Bibliometric Scopus data for Leaning Analytics
收藏DataCite Commons2025-04-01 更新2025-04-16 收录
下载链接:
https://ieee-dataport.org/documents/bibliometric-scopus-data-leaning-analytics
下载链接
链接失效反馈官方服务:
资源简介:
This study investigates the landscape of scientific publications in learning analytics from 2013 to the present using bibliometric indicators. A comprehensive search strategy identified 648 relevant publications from the Scopus database. Descriptive and bibliometric analyses were conducted to gain insights. Findings reveal the Journal of Learning Analytics as a prominent contributor, indicating its significance in the field. "Computers in Human Behavior" exhibited substantial impact with high h-index (23) and g-index (32), reflecting the dissemination of highly cited articles. An upward trend in publication numbers over time signifies growing interest in learning analytics research. Australia emerged as the most influential country, suggesting significant contributions to the field. Authorship patterns predominantly featured single-authored documents, with two or three-author collaborations being common. Larger multi-author collaborations were less frequent.
提供机构:
IEEE DataPort
创建时间:
2025-04-01



