Gender differences in conceptualizations of STEM career interest : Complimentary perspectives from data mining , multivariate data analysis and multidimensional scaling
dc.contributor.author | Knezek, G. | |
dc.contributor.author | Christensen, R. | |
dc.contributor.author | Tyler-Wood, T. | |
dc.contributor.author | Gibson, David | |
dc.date.accessioned | 2019-07-02T12:49:46Z | |
dc.date.available | 2019-07-02T12:49:46Z | |
dc.date.issued | 2014 | |
dc.identifier.citation | Knezek, G. and Christensen, R. and Tyler-Wood, T. and Gibson, D. 2014. Gender differences in conceptualizations of STEM career interest: Complimentary perspectives from data mining, multivariate data analysis and multidimensional scaling. Journal of STEM Education. 16 (4): pp. 13-19. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/75889 | |
dc.description.abstract |
Data gathered from 325 middle school students in four U.S. states indicate that both male (p < 0.0005, RSQ = 0.33) and female (p < 0.0005, RSQ = 0.36) career aspirations for "being a scientist" are predictable based on knowledge of dispositions toward mathematics, science and engineering, plus self-reported creative tendencies. For males, strong predictors are creative tendencies (beta = 0.348) and dispositions toward science (beta = 0.326), while dispositions toward mathematics is a weaker (beta = 0.137) but still a significant (p < 0.05) predictor. For females, significant (p < 0.05) predictors ordered by strength of contribution are dispositions toward science (beta = 0.360), creative tendencies (beta = 0.253) and dispositions toward mathematics (beta = 0.200). Additional analyses indicate that engineering appears to be more closely aligned with STEM career aspirations for females than for males. These findings contribute to the growing body of knowledge indicating that at the middle school level major contributors to choosing a path toward a STEM career differ for boys versus girls. | |
dc.relation.uri | https://www.learntechlib.org/p/171343/ | |
dc.title | Gender differences in conceptualizations of STEM career interest : Complimentary perspectives from data mining , multivariate data analysis and multidimensional scaling | |
dc.type | Journal Article | |
dcterms.source.title | Journal of STEM Education | |
dc.date.updated | 2019-07-02T12:49:45Z | |
curtin.department | Learning Futures | |
curtin.accessStatus | Fulltext not available | |
curtin.faculty | Curtin Learning and Teaching (CLT) | |
curtin.contributor.orcid | Gibson, David [0000-0003-1053-4690] | |
curtin.contributor.scopusauthorid | Gibson, David [35731134600] |