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A multiple case study of social cognitive influences on career choice in Science, Mathematics and Technology among Kenyan women

Posted on:2011-08-06Degree:Ph.DType:Dissertation
University:Oregon State UniversityCandidate:Kagume, Daphne WambuiFull Text:PDF
GTID:1447390002464583Subject:Unknown
Abstract/Summary:
Kenyan women exhibit a pattern of unequal access and participation to education, particularly Science, Mathematics and Technology (SMT) subjects and careers. This is the result of documented challenges that include cultural attitudes that overburden girls with chores to the detriment of their school work, and a preference by parents to educate boys instead of girls when faced with financial difficulties. Other challenges include unequal funding of schools by the government that has resulted in fewer resources such as Science laboratories in girls' schools and subsequent poor performance in Science subjects in the national examinations. Pervasive gender stereotypes abound in Kenyan schools and many students make subject and major choices based on these stereotypes as opposed to using interest and ability to determine career choice. This stereotyping is exacerbated by the lack of career guidance in Kenyan schools meaning students do not have accurate sources of information about careers. This multiple case study was carried out to determine the individual and social factors that help Kenyan women make an SMT career choice. Women ages 20-30 were interviewed together with a parent/mentor using semi-structured questions to investigate their perceptions of themselves and their environments and how that influenced them to go into SMT careers. Results revealed high self-efficacy in Science and Mathematics, strong environmental support and coping efficacy all helped these women make a congruent career choice in SMT. This study contributes to the knowledge base on how counselors can help more Kenyan girls and women choose Science careers if that is really where their interests lie.
Keywords/Search Tags:Science, Kenyan, Women, Career, Mathematics, SMT
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