EAGER:X+CS: CS Pathways for Non CS majors
EAGER:X CS:非 CS 专业的 CS 衔接课程
基本信息
- 批准号:1841563
- 负责人:
- 金额:$ 29.99万
- 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
- 起止时间:2018-09-01 至 2022-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
With computing impacting every field, and becoming a fundamental mode of inquiry in most disciplines,there is great demand for university coursework in computer science (CS). This has been reflected in a growthin CS majors. According to the numbers compiled by the Computer Research Association, in the decade since 2006, the number of computer science majors had tripled since 2006 and doubled since 2011. The trend has continued in the two years since, and University of Maryland - Baltimore County has not been an exception. According to several National Science Foundation public presentations that as the growth in computer science majors crests, there is a building wave of what is being viewed as "CS+X" students -- students studying in a discipline other than computer science, but needing a significant body of coursework. Our experience shows that by exposing such students to computing, we will diversify and broaden the participation in CS classes. We propose to create pathways into computing for such non computer science majors.This project will involve designing a sequence of new classes including, but also beyond, theintroductory programming sequence. These classes will introduce key concepts to students who do not intend to major in CS. Preliminary work has shown that this pool of students is much more diverse than that typically take CS courses. This project will focus on creating a sequence of courses that focus more on concepts important for various domains, as well as concepts related to scaling up (e.g., scalable data structures). It will also experiment with customized "X+CS" majors through the Individualized Study program. The researchers will consult colleagues from industry as they develop the course sequence.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.
随着计算影响各个领域,并成为大多数学科的基本探究模式,对计算机科学(CS)的大学课程有很大的需求。这反映在计算机科学专业的增长上。根据计算机研究协会编制的数据,自 2006 年以来的十年间,计算机科学专业的数量自 2006 年以来增加了两倍,自 2011 年以来增加了一倍。此后的两年里,这一趋势仍在持续,马里兰大学巴尔的摩郡分校也不例外。根据美国国家科学基金会的几份公开演讲,随着计算机科学专业的增长达到顶峰,出现了一股被视为“CS+X”学生的浪潮,即学习计算机科学以外学科但需要计算机科学专业知识的学生。重要的课程作业。我们的经验表明,通过让这些学生接触计算机,我们将多样化和扩大计算机科学课程的参与。我们建议为此类非计算机科学专业的学生创建进入计算的途径。该项目将涉及设计一系列新课程,包括但不限于入门编程序列。这些课程将为不打算主修计算机科学的学生介绍关键概念。初步工作表明,这个学生群体比通常参加计算机科学课程的学生更加多样化。该项目将专注于创建一系列课程,更多地关注对各个领域重要的概念,以及与扩展相关的概念(例如,可扩展的数据结构)。它还将通过个性化学习计划尝试定制“X+CS”专业。研究人员在开发课程序列时将咨询业界同事。该奖项反映了 NSF 的法定使命,并通过使用基金会的智力价值和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
X+CS: A Computing Pathway for Non-Computer Science Majors
X CS:非计算机科学专业的计算途径
- DOI:
- 发表时间:2020-03
- 期刊:
- 影响因子:0
- 作者:Mitchell, S;Cole, K;Joshi, A
- 通讯作者:Joshi, A
