors of university researchers"

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