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Targeted Infusion Project: A Multidisciplinary Approach to Infusing Data Science and Analytics into the Undergraduate Curriculum at Bowie State University

Targeted Infusion Project: A Multidisciplinary Approach to Infusing Data Science and Analytics into the Undergraduate Curriculum at Bowie State University
有针对性的注入项目:将数据科学和分析注入鲍伊州立大学本科课程的多学科方法
批准号:
1818669
负责人:
Azene Zenebe
金额:
$39.98万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
未结题
起止时间:
2018-06-15 至 2025-05-31

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中文摘要
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英文摘要
The Historically Black Colleges and Universities Undergraduate Program (HBCU-UP) through Targeted Infusion Projects supports the development, implementation, and study of evidence-based innovative models and approaches for improving the preparation and success of HBCU undergraduate students so that they may pursue science, technology, engineering or mathematics (STEM) graduate programs and/or careers. The project at Bowie State University seeks to to integrate the advancement of big data technologies and analytics into the areas of Computer Science and Information Systems as well as apply big data and analytics to the disciplines of Economics, Biology, Chemistry and others. The activities and strategies are evidence-based and a strong plan for formative and summative evaluation is part of the project. Undergraduate students are included in the project and will be provided with summer research opportunities. This project has the objectives to: develop data science and analytics (DSA) course modules and deliver them in the disciplines of Chemistry, Biology, Computer Science, Information Systems, and Economics; create new courses and integrate the DSA modules into existing courses that will lead to an undergraduate certificate in DSA; offer undergraduate research opportunities; and establish a faculty training and learning community. This project will impact over 700 students per semester and several faculty. Opportunity are provided for minorities in STEM fields to address social and scientific issues impacting minority communities locally, nationally, and globally using big data and analytics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
Cyber Threat Intelligence Discovery using Machine Learning from the Dark Web
使用暗网机器学习发现网络威胁情报
DOI: 10.58729/1941-6687.1436
发表时间: 2022
期刊: Communications of the IIMA
影响因子: --
作者: [Zenebe, Azene]
通讯作者: Zenebe, Azene
ANALYSIS OF COVID-19 CASES BY ECONOMIC, HEALTH, EDUCATION AND RACE INDICATORS OF COMMUNITIES
按社区经济、健康、教育和种族指标对 COVID-19 病例进行分析
DOI: --
发表时间: 2021
期刊: Economics and Technology Proceedings 2021
影响因子: --
作者: [Azene Zenebe, Bowie State]
通讯作者: Azene Zenebe, Bowie State
HOUSING OPTIONS OF FEMALE-HEADED HOUSEHOLDS: EVIDENCE FROM THE AMERICAN HOUSING SURVEY
女户主家庭的住房选择:来自美国住房调查的证据
DOI: --
发表时间: 2021
期刊: Journal of economics and economic education research
影响因子: --
作者: [Augustin N. Ntembe, Bowie State]
通讯作者: Augustin N. Ntembe, Bowie State
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