Co-citations Map: Literature review on Learning Ecologies, 1991-2018

The co-citation map was adopted as type of analysis over 85 papers sampled from five scientific databases (pls. cfr: Systematic Review on the Research Topic "Learning Ecologies" - Dataset and Analysis". This was adopted as method to further understand the relationships and advancement of work relating the concept of LE. The software tool to carry out this phase of the study was Citenet Explorer for the analysis and visualization of co-citations along the period 1999-2018. The total number of citations and the relationships between most cited authors and all authors were extracted from the corpus analyzed (Systematic Review on the Research Topic "Learning Ecologies" - Dataset and Analysis"; a specific dataset was created and the outputs were processed by the specialized software that delivers the bibliometric maps as output. All the instructions to use the two files that compose the dataset requested by the software, as well as the software specifications can be found at CiteNet Explore page: http://www.citnetexplorer.nl/ Finally, the Fig. 7 with the analysis we performed shows the co-citations map, where at a first sight it is possible to see two main groups of nodes or authors cited (X axis) across a timespan (Y axis), and sparse elements at the center and at the beginning of the period (1991). The main and more compact group (also in terms of clusterisation of nodes, which are showed in green) related the publications that cite the seminal work of Barron (2004). These publications are mostly classified as using socio-constructivist theories and are placed in the area of social sciences, while for other categories (such as the methodological approach, research applications and the alignment are more fragmented). There are four seminal works (Abd-El-Khalick & Akerson, 2004; Barron, 2004; T ; Okamoto, Kayama, Inoue, & Cristea, 2002; Toshio Okamoto & Kayama, 2004) to which other papers can be connected. Beyond the mentioned work of Barron, the other three works can be placed in the area of technology (development of eLearning environments) and STEM education, supporting the idea of disciplinary fragmentation.本研究采用共引图谱作为分析方法，分析样本为从5个科学数据库中抽取的85篇文献（详见《研究主题"学习生态"的系统综述——数据集与分析》）。该方法用于进一步探究与学习生态（Learning Ecologies，简称LE）概念相关研究的关联与进展。本研究此阶段采用的软件工具为CiteNet Explorer，用于1999年至2018年间共引关系的分析与可视化。从分析的文献集（详见《研究主题"学习生态"的系统综述——数据集与分析》）中提取了总被引频次，以及高被引作者与全体作者间的关联关系；本研究构建了专属数据集，并通过可生成文献计量图谱的专用软件对输出结果进行处理。该软件所需的数据集由两个文件组成，关于这两个文件的使用说明以及软件的规格参数，均可在CiteNet Explorer官网（http://www.citnetexplorer.nl/）查询获取。最后，本研究完成的分析结果如图7所示，该共引图谱的横轴为时间跨度，纵轴为被引节点或作者，初步可见两大主要节点集群，在研究初期（1991年）及图谱中心区域的节点分布较为零散。其中规模更大且结构更紧凑的集群（节点以绿色标识）关联的是引用Barron（2004）经典研究的文献。这类文献大多采用社会建构主义理论，归属社会科学领域；而其他类别（如方法论路径、研究应用及相关契合性研究）则呈现出更为分散的态势。本研究共识别出4项经典奠基性研究（Abd-El-Khalick & Akerson, 2004；Barron, 2004；Okamoto, Kayama, Inoue, & Cristea, 2002；Toshio Okamoto & Kayama, 2004），其余文献均可与这四项研究建立关联。除前述Barron的研究外，其余三项奠基性研究均归属技术（电子学习环境开发）与STEM教育领域，这也印证了研究主题的学科碎片化特征。