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Lifelong learning among older adults in China: Characteristics, influencing factors, and heterogeneity analysis.

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Title: Lifelong learning among older adults in China: Characteristics, influencing factors, and heterogeneity analysis.
Authors: Wu, Feng (AUTHOR), Jiang, Fengjuan (AUTHOR)
Source: Educational Gerontology. Jul2026, Vol. 52 Issue 7, p781-797. 17p.
Subjects: Digital technology, Cross-sectional method, Secondary analysis, Income, Research funding, Sex distribution, Internet, Population geography, Multivariate analysis, Descriptive statistics, Surveys, Aging, Continuing education, Learning strategies, Literacy, Interpersonal relations, Social support, Social participation, Friendship, Regression analysis
Geographic Terms: China
Abstract: This study analyzes lifelong learning participation among older adults in China, drawing on six waves of data from Chinese General Social Survey (CGSS). Despite overall participation remains low – over 80% report infrequent engagement – a modest upward trend is observed, with the proportion of active learners rising from 7.6% to 11.8% over the decade. Internet use is positively associated with learning engagement, underscoring the role of digital technologies in promoting access to educational opportunities. However, structural barriers such as digital illiteracy and limited access to technology perpetuate disparities by region, income, and education. Supportive social ties, particularly friendships, are linked to increased participation, while certain forms of social interaction may compete with time for learning. These findings contribute to research on active aging and digital inclusion, highlighting the need for policies that address infrastructural gaps, promote affordability, and deliver targeted digital literacy initiatives to support equitable lifelong learning in later life. [ABSTRACT FROM AUTHOR]
Copyright of Educational Gerontology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Lifelong learning among older adults in China: Characteristics, influencing factors, and heterogeneity analysis.
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  Data: <searchLink fieldCode="AR" term="%22Wu%2C+Feng%22">Wu, Feng</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jiang%2C+Fengjuan%22">Jiang, Fengjuan</searchLink> (AUTHOR)
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  Data: This study analyzes lifelong learning participation among older adults in China, drawing on six waves of data from Chinese General Social Survey (CGSS). Despite overall participation remains low – over 80% report infrequent engagement – a modest upward trend is observed, with the proportion of active learners rising from 7.6% to 11.8% over the decade. Internet use is positively associated with learning engagement, underscoring the role of digital technologies in promoting access to educational opportunities. However, structural barriers such as digital illiteracy and limited access to technology perpetuate disparities by region, income, and education. Supportive social ties, particularly friendships, are linked to increased participation, while certain forms of social interaction may compete with time for learning. These findings contribute to research on active aging and digital inclusion, highlighting the need for policies that address infrastructural gaps, promote affordability, and deliver targeted digital literacy initiatives to support equitable lifelong learning in later life. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Educational Gerontology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1080/03601277.2025.2515565
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      – Code: eng
        Text: English
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        PageCount: 17
        StartPage: 781
    Subjects:
      – SubjectFull: Digital technology
        Type: general
      – SubjectFull: Cross-sectional method
        Type: general
      – SubjectFull: Secondary analysis
        Type: general
      – SubjectFull: Income
        Type: general
      – SubjectFull: Research funding
        Type: general
      – SubjectFull: Sex distribution
        Type: general
      – SubjectFull: Internet
        Type: general
      – SubjectFull: Population geography
        Type: general
      – SubjectFull: Multivariate analysis
        Type: general
      – SubjectFull: Descriptive statistics
        Type: general
      – SubjectFull: Surveys
        Type: general
      – SubjectFull: Aging
        Type: general
      – SubjectFull: Continuing education
        Type: general
      – SubjectFull: Learning strategies
        Type: general
      – SubjectFull: Literacy
        Type: general
      – SubjectFull: Interpersonal relations
        Type: general
      – SubjectFull: Social support
        Type: general
      – SubjectFull: Social participation
        Type: general
      – SubjectFull: Friendship
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      – SubjectFull: Regression analysis
        Type: general
      – SubjectFull: China
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    Titles:
      – TitleFull: Lifelong learning among older adults in China: Characteristics, influencing factors, and heterogeneity analysis.
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            NameFull: Wu, Feng
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            NameFull: Jiang, Fengjuan
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          Dates:
            – D: 01
              M: 07
              Text: Jul2026
              Type: published
              Y: 2026
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              Value: 52
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