分析的支柱应用于信息科学与技术硕士学位

Jai W. Kang, Edward P. Holden, Qi Yu
{"title":"分析的支柱应用于信息科学与技术硕士学位","authors":"Jai W. Kang, Edward P. Holden, Qi Yu","doi":"10.1145/2808006.2808028","DOIUrl":null,"url":null,"abstract":"The Master of Science (MS) program in Information Sciences and Technologies (IST) at Rochester Institute of Technology conducted a significant upgrade of its curriculum in 2013, aiming to better prepare its graduates for the new trends and challenges in the fast evolving IT computing industry. In particular, the upgraded MS program places a strong emphasis on data analytics, where all students in the program get an intensive training in data analytics foundation in our core courses. Students can then continue with advanced work in the Analytics Track to receive deeper theoretical knowledge in the field. In this paper, we report our experience of offering this analytics-centric curriculum over the past two years. We first formally define four pillars of analytics and trace the skills needed to support each pillar and the courses that provide those skills. We then describe the course experiences through a sampling of the projects completed by students in their course work. We also provide some student feedback on the course experience. We conclude with a discussion of the capstone experience and a sampling of capstone projects. We show the movement toward analytics in the capstone experiences, particularly since the program began in 2013. The positive course experience and the fast increasing number of capstone projects in the analytics area show strong evidence about the initial success of the analytics-centric curriculum.","PeriodicalId":431742,"journal":{"name":"Proceedings of the 16th Annual Conference on Information Technology Education","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Pillars of Analytics Applied in MS Degree in Information Sciences and Technologies\",\"authors\":\"Jai W. Kang, Edward P. Holden, Qi Yu\",\"doi\":\"10.1145/2808006.2808028\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Master of Science (MS) program in Information Sciences and Technologies (IST) at Rochester Institute of Technology conducted a significant upgrade of its curriculum in 2013, aiming to better prepare its graduates for the new trends and challenges in the fast evolving IT computing industry. In particular, the upgraded MS program places a strong emphasis on data analytics, where all students in the program get an intensive training in data analytics foundation in our core courses. Students can then continue with advanced work in the Analytics Track to receive deeper theoretical knowledge in the field. In this paper, we report our experience of offering this analytics-centric curriculum over the past two years. We first formally define four pillars of analytics and trace the skills needed to support each pillar and the courses that provide those skills. We then describe the course experiences through a sampling of the projects completed by students in their course work. We also provide some student feedback on the course experience. We conclude with a discussion of the capstone experience and a sampling of capstone projects. We show the movement toward analytics in the capstone experiences, particularly since the program began in 2013. The positive course experience and the fast increasing number of capstone projects in the analytics area show strong evidence about the initial success of the analytics-centric curriculum.\",\"PeriodicalId\":431742,\"journal\":{\"name\":\"Proceedings of the 16th Annual Conference on Information Technology Education\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 16th Annual Conference on Information Technology Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2808006.2808028\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 16th Annual Conference on Information Technology Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2808006.2808028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

摘要

2013年,罗切斯特理工学院信息科学与技术(IST)理学硕士(MS)项目对其课程进行了重大升级,旨在让毕业生更好地为快速发展的IT计算行业的新趋势和挑战做好准备。特别值得一提的是,升级后的硕士课程非常重视数据分析,所有学生都在我们的核心课程中接受数据分析基础的强化培训。然后,学生可以继续学习分析跟踪的高级工作,以获得该领域更深入的理论知识。在本文中,我们报告了我们在过去两年中提供这种以分析为中心的课程的经验。我们首先正式定义分析的四个支柱,并跟踪支持每个支柱所需的技能和提供这些技能的课程。然后,我们通过学生在课程作业中完成的项目样本来描述课程体验。我们还提供一些学生对课程体验的反馈。最后,我们讨论了顶点项目的经验和顶点项目的样本。我们在顶点体验中展示了向分析的转变,特别是自2013年该项目开始以来。积极的课程体验和分析领域顶点项目数量的快速增长,有力地证明了以分析为中心的课程的初步成功。
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
Pillars of Analytics Applied in MS Degree in Information Sciences and Technologies
The Master of Science (MS) program in Information Sciences and Technologies (IST) at Rochester Institute of Technology conducted a significant upgrade of its curriculum in 2013, aiming to better prepare its graduates for the new trends and challenges in the fast evolving IT computing industry. In particular, the upgraded MS program places a strong emphasis on data analytics, where all students in the program get an intensive training in data analytics foundation in our core courses. Students can then continue with advanced work in the Analytics Track to receive deeper theoretical knowledge in the field. In this paper, we report our experience of offering this analytics-centric curriculum over the past two years. We first formally define four pillars of analytics and trace the skills needed to support each pillar and the courses that provide those skills. We then describe the course experiences through a sampling of the projects completed by students in their course work. We also provide some student feedback on the course experience. We conclude with a discussion of the capstone experience and a sampling of capstone projects. We show the movement toward analytics in the capstone experiences, particularly since the program began in 2013. The positive course experience and the fast increasing number of capstone projects in the analytics area show strong evidence about the initial success of the analytics-centric curriculum.
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
期刊最新文献
Programming in Scratch and Mathematics: Augmenting Your Geometry Curriculum, Today! Experiential Learning Business/Industry and Education Wants and Needs Session details: SIGITE Paper Session 2 The Cyber Education Project and IT IAS Curriculum The CCL-Parallax Programmable Badge: Learning with Low-Cost, Communicative Wearable Computers
×
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