Date of Award

Summer 8-17-2014

Degree Type

Dissertation

Degree Name

PhD Higher Education Leadership, Management, Policy

Department

Education Leadership, Management and Policy

Advisor

Rong Chen

Committee Member

Eunyoung Kim

Committee Member

William Miron

Keywords

Female science underrepresentation, Programme for International Student Assessment (PISA), intention to study science postsecondary, logistic regression

Abstract

The goal of this study was to perform an exploratory analysis of a comprehensive list of independent variables identified from literature to determine which, if any, are effective predictors in forecasting a female’s intention to study science postsecondary. This is likely to be indicative of interest to study science when pursing higher education as well as choice of major and possible career. The postulated model guiding this analysis, which was based on prior research, recognized that factors pertaining to students, parents, schools, and peers are all important. This study used logistic regression to analyze data from the 2006 Programme for International Student Assessment (PISA). The findings of this study suggest that external factors, such as those considered from the environment, are indeed important in determining a female’s intention to study science postsecondary. The findings of this study provided further refinement by demonstrating that for the 15 countries included in this analysis from the Oceania, Latin America, European, and Asian regions there were some overarching and consistent factors that are positively associated with females’ intentions to study science postsecondary. These findings essentially paint a portrait of females who intend to study science postsecondary, which are used to suggest additional research as well as interventions to help mitigate the female scientist conundrum observed worldwide.

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