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Anupam Joshi其他文献
Collaborative joins in a pervasive computing environment
普适计算环境中的协作加入
- DOI:
10.1007/s00778-004-0127-3 - 发表时间:
2005-04-01 - 期刊:
- 影响因子:0
- 作者:
F. Perich;Anupam Joshi;Y. Yesha;Timothy W. Finin - 通讯作者:
Timothy W. Finin
FABULA: Intelligence Report Generation Using Retrieval-Augmented Narrative Construction
FABULA:使用检索增强叙事构建生成情报报告
- DOI:
10.1145/3625007.3627505 - 发表时间:
2023-10-20 - 期刊:
- 影响因子:0
- 作者:
P. Ranade;Anupam Joshi - 通讯作者:
Anupam Joshi
Knowledge Infusion in Privacy Preserving Data Generation
隐私保护数据生成中的知识注入
- DOI:
10.1016/j.ijepes.2023.109442 - 发表时间:
2023-12-01 - 期刊:
- 影响因子:0
- 作者:
Anantaa Kotal;C.S.E.E. Dept;Nilanjana Das;Anupam Joshi - 通讯作者:
Anupam Joshi
Web mining: research and practice
网络挖掘:研究与实践
- DOI:
10.1109/mcse.2004.23 - 发表时间:
2004-07-01 - 期刊:
- 影响因子:2.1
- 作者:
Pranam Kolari;Anupam Joshi - 通讯作者:
Anupam Joshi
KiNETGAN: Enabling Distributed Network Intrusion Detection through Knowledge-Infused Synthetic Data Generation
KiNETGAN:通过注入知识的合成数据生成实现分布式网络入侵检测
- DOI:
10.48550/arxiv.2405.16476 - 发表时间:
2024-05-26 - 期刊:
- 影响因子:0
- 作者:
Anantaa Kotal;Br;on Luton;on;Anupam Joshi - 通讯作者:
Anupam Joshi
Anupam Joshi的其他文献
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{{ truncateString('Anupam Joshi', 18)}}的其他基金
JST: SCC-PG: Bridging the Digital Gap and Identifying Cross-Cultural Pathways for Adoption of IoT Technologies to Support Super-Aging Societies in the U.S. and Japan
JST:SCC-PG:弥合数字鸿沟并确定采用物联网技术支持美国和日本超级老龄化社会的跨文化途径
- 批准号:
1952032 - 财政年份:2020
- 资助金额:
$ 29.99万 - 项目类别:
Standard Grant
EAGER: T2K: From Tables to Knowledge
EAGER:T2K:从表格到知识
- 批准号:
1250627 - 财政年份:2012
- 资助金额:
$ 29.99万 - 项目类别:
Standard Grant
Collaborative Proposal: ITR-SemDIS: Discovering Complex Relationships in the Semantic Web
合作提案:ITR-SemDIS:发现语义网中的复杂关系
- 批准号:
0325172 - 财政年份:2003
- 资助金额:
$ 29.99万 - 项目类别:
Continuing Grant
Profile Driven Architecture for Data Management in Pervasive Environments
用于普遍环境中数据管理的配置文件驱动架构
- 批准号:
0209001 - 财政年份:2002
- 资助金额:
$ 29.99万 - 项目类别:
Continuing Grant
NGS: Agent Oriented Approaches to a Ubiquitous Grid
NGS:面向代理的无处不在网格方法
- 批准号:
0203958 - 财政年份:2002
- 资助金额:
$ 29.99万 - 项目类别:
Continuing Grant
Dynamic Negotiation Agents in Mobile Computing
移动计算中的动态协商代理
- 批准号:
0070802 - 财政年份:2000
- 资助金额:
$ 29.99万 - 项目类别:
Continuing Grant
CAREER: MultiAgent Systems to Support Mobile Information Access
职业:支持移动信息访问的多代理系统
- 批准号:
9875433 - 财政年份:1999
- 资助金额:
$ 29.99万 - 项目类别:
Continuing Grant
Web Personalization and Mining Using Robust Fuzzy Clustering Methods
使用鲁棒模糊聚类方法进行 Web 个性化和挖掘
- 批准号:
9800899 - 财政年份:1998
- 资助金额:
$ 29.99万 - 项目类别:
Continuing Grant
Web Personalization and Mining Using Robust Fuzzy Clustering Methods
使用鲁棒模糊聚类方法进行 Web 个性化和挖掘
- 批准号:
9801711 - 财政年份:1998
- 资助金额:
$ 29.99万 - 项目类别:
Continuing Grant
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