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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Lopez, A.M. Kun Zhang Lopez, F.G. |
| Copyright Year | 2008 |
| Description | Author affiliation: Comput. Sci. Dept., Xavier Univ. of Louisiana, LA (Lopez, A.M.; Kun Zhang) || Counseling Psychol. Program, Univ. of Houston, Houston, TX (Lopez, F.G.) |
| Abstract | Gender and race play significant roles in how people view and experience the world. In certain contexts both gender and race may activate doubts about onepsilas career-related performance- and coping-related capabilities. This paper presents findings on the effects of gender and race in the undergraduate pipeline of the computing disciplines (i.e., computer engineering, computer science, software engineering, information systems, and information technology) through the more proximal impacts of stereotyping, coping self-efficacy and collective self-esteem. Data were collected in Fall 2004 from 1,208 computing discipline and 581 non-computing discipline students attending forty-two colleges and universities across the United States. Twenty-one of these institutions were Historically Black Colleges and Universities and 21 were Predominantly White Institutions. Data were analyzed using statistical and data mining techniques to investigate the influence of stereotyping, coping self-efficacy and collective self-esteem in the computing disciplines. |
| File Size | 473597 |
| File Format | |
| ISBN | 9781424419692 |
| ISSN | 01905848 |
| DOI | 10.1109/FIE.2008.4720372 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-10-22 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Pipelines Educational institutions Computer science Information technology Software engineering Information systems Data analysis Data mining Recruitment Sampling methods Stereotyping Collective Self-esteem Coping Self-efficacy Gender Race |
| Content Type | Text |
| Resource Type | Article |
| Subject | Education Computer Science Applications Software |
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