数据分析、网络知识结构与学习成绩

IF 1.6 Q3 BUSINESS, FINANCE Journal of Emerging Technologies in Accounting Pub Date : 2023-10-01 DOI:10.2308/jeta-2022-056
Freddie Choo, Kim Tan
{"title":"数据分析、网络知识结构与学习成绩","authors":"Freddie Choo, Kim Tan","doi":"10.2308/jeta-2022-056","DOIUrl":null,"url":null,"abstract":"ABSTRACT The first objective of this study was to investigate whether data analytics could form a netlike knowledge structure (NKS) of learned course materials in accounting. We tested a group of students that used data analytics to solve an asset misappropriation case study and a control group that did not. We found evidence that data analytics has formed such a structure. The second objective was to investigate whether NKS was associated with academic performance. We conducted regression analyses on the NKSs and test scores. We found evidence that NKS with high connectivity and processing efficiency was associated with better accounting test scores. Overall, the findings imply that integrating data analytics into accounting courses benefits the learning of course materials by forming an NKS positively associated with academic performance. This study makes several contributions, including extending the work on NKS conducted predominantly in the cognitive science domain to the accounting domain.","PeriodicalId":45427,"journal":{"name":"Journal of Emerging Technologies in Accounting","volume":"44 1","pages":"0"},"PeriodicalIF":1.6000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Data Analytics, Netlike Knowledge Structure, and Academic Performance\",\"authors\":\"Freddie Choo, Kim Tan\",\"doi\":\"10.2308/jeta-2022-056\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT The first objective of this study was to investigate whether data analytics could form a netlike knowledge structure (NKS) of learned course materials in accounting. We tested a group of students that used data analytics to solve an asset misappropriation case study and a control group that did not. We found evidence that data analytics has formed such a structure. The second objective was to investigate whether NKS was associated with academic performance. We conducted regression analyses on the NKSs and test scores. We found evidence that NKS with high connectivity and processing efficiency was associated with better accounting test scores. Overall, the findings imply that integrating data analytics into accounting courses benefits the learning of course materials by forming an NKS positively associated with academic performance. This study makes several contributions, including extending the work on NKS conducted predominantly in the cognitive science domain to the accounting domain.\",\"PeriodicalId\":45427,\"journal\":{\"name\":\"Journal of Emerging Technologies in Accounting\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2023-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Emerging Technologies in Accounting\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2308/jeta-2022-056\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Emerging Technologies in Accounting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2308/jeta-2022-056","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0

摘要

摘要本研究的第一个目的是探讨数据分析是否可以形成一个网状的知识结构(NKS)的学习课程材料在会计。我们测试了一组使用数据分析来解决资产盗用案例研究的学生和一组没有使用数据分析的对照组。我们发现数据分析已经形成了这样一个结构的证据。第二个目的是调查NKS是否与学习成绩有关。我们对nks和考试成绩进行了回归分析。我们发现证据表明,高连接和处理效率的NKS与更好的会计考试成绩相关。总体而言,研究结果表明,将数据分析整合到会计课程中,通过形成与学习成绩正相关的NKS,有利于课程材料的学习。本研究做出了一些贡献,包括将主要在认知科学领域进行的NKS工作扩展到会计领域。
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
Data Analytics, Netlike Knowledge Structure, and Academic Performance
ABSTRACT The first objective of this study was to investigate whether data analytics could form a netlike knowledge structure (NKS) of learned course materials in accounting. We tested a group of students that used data analytics to solve an asset misappropriation case study and a control group that did not. We found evidence that data analytics has formed such a structure. The second objective was to investigate whether NKS was associated with academic performance. We conducted regression analyses on the NKSs and test scores. We found evidence that NKS with high connectivity and processing efficiency was associated with better accounting test scores. Overall, the findings imply that integrating data analytics into accounting courses benefits the learning of course materials by forming an NKS positively associated with academic performance. This study makes several contributions, including extending the work on NKS conducted predominantly in the cognitive science domain to the accounting domain.
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
CiteScore
4.30
自引率
27.80%
发文量
14
期刊最新文献
Deloitte Canada’s Cocreated ICT Simulation for Advanced Accounting Navigating the Digital Landscape: Unraveling Technological, Organizational, and Environmental Factors Affecting Digital Auditing Readiness in the Malaysian Public Sector A Tableau Teaching Application in Financial Data Analytics to State Local Governments: A Case Study on Louisiana Local Government Large Language Models: An Emerging Technology in Accounting Editorial Policy
×
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