美国大学和HBCUs教育教授的统计技能差距

IF 1.5 Q2 EDUCATION, SCIENTIFIC DISCIPLINES Journal of Statistics and Data Science Education Pub Date : 2022-01-02 DOI:10.1080/26939169.2022.2034488
Kimberlee Everson
{"title":"美国大学和HBCUs教育教授的统计技能差距","authors":"Kimberlee Everson","doi":"10.1080/26939169.2022.2034488","DOIUrl":null,"url":null,"abstract":"Abstract This study aims to identify some perceived gaps in a selection of statistical skills and software abilities of professors of education in United States colleges and universities. In addition to a general U. S. sample, a sample of education professors in Historically Black Colleges and Universities (HBCUs) was examined in order to understand their unique needs. Results showed that many professors from both samples felt they were weak in their abilities with more advanced statistical methods such as structural equation modeling and propensity score matching. Professors of education at HBCUs, however, had significant perceived skill-need methodology gaps in most of the methodologies evaluated. The general U.S. sample indicated a skill-need gap with statistical software packages such as R, and the HBCU sample indicated a skill-need gap with all five software packages evaluated (Excel, SPSS, SAS, Stata, and R). Affordable training workshops addressing the greatest areas of perceived need should be helpful in reducing this skill-need gap.","PeriodicalId":34851,"journal":{"name":"Journal of Statistics and Data Science Education","volume":"30 1","pages":"45 - 53"},"PeriodicalIF":1.5000,"publicationDate":"2022-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Statistical Skills Gaps of Professors of Education at U.S. Universities and HBCUs\",\"authors\":\"Kimberlee Everson\",\"doi\":\"10.1080/26939169.2022.2034488\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract This study aims to identify some perceived gaps in a selection of statistical skills and software abilities of professors of education in United States colleges and universities. In addition to a general U. S. sample, a sample of education professors in Historically Black Colleges and Universities (HBCUs) was examined in order to understand their unique needs. Results showed that many professors from both samples felt they were weak in their abilities with more advanced statistical methods such as structural equation modeling and propensity score matching. Professors of education at HBCUs, however, had significant perceived skill-need methodology gaps in most of the methodologies evaluated. The general U.S. sample indicated a skill-need gap with statistical software packages such as R, and the HBCU sample indicated a skill-need gap with all five software packages evaluated (Excel, SPSS, SAS, Stata, and R). Affordable training workshops addressing the greatest areas of perceived need should be helpful in reducing this skill-need gap.\",\"PeriodicalId\":34851,\"journal\":{\"name\":\"Journal of Statistics and Data Science Education\",\"volume\":\"30 1\",\"pages\":\"45 - 53\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2022-01-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Statistics and Data Science Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/26939169.2022.2034488\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"EDUCATION, SCIENTIFIC DISCIPLINES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Statistics and Data Science Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/26939169.2022.2034488","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
引用次数: 0

摘要

摘要:本研究旨在确定美国高校教育教授在统计技能和软件能力方面的一些认知差距。除了一般的美国样本外,为了了解他们的独特需求,我们还研究了历史上黑人学院和大学(HBCUs)的教育教授样本。结果显示,两个样本中的许多教授都认为自己在使用结构方程建模和倾向得分匹配等更先进的统计方法方面的能力较弱。然而,在大多数评估的方法中,HBCUs的教育教授都有明显的技能需求方法差距。一般的美国样本表明对统计软件包(如R)的技能需求差距,HBCU样本表明对所有五种软件包(Excel, SPSS, SAS, Stata和R)的技能需求差距。针对感知需求最大领域的可负担的培训研讨会应该有助于减少这种技能需求差距。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Statistical Skills Gaps of Professors of Education at U.S. Universities and HBCUs
Abstract This study aims to identify some perceived gaps in a selection of statistical skills and software abilities of professors of education in United States colleges and universities. In addition to a general U. S. sample, a sample of education professors in Historically Black Colleges and Universities (HBCUs) was examined in order to understand their unique needs. Results showed that many professors from both samples felt they were weak in their abilities with more advanced statistical methods such as structural equation modeling and propensity score matching. Professors of education at HBCUs, however, had significant perceived skill-need methodology gaps in most of the methodologies evaluated. The general U.S. sample indicated a skill-need gap with statistical software packages such as R, and the HBCU sample indicated a skill-need gap with all five software packages evaluated (Excel, SPSS, SAS, Stata, and R). Affordable training workshops addressing the greatest areas of perceived need should be helpful in reducing this skill-need gap.
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
Journal of Statistics and Data Science Education
Journal of Statistics and Data Science Education EDUCATION, SCIENTIFIC DISCIPLINES-
CiteScore
3.90
自引率
35.30%
发文量
52
审稿时长
12 weeks
期刊最新文献
Investigating Sensitive Issues in Class Through Randomized Response Polling Teaching Students to Read COVID-19 Journal Articles in Statistics Courses Journal of Statistics and Data Science Education 2023 Associate Editors Interviews of Notable Statistics and Data Science Educators Coding Code: Qualitative Methods for Investigating Data Science Skills
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1