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A cross-database bibliometric analysis of ubiquitous learning: Trends, influences, and future directions
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The concept of ubiquitous learning has emerged as a pedagogical approach in response to the advancements made in mobile, wireless communication, and sensing technologies. The domain of ubiquitous learning is distinguished by swift progression, thereby presenting a difficulty in maintaining current knowledge of its developments. The implementation of bibliometric analysis would enable the tracking of its development and current status. The objective of the present investigation is to perform a thorough bibliometric examination of the domain of ubiquitous learning. This research aims to discern significant attributes, patterns, and influencers within the discipline by analyzing scholarly works. The primary objective of this study is to provide a comprehensive depiction of the salient characteristics and patterns exhibited by the datasets employed in ubiquitous learning research, namely Scopus, Web of Science (WoS), and merged datasets. Additionally, the study seeks to trace the historical development of publications in this domain and to ascertain the most noteworthy publications and authors that have exerted a significant impact on this field. This study provides an extensive bibliometric analysis of ubiquitous learning, examining output from Scopus, WoS, and a merged dataset. It highlights the field’s growth and the rising use of diverse data sources, with Scopus and the merged dataset revealing broader insights. The analysis reveals an interest peak in 2016 and a subsequent decline likely due to incomplete recent data. Documents, predominantly articles, differ across databases, underscoring the unique contributions of each. The study identifies “Lecture Notes in Computer Science” and “Ubiquitous Learning” as major research sources. It recognizes Hwang, G.-J. as a highly influential author, with Asian institutions leading in research output. However, Western institutions also show strong representation in WoS and merged databases. Despite variations in total citation counts, countries like China, Switzerland, and Ireland contribute significantly to the field. Terms like “mobile learning” and “life log” have vital roles in bridging research clusters, while thematic maps reveal evolving trends like mobile learning and learning analytics. The collaborative structure and key figures in ubiquitous learning are illuminated through network analysis, emphasizing the importance of cross-database analysis for a comprehensive view of the field.
Title: A cross-database bibliometric analysis of ubiquitous learning: Trends, influences, and future directions
Description:
The concept of ubiquitous learning has emerged as a pedagogical approach in response to the advancements made in mobile, wireless communication, and sensing technologies.
The domain of ubiquitous learning is distinguished by swift progression, thereby presenting a difficulty in maintaining current knowledge of its developments.
The implementation of bibliometric analysis would enable the tracking of its development and current status.
The objective of the present investigation is to perform a thorough bibliometric examination of the domain of ubiquitous learning.
This research aims to discern significant attributes, patterns, and influencers within the discipline by analyzing scholarly works.
The primary objective of this study is to provide a comprehensive depiction of the salient characteristics and patterns exhibited by the datasets employed in ubiquitous learning research, namely Scopus, Web of Science (WoS), and merged datasets.
Additionally, the study seeks to trace the historical development of publications in this domain and to ascertain the most noteworthy publications and authors that have exerted a significant impact on this field.
This study provides an extensive bibliometric analysis of ubiquitous learning, examining output from Scopus, WoS, and a merged dataset.
It highlights the field’s growth and the rising use of diverse data sources, with Scopus and the merged dataset revealing broader insights.
The analysis reveals an interest peak in 2016 and a subsequent decline likely due to incomplete recent data.
Documents, predominantly articles, differ across databases, underscoring the unique contributions of each.
The study identifies “Lecture Notes in Computer Science” and “Ubiquitous Learning” as major research sources.
It recognizes Hwang, G.
-J.
as a highly influential author, with Asian institutions leading in research output.
However, Western institutions also show strong representation in WoS and merged databases.
Despite variations in total citation counts, countries like China, Switzerland, and Ireland contribute significantly to the field.
Terms like “mobile learning” and “life log” have vital roles in bridging research clusters, while thematic maps reveal evolving trends like mobile learning and learning analytics.
The collaborative structure and key figures in ubiquitous learning are illuminated through network analysis, emphasizing the importance of cross-database analysis for a comprehensive view of the field.
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