ITWF: Characteristics and Career Paths of Current IT Workers

ITWF：当前IT从业者的特征和职业路径

• 批准号: 0204464
• 负责人: Joshua Rosenbloom
• 金额: $ 34.72万
• 依托单位: University of Kansas Center for Research Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-07-15 至 2005-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0204464&HistoricalAwards=false
• 关键词: ITWF; Characteristics; Career; Paths; Current

EIA-0204464Rosenbloom, Joshua L., Ash, Ronald A.University of Kansas Title: Characteristics and Career Paths of Current IT WorkersThis award provides support for a study that will identify important decision points in the educational and work experiences of Information Technology (IT) workers that have led them to enter and remain in the IT workforce. The results of this study will document the normal patterns of entry and retention in the IT workforce to provide a baseline to examine the special problems of women and minorities who are greatly underrepresented in this expanding and lucrative sector of the economy.Through a survey of both current IT and non-IT workers in the greater Kansas City area, the project will gather data on individual personality traits in conjunction with detailed family background, and educational and work histories. These data will in turn be used to identify aspects of attitudes, family background, and educational and work experiences that have influenced individual decisions to enter IT jobs, as well as to remain in (or exit from) them. Among IT workers the same data will be used to explore differences by sex, and race and ethnicity. The results will illuminate both the similarities between IT and science and engineering career choices, and the differences.

EIA-0204464RosenBloom，Joshua L.，Ash，Ronald A.堪萨斯大学标题：当前IT工作者的特征和职业道路该奖项为一项研究提供支持，该研究将确定信息技术(IT)工作者的教育和工作经历中的重要决策点，这些决策点导致他们进入并留在IT劳动力队伍中。这项研究的结果将记录IT劳动力的进入和保留的正常模式，以提供一个基线，以检查在这个不断扩大和有利可图的经济部门中女性和少数族裔的特殊问题。通过对大堪萨斯城地区现有IT和非IT员工的调查，该项目将收集关于个人个性特征的数据，以及详细的家庭背景、教育和工作历史。这些数据将被用来确定态度、家庭背景、教育和工作经历等方面，这些方面影响了个人进入IT工作的决定，以及留在或退出IT工作的决定。在IT工作者中，同样的数据将被用来探索性别、种族和民族的差异。结果将阐明IT和科学以及工程职业选择之间的相似之处和差异。