文献计量分析:发现学习研究中的合作网络

Andi Suparjo, Edwin Musdi, Y. Yerizon, I. Arnawa
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引用次数: 0

摘要

本研究确定了与发现式学习有关的出版物。发现式学习是一种学习模式,鼓励学生通过自我发现和研究来主动学习,从而使所取得的成果持久而难以忘怀。本研究旨在通过文献计量学研究,识别和分析 2014-2023 年间在几种著名国际期刊上发表的研究发现式学习的文章。文献计量学分析得出了四项结论:在过去十年中,Scopus 索引期刊上有关发现学习的论文每年都呈现出一种流动和平衡的模式;在发表论文最多的十种期刊中,有 328 种期刊发表了论文。排名第一的期刊发表了 15 篇文章,排名第十的期刊发表了 5 篇文章;2020 年发表的文章被引用次数最多,共计 1101 次。被引用次数最多的文章作者是B.R. Goldsmith,共被引用241次;作者的关键词中使用频率最高的前三位是发现、机器和机器学习
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bibliometric Analysis: Collaboration Networks In Discovery Learning Research
This research identifies publications related to Discovery learning. Discovery learning is a learning model that encourages active learning in students through self-discovery and research so that the results achieved are long-lasting and difficult to forget. This research aims to identify and analyze articles researching Discovery Learning that have been published in several reputable international journals published in the 2014-2023 period, which was carried out using bibliometric studies. Bibliometric analysis produced four findings: publications about Discovery Learning in Scopus-indexed journals have been in a fluid and balanced pattern every year for the last ten years; 328 of the ten journals producing the most articles have been published. The top-ranked journal published 15 articles, and the tenth-ranked journal published five articles; The most citations occurred in articles published in 2020 with a total of 1101 citations. The most cited article was written by B.R. Goldsmith with 241 citations; The author's keywords that are most frequently used in the top three are discovery, machine, and machine learning
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