三角测量和揭示相互作用的方法

Vanessa Svihla
{"title":"三角测量和揭示相互作用的方法","authors":"Vanessa Svihla","doi":"10.3115/1599503.1599518","DOIUrl":null,"url":null,"abstract":"Quantitative methods in educational research tend to be heavily reductionist and to disregard interaction; most statistical models include an assumption of no interaction. Qualitative methods allow complexity and interaction, but tend not to include representations or otherwise allow the reader to \"see\" the interaction as the researcher can. By combining traditional qualitative methods with statistical modeling, we are afforded a better opportunity to see aspects of a phenomenon, but not always greater integration; interpretation does not easily emerge from potentially divergent data sets. By including social network analysis, which provides both summary statistics and graphical depiction of interaction we are afforded a better opportunity to examine collaborative work. Furthermore, technology facilitates collection and analysis of change over time in computer supported collaborative work. These methods enable a multifarious view of quantitative data, and allow for interpretation to more naturally emerge from multiple data sets.","PeriodicalId":120843,"journal":{"name":"International Conference on Computer Supported Collaborative Learning","volume":"102 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Methods for triangulation and revealing interaction\",\"authors\":\"Vanessa Svihla\",\"doi\":\"10.3115/1599503.1599518\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Quantitative methods in educational research tend to be heavily reductionist and to disregard interaction; most statistical models include an assumption of no interaction. Qualitative methods allow complexity and interaction, but tend not to include representations or otherwise allow the reader to \\\"see\\\" the interaction as the researcher can. By combining traditional qualitative methods with statistical modeling, we are afforded a better opportunity to see aspects of a phenomenon, but not always greater integration; interpretation does not easily emerge from potentially divergent data sets. By including social network analysis, which provides both summary statistics and graphical depiction of interaction we are afforded a better opportunity to examine collaborative work. Furthermore, technology facilitates collection and analysis of change over time in computer supported collaborative work. These methods enable a multifarious view of quantitative data, and allow for interpretation to more naturally emerge from multiple data sets.\",\"PeriodicalId\":120843,\"journal\":{\"name\":\"International Conference on Computer Supported Collaborative Learning\",\"volume\":\"102 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Computer Supported Collaborative Learning\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3115/1599503.1599518\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Computer Supported Collaborative Learning","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3115/1599503.1599518","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

教育研究中的定量方法往往过于简化,忽视相互作用;大多数统计模型都假定没有相互作用。定性方法允许复杂性和相互作用,但往往不包括表征或允许读者“看到”研究人员所能看到的相互作用。通过将传统的定性方法与统计建模相结合,我们有更好的机会看到现象的各个方面,但并不总是更好的整合;从可能存在分歧的数据集中很难得出解释。通过包括社会网络分析,它提供了总结统计和交互的图形描述,我们提供了一个更好的机会来检查协作工作。此外,在计算机支持的协作工作中,技术促进了随时间变化的收集和分析。这些方法支持定量数据的多种视图,并允许从多个数据集中更自然地产生解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Methods for triangulation and revealing interaction
Quantitative methods in educational research tend to be heavily reductionist and to disregard interaction; most statistical models include an assumption of no interaction. Qualitative methods allow complexity and interaction, but tend not to include representations or otherwise allow the reader to "see" the interaction as the researcher can. By combining traditional qualitative methods with statistical modeling, we are afforded a better opportunity to see aspects of a phenomenon, but not always greater integration; interpretation does not easily emerge from potentially divergent data sets. By including social network analysis, which provides both summary statistics and graphical depiction of interaction we are afforded a better opportunity to examine collaborative work. Furthermore, technology facilitates collection and analysis of change over time in computer supported collaborative work. These methods enable a multifarious view of quantitative data, and allow for interpretation to more naturally emerge from multiple data sets.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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:481959085
Book学术官方微信