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Collaborative Project: CSR-CSI Making Sensor Networks Accessible to Undergraduates Through Activity-Based Laboratory Materials

Collaborative Project: CSR-CSI Making Sensor Networks Accessible to Undergraduates Through Activity-Based Laboratory Materials
合作项目:CSR-CSI 通过基于活动的实验室材料让本科生可以使用传感器网络
批准号:
0720914
负责人:
Jens Mache
金额:
$0.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-08-01 至 2010-07-31

项目摘要

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中文摘要
翻译
传感器网络被认为是“改变世界的十大新兴技术”之一。教授传感器网络概念是具有挑战性的,因为该领域利用了一套完全不同的计算学科。对于传感器网络编程教育,存在一些“教程”,但它们的目标受众主要是研究生和专业研究人员。pi的经验表明,这些教程的呈现对本科生来说是困难的,因为他们没有必要的先决知识。在过去,没有实验练习适合以活动为基础的教学,这是一个新的和令人兴奋的领域。为了填补这一空白,CSR-CSI项目正在两所机构开展示范性的实验室练习:刘易斯克拉克学院(Lewis & Clark College)和波特兰州立大学(Portland State University),一所小型私立文理学院和一所授予博士学位的研究型大学。根据学生、行业顾问和教育顾问的意见,pi正在开发示范性的实验练习,确定适当的主题,澄清先决知识和准备材料,并以适合本科生的格式呈现材料。这项工作的智力优点在于阐明了使用和编程传感器网络的先决知识,并为向本科生教授这些主题奠定了基础。该项目还丰富了美国的科学和工程研究能力,并为本科生提供了基于活动的学习。这些材料的有效性在为大量少数民族和妇女提供服务的院校的本科生中进行了测试。
英文摘要
Sensor networks are considered one of the "10 Emerging Technologies That Will Change the World". Teaching sensor network concepts is challenging because the field draws upon a disparate set of computing disciplines. For sensor network programming education, some "tutorials" exist, but their target audience is largely graduate students and professional researchers.The PIs' experience shows that the presentation of these tutorials is difficult for undergraduate students as they do not have the prerequisite knowledge necessary. In the past, no lab exercises were available that are appropriate for activity-based teaching of this new and exciting field to undergraduates.To fill this void, this CSR-CSI project is developing exemplary laboratory exercises at two institutions: Lewis & Clark College, a small private liberal arts institution, and Portland State University, a Ph.D.-granting research university. With input from students, industrial advisors, and an educational consultant, the PIs are developing exemplary lab exercises, identifying topics that are appropriate, clarifying prerequisite knowledge and preparatory material, and presenting the material in a format that is suitable for undergraduates.The intellectual merits of this work are in clarifying the prerequisite knowledge to employing and programming sensor networks, and building a foundation for teaching these topics to undergraduates. This project also enriches the scientific and engineering research capability of the US, and provide undergraduates with activity-based learning. The effectiveness of the materials is tested on undergraduates at institutions serving a large population of minorities and women.
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Using Machine Learning to Provide Students with Rapid Feedback during Hands-on Cybersecurity Exercises
  • 批准号:
    2216485
  • 项目类别:
    Standard Grant
  • 资助金额:
    $13.82万
  • 财政年份:
    2022
  • 负责人:
    Jens Mache
  • 依托单位:
Collaborative Research: Modeling Student Activity and Learning on Cybersecurity Testbeds
  • 批准号:
    1723714
  • 项目类别:
    Standard Grant
  • 资助金额:
    $12.5万
  • 财政年份:
    2017
  • 负责人:
    Jens Mache
  • 依托单位:
EDURange: Supporting cyber security education with hands-on exercises, a student-staffed help-desk, and webinars
  • 批准号:
    1516100
  • 项目类别:
    Standard Grant
  • 资助金额:
    $16.65万
  • 财政年份:
    2015
  • 负责人:
    Jens Mache
  • 依托单位:
Collaborative Research: TUES: Type 1: EDURange: A Cybersecurity Competition Platform to Enhance Undergraduate Security Analysis Skills
  • 批准号:
    1141314
  • 项目类别:
    Standard Grant
  • 资助金额:
    $7.83万
  • 财政年份:
    2012
  • 负责人:
    Jens Mache
  • 依托单位:
海外基金