The Curious Case of Centrality Measures: A Large-Scale Empirical Investigation

Mohammed Saqr, Sonsoles López-Pernas
{"title":"The Curious Case of Centrality Measures: A Large-Scale Empirical Investigation","authors":"Mohammed Saqr, Sonsoles López-Pernas","doi":"10.18608/jla.2022.7415","DOIUrl":null,"url":null,"abstract":"There has been extensive research using centrality measures in educational settings. One of the most common lines of such research has tested network centrality measures as indicators of success. The increasing interest in centrality measures has been kindled by the proliferation of learning analytics. Previous works have been dominated by single-course case studies that have yielded inconclusive results regarding the consistency and suitability of centrality measures as indicators of academic achievement. Therefore, large-scale studies are needed to overcome the multiple limitations of existing research (limited datasets, selective and reporting bias, as well as limited statistical power). This study aims to empirically test and verify the role of centrality measures as indicators of success in collaborative learning. For this purpose, we attempted to reproduce the most commonly used centrality measures in the literature in all the courses of an institution over five years of education. The study included a large dataset (n=3,277) consisting of 69 course offerings, with similar pedagogical underpinnings, using meta-analysis as a method to pool the results of different courses. Our results show that degree and eigenvector centrality measures can be a consistent indicator of performance in collaborative settings. Betweenness and closeness centralities yielded uncertain predictive intervals and were less likely to replicate. Our results have shown moderate levels of heterogeneity, indicating some diversity of the results comparable to single laboratory replication studies.","PeriodicalId":145357,"journal":{"name":"J. Learn. Anal.","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Learn. Anal.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18608/jla.2022.7415","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15

Abstract

There has been extensive research using centrality measures in educational settings. One of the most common lines of such research has tested network centrality measures as indicators of success. The increasing interest in centrality measures has been kindled by the proliferation of learning analytics. Previous works have been dominated by single-course case studies that have yielded inconclusive results regarding the consistency and suitability of centrality measures as indicators of academic achievement. Therefore, large-scale studies are needed to overcome the multiple limitations of existing research (limited datasets, selective and reporting bias, as well as limited statistical power). This study aims to empirically test and verify the role of centrality measures as indicators of success in collaborative learning. For this purpose, we attempted to reproduce the most commonly used centrality measures in the literature in all the courses of an institution over five years of education. The study included a large dataset (n=3,277) consisting of 69 course offerings, with similar pedagogical underpinnings, using meta-analysis as a method to pool the results of different courses. Our results show that degree and eigenvector centrality measures can be a consistent indicator of performance in collaborative settings. Betweenness and closeness centralities yielded uncertain predictive intervals and were less likely to replicate. Our results have shown moderate levels of heterogeneity, indicating some diversity of the results comparable to single laboratory replication studies.
中心性测度的奇特案例:一项大规模实证调查
在教育环境中使用中心性测量已经进行了广泛的研究。这类研究中最常见的一条路线是测试网络中心性指标作为成功的指标。学习分析的扩散引发了对中心性度量的日益增长的兴趣。以前的工作主要是由单一课程的案例研究,这些研究对中心性测量作为学术成就指标的一致性和适用性产生了不确定的结果。因此,需要大规模的研究来克服现有研究的多重局限性(有限的数据集,选择性和报告偏倚,以及有限的统计能力)。本研究旨在实证检验和验证中心性测量作为协作学习成功指标的作用。为此,我们试图重现文献中最常用的中心性测量方法,适用于一个机构五年以上教育的所有课程。该研究包括一个由69门课程组成的大型数据集(n= 3277),具有相似的教学基础,使用元分析作为汇集不同课程结果的方法。我们的研究结果表明,度和特征向量中心性度量可以成为协作环境中绩效的一致指标。中间和接近中心性产生了不确定的预测间隔,并且不太可能重复。我们的结果显示出中等程度的异质性,表明与单实验室重复研究相比,结果具有一定的多样性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信