Kannan Thamizhiniyan, Kathirkamanathan Chellamani, Abdul Huq Jahitha Begum, Sheriff Naseema
{"title":"终身学习中的科学生产力与合作网络:纵向文献计量分析(1963-2022 年)","authors":"Kannan Thamizhiniyan, Kathirkamanathan Chellamani, Abdul Huq Jahitha Begum, Sheriff Naseema","doi":"10.5530/jscires.13.1.17","DOIUrl":null,"url":null,"abstract":"In the post-pandemic era, lifelong learning (LLL) emerged as the key to professional development and the core competency of all disciplines. Even globally, there is a dearth of evidence based bibliometric analysis, notably on LLL. This study addresses this gap by examining the data retrieved from the Elsevier Scopus database. A systematic search method was adopted to retrieve 1806 publications from 790 journals from 1963 to 2022. The R package, Biblioshiny, was used for data analysis, including productivity/performance analysis, citation analysis, and collaboration network analysis of social structure. The findings showed that the number of publications has significantly increased over time. A large number of studies were published in 2022. Overall, 85 countries contributed to LLL. Among them, the United States was the most productive with 787 publications, and the United Kingdom was the country with 4731 citations. Learning was the trending topic, and skill development was an emerging theme in LLL. The results will aid the stakeholders in identifying largely unexplored areas of research that need more attention and funding. This study outlines not only the current scientific developments but also the potential future of LLL research. This study will also be used as a resource for researchers and teachers in LLL. Future research directions in this area of knowledge are also outlined.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Scientific Productivity and Collaboration Networks in Lifelong Learning: A Longitudinal Bibliometric Analysis (1963-2022)\",\"authors\":\"Kannan Thamizhiniyan, Kathirkamanathan Chellamani, Abdul Huq Jahitha Begum, Sheriff Naseema\",\"doi\":\"10.5530/jscires.13.1.17\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the post-pandemic era, lifelong learning (LLL) emerged as the key to professional development and the core competency of all disciplines. Even globally, there is a dearth of evidence based bibliometric analysis, notably on LLL. This study addresses this gap by examining the data retrieved from the Elsevier Scopus database. A systematic search method was adopted to retrieve 1806 publications from 790 journals from 1963 to 2022. The R package, Biblioshiny, was used for data analysis, including productivity/performance analysis, citation analysis, and collaboration network analysis of social structure. The findings showed that the number of publications has significantly increased over time. A large number of studies were published in 2022. Overall, 85 countries contributed to LLL. Among them, the United States was the most productive with 787 publications, and the United Kingdom was the country with 4731 citations. Learning was the trending topic, and skill development was an emerging theme in LLL. The results will aid the stakeholders in identifying largely unexplored areas of research that need more attention and funding. This study outlines not only the current scientific developments but also the potential future of LLL research. This study will also be used as a resource for researchers and teachers in LLL. Future research directions in this area of knowledge are also outlined.\",\"PeriodicalId\":43282,\"journal\":{\"name\":\"Journal of Scientometric Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2024-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Scientometric Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5530/jscires.13.1.17\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Scientometric Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5530/jscires.13.1.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
Scientific Productivity and Collaboration Networks in Lifelong Learning: A Longitudinal Bibliometric Analysis (1963-2022)
In the post-pandemic era, lifelong learning (LLL) emerged as the key to professional development and the core competency of all disciplines. Even globally, there is a dearth of evidence based bibliometric analysis, notably on LLL. This study addresses this gap by examining the data retrieved from the Elsevier Scopus database. A systematic search method was adopted to retrieve 1806 publications from 790 journals from 1963 to 2022. The R package, Biblioshiny, was used for data analysis, including productivity/performance analysis, citation analysis, and collaboration network analysis of social structure. The findings showed that the number of publications has significantly increased over time. A large number of studies were published in 2022. Overall, 85 countries contributed to LLL. Among them, the United States was the most productive with 787 publications, and the United Kingdom was the country with 4731 citations. Learning was the trending topic, and skill development was an emerging theme in LLL. The results will aid the stakeholders in identifying largely unexplored areas of research that need more attention and funding. This study outlines not only the current scientific developments but also the potential future of LLL research. This study will also be used as a resource for researchers and teachers in LLL. Future research directions in this area of knowledge are also outlined.