Galiya A. Abayeva, Gulzhan S. Orazayeva, Saltanat J. Omirbek, G. Ibatova, V. Zakirova, Vera K. Vlasova
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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. 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引用次数: 0
摘要
泛在学习的概念已经作为一种教学方法出现,以应对移动、无线通信和传感技术的进步。泛在学习领域的特点是进展迅速,因此难以保持其发展的当前知识。文献计量分析的实施将有助于跟踪其发展和现状。本研究的目的是对泛在学习领域进行彻底的文献计量学检查。本研究旨在通过分析学术著作来辨别学科中的重要属性、模式和影响者。本研究的主要目的是全面描述泛在学习研究中使用的数据集所表现出的显著特征和模式,即Scopus、Web of Science(WoS)和合并数据集。此外,该研究试图追踪该领域出版物的历史发展,并确定对该领域产生重大影响的最值得注意的出版物和作者。本研究对泛在学习进行了广泛的文献计量分析,检查了Scopus、WoS和合并数据集的输出。它强调了该领域的发展和对不同数据源的日益使用,Scopus和合并后的数据集揭示了更广泛的见解。分析显示,兴趣在2016年达到峰值,随后可能由于近期数据不完整而下降。文档(主要是文章)因数据库而异,突出了每个数据库的独特贡献。该研究确定“计算机科学讲义”和“普遍学习”是主要的研究来源。它承认黄是一位极具影响力的作家,亚洲机构在研究成果方面处于领先地位。然而,西方机构在WoS和合并数据库中也表现出强大的代表性。尽管引用总数各不相同,但中国、瑞士和爱尔兰等国在这一领域做出了重大贡献。“移动学习”和“生活日志”等术语在连接研究集群方面发挥着至关重要的作用,而主题地图则揭示了移动学习和学习分析等不断发展的趋势。通过网络分析阐明了泛在学习中的协作结构和关键人物,强调了跨数据库分析对全面了解该领域的重要性。
A cross-database bibliometric analysis of ubiquitous learning: Trends, influences, and future directions
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.