JOURNAL ARTICLE

Transitions in older adulthood: A conceptual proposal incorporating the maker movement, lifelong learning, and information behavior.

  • Published In: Journal of the Association for Information Science & Technology, 2026, v. 77, n. 2. P. 383 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Jung, Yong Ju; Rubenstein, Ellen L.; Park, Hyewon 3 of 3

Abstract

Older adults comprise a group that has recently gained attention for broadening the maker movement. Research has shown that older adults have benefited from makerspaces and making with both tangible and digital technologies, especially in enhancing digital literacy. However, most previous research has not thoroughly considered older adults' unique situations and life transitions, such as retirement, and their lifelong learning beyond obtaining certain technical skills in makerspaces. In this regard, this conceptual paper proposes a theoretical foundation by unpacking the connections of theories related to the maker movement, information behavior, lifelong learning, and transitions that older adults experience. Considering the process of a transition—from an event, to understanding, negotiating, resolving, and to new life—this paper discusses how theories of lifelong learning (e.g., transformative learning, functionalist paradigm, and communities of practice) and the basic concepts of the maker movement (e.g., maker mindset) intersect with older adults' transitions and information behavior. Then, we conclude with some potential applications of our conceptual proposal to practice and research. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of the Association for Information Science & Technology. 2026/02, Vol. 77, Issue 2, p383
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2026
  • ISSN:2330-1635
  • DOI:10.1002/asi.25007
  • Accession Number:191105244
  • Copyright Statement:Copyright of Journal of the Association for Information Science & Technology is the property of Wiley-Blackwell 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.)

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