Authorship Patterns in Lifelong Learning Literature Emanating from Asia during 2000–2024: A Twofold Bibliometric and Data-Analytical Approach

Background: Lifelong learning is an established field because of its importance in supporting continuing education, career advancement, and societal progress. Examining authorship patterns can reveal temporal, institutional, national, and gender-related dimensions of research development.
Objective: This study analyzes authorship patterns in English-language journal articles on Lifelong Learning emanating from Asia during 2000–2024, focusing on annual scientific production, average citation count per year, author productivity, author-productivity distribution in relation to Lotka’s law, affiliation output, Single Country Publications (SCP), Multiple Country Publications (MCP), citation counts, and name-based gender classification by author position.
Methods: Bibliographic records were retrieved from OpenAlex in June 2026 using the search string “lifelong learning”. Eligibility was restricted to English-language journal articles published during 2000–2024 and meeting the Asian geographical criterion. The retrieval yielded 3,103 records, downloaded in CSV format. Analysis used Bibliometrix/Biblioshiny for bibliometric indicators and OpenRefine with Genderize.io for data wrangling and name-based gender classification. Bibliometrix loaded 3,099 records (99.817%).
Results: Annual scientific production generally increased, whereas average citation counts varied across years. Marjaan Laal was the most prolific author with 11 documents. Of 7,292 authors represented in the author-productivity distribution, 6,703 (91.92%) contributed one document, broadly consistent with the pattern predicted by Lotka’s law. Universiti Kebangsaan Malaysia led affiliation output with 123 articles. China recorded the highest SCP (558) and MCP (41), whereas Turkey had the highest citation count (1,721), followed by China (1,312). Of 7,491 names queried through Genderize.io, 421 returned null values; 4,038 (53.91%) were classified as male and 3,032 (40.47%) as female.
Conclusion: The study provides a quantitative baseline of Lifelong Learning scholarship in Asia, integrating production, citation accumulation, author productivity, institutional and national contributions, and name-based gender classification. Despite metadata limitations, findings can inform decisions. Future research should compare databases, test Lotka’s law, examine collaboration and thematic change, and develop reproducible workflows.

Authorship pattern; Bibliometric analysis; Gender analysis; Lifelong learning

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