The DOI matches its Crossref record; 82 of the 82 references it cites were found in a registry or an index.
Early determinants of women in the IT workforce: a model of girls' career choices
Abstract
Purpose: To develop a testable model for girls' career choices in technology fields based on past research and hypotheses about the future of the information technology (IT) workforce. Design/methodology/approach: Review and assimilation of literature from education, psychology, sociology, computer science, IT, and business in a model that identifies factors that can potentially influence a girl's choice towards or against IT careers. The factors are categorized into social factors (family, peers, and media), structural factors (computer use, teacher/counselor influence, same sex versus coeducational schools), and individual differences. The impact of culture on these various factors is also explored. Findings: The model indicates that parents, particularly fathers, are the key influencers of girls' choice of IT careers. Teachers and counselors provide little or no career direction. Hypotheses propose that early access to computers may reduce intimidation with technology and that same‐sex education may serve to reduce career bias against IT. Research limitations/implications: While the model is multidisciplinary, much of research from which it draws is five to eight years old. Patterns of career choices, availability of technology, increased independence of women and girls, offshore/nearshore outsourcings of IT jobs are just some of the factors that may be insufficiently addressed in this study. Practical implications: A “Recommendations” section provides some practical steps to increase the involvement of girls in IT‐related careers and activities at an early age. The article identifies cultural research as a limitation and ways to address this. Originality/value: The paper is an assimilation of literature from diverse fields and provides a testable model for research on gender and IT.
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Cites
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Cited by
Hsu, T.-C., Abelson, H., & Van Brummelen, J. (2022) · The International Review of Research in Open and Distributed Learning · doi:10.19173/irrodl.v22i4.5474 · Cited by 65
(2011) · ATE Central (National Science Foundation) · Cited by 48
Metadata
- Authors
- Adya, M., & Kaiser, K. M.
- Venue
- Information Technology & People
- Publisher
- Emerald
- Published
- 2005-09-01
- Volume
- 18
- Issue
- 3
- Pages
- 230-259
- ISSN
- 0959-3845 (ISSN-L)
- OpenAlex
- W2026904675
- Cited by
- 270
- References
- 82
- FWCI
- 16.05
- Type
- journal article
- Language
- en
- Open access
- closed
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- Adya, M., & Kaiser, K. M. (2005). Early determinants of women in the IT workforce: a model of girls' career choices. Information Technology & People. https://doi.org/10.1108/09593840510615860
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.