SGER: A Model for Increasing Participation and Graduation Rates in Computer Engineering Related Disciplines

SGER：提高计算机工程相关学科的参与度和毕业率的模型

• 批准号: 0748418
• 负责人: Edward Brown
• 金额: --
• 依托单位: Rochester Institute of Tech
• 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
• 起止时间: 2007-09-15 至 2010-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0748418&HistoricalAwards=false
• 关键词: SGER; Model; Increasing; Participation; Graduation

In 2004, there were 64,675 bachelor degrees awarded to students majoring in engineering fields in the United States. Out of that total, women received 20.5% of the total degrees awarded, African Americans received 5%, Latin Americans received 6.9%, and Native Americans received approximately 0.5%. These percentages were disproportionate compared to their individual total population numbers within the U.S. for that same year. This SGER proposal argues that there is a major disconnect in the pipeline leading to the production and increase of undergraduate computer-engineering-related degrees by underrepresented student populations (i.e., female and minority students). To repair this disconnect, the focus must be on how young computer science and engineering students from underrepresented populations are trained and the inevitable obstacles students from these backgrounds face as they try to adapt to the culture of the computer science and engineering educational environments. This is essential to their professional success and the technological future of the United States since this is an ideal pool for finding the next generation of computer science and engineering professionals, technicians, and knowledge workers. This proposal provides a description of a laboratory apprenticeship training model that incorporates four major components for successfully achieving the increased recruitment, retention, training, and timely graduation rates of students from underrepresented and underserved backgrounds.

2004年，美国共有64，675名工程专业学生获得学士学位。 其中，妇女获得的学位占学位总数的20.5%，非洲裔美国人获得5%，拉丁美洲人获得6.9%，美洲原住民获得约0.5%。 这些百分比与同年美国境内的个人总人口数相比不成比例。 SGER的这一提案认为，在管道中存在一个重大的脱节，导致代表性不足的学生群体（即，少数民族学生）。 为了修复这种脱节，重点必须放在如何培养来自代表性不足人群的年轻计算机科学和工程专业学生，以及来自这些背景的学生在试图适应计算机科学和工程教育环境的文化时所面临的不可避免的障碍。 这对他们的专业成功和美国的技术未来至关重要，因为这是寻找下一代计算机科学和工程专业人员，技术人员和知识工作者的理想人才库。 该提案描述了一种实验室学徒培训模式，该模式包括四个主要组成部分，用于成功实现来自代表性不足和服务不足背景的学生的招聘，保留，培训和及时毕业率的提高。