2011 - Who Wants to Have a Career in Science or Math? Exploring Adolescents’ Future Aspirations by Gender and Race/Ethnicity

Attribution: Riegle-Crumb, Catherine, Moore, Chelsea, & Ramos-Wada, Aida
Researchers: Aida Ramos-WadaCatherine Riegle-CrumbChelsea Moore
University Affiliation: University of Texas at Austin
Email: riegle@austin.utexas.edu
Research Question:
The authors investigate how different racial/ethnic and gender subgroups compare to White males in terms of adolescent career aspirations in science and math, further considering the role that achievement and attitudes may play in shaping disparities at this early point in occupational trajectories.
Published: Yes
Journal Name or Institutional Affiliation: Science Education
Journal Entry: Vol 95. Pp. 458-476
Year: 2011
Findings:
  1. The importance of enjoyment, self-concept, and achievement in explaining disparities in science career aspirations relative to White males varies according to the female subgroup considered, such that no singular story applies to females across different racial/ethnic backgrounds.
  2. For math, White and Hispanic females remain approximately half as likely as White males to aspire to a math occupation regardless of all indicators considered.
  3. Black and Hispanic adolescent boys have generally comparable aspirations toward future careers in science and math as their White male peers, despite notably large differences in achievement.
  4. Black male youth are the only subgroup that shows comparable aspirations to White males in both subjects before accounting for other factors.
  5. Other than Black males, there distinct patterns by subject, so that patterns of equity are different for science career aspirations than they are for math. For example, Hispanic males’ aspirations toward a future math career do not differ significantly from those of White males, whereas their lower relative science aspirations can be explained by social background differences.
  6. Comparing White male aspirations to different female subgroups, the authors are able to explain disparities in science career aspirations by taking into account attitudes and achievement, factors known to influence choice of college major and occupation much later in life.
  7. Once differences in achievement are held constant, Black females are as likely as White males to aspire toward a science career. Adjusting for achievement similarly results in comparable science aspirations for Hispanic females. Yet in contrast to the patterns observed for Black females, accounting for enjoyment and self-concept also results in predicted levels of science aspirations for Hispanic females that are comparable to White males.
  8. Adjusting for differences in science enjoyment led to comparable aspirations between White females and their male peers.
  9. The association of enjoyment with aspirations in science (as well as math) is stronger than they observe for respective levels of self-concept, suggesting that enjoyment is a crucial factor in the development of future interests.
  10. Well more than half of the students from all groups report strongly enjoying science in the fourth grade. Among eighth-grade students, this proportion decreases across the board- yet more so for female adolescents than for male adolescents. While there are no differences between groups in science enjoyment in the fourth grade, there are significant differences in the eighth grade, such that significantly lower proportions of females from all racial/ethnic backgrounds report strongly enjoying science in comparison to White males.
  11. Low levels of academic preparation may function early to deter minority females, but perhaps function much later to impede the STEM trajectories of minority males.
Scholarship Types: Journal Article Reporting Empirical ResearchKeywords: AspirationsCareerEighth Grade StudentsGenderMathRaceScienceSTEMRegions: NationalMethodologies: QuantitativeResearch Designs: Secondary Survey DataAnalysis Methods: Descriptive StatisticsLogistic Regression Models Sampling Frame:Eighth Grade Students
Sampling Types: NationalAnalysis Units: StudentData Types: Quantitative-Cross Sectional
Data Description:
    • The authors utilized Eccles et al. expectancy-value model. This model posits that expectancies of success and subjective task values are key predictors of academic decision making that are related but distinct. Expectancies of success are defined as individuals’ beliefs about how well they perform on a future task.
    • 2003 Trends in International Mathematics and Science Study (TIMSS). The 2003 TIMSS uses a two-stage sampling design, where schools are sampled and then classrooms within those schools. The eighth-grade sample includes 232 schools, with selection based on the probability proportional to each school’s estimated enrollment, and two classrooms sampled within each school. The authors limit their sample to White, Black, and Hispanic students.
    • They utilize the nationally representative sample of eighth-grade students from the United States as it is the only recent national data set that provides the opportunity to examine the STEM-related career aspirations of adolescent youth.
    • DV- separate questions about students their career aspirations in the field of science and math. Specifically, they were asked, “How much do you agree with these statements about science? I would like a job that involves using science.” A parallel version was asked for math. Because the authors were interested in parsing out those students who already had a strong aspiration toward a career in the subject, they dichotomize the original coding of both variables so that “agree a lot” has a value of 1, and all other responses make up the reference category (0). The authors chose to model the decision to aspire toward a science career as distinct from that for math.
    • IV- a key element of subjective task value is represented by students’ intrinsic interest. This is measured by students’ response to how much they agree with the statement, “I enjoy learning science (or math).” For each subject, the authors dichotomized this variable to be 1 if students “agree a lot” and 0 for all other responses. To capture students’ self-concept, the authors use students’ agreement with the statement, “I usually do well in science (or math).” This variable is also coded the same way.
    • To measure students’ achievement in science and math, the authors utilized the tests administered by TIMSS in each subject.
    • The authors control on other characteristics that may be associated with career aspirations. To account for differences in family socioeconomic background, they include two variables- parental education level, which is student reported, and the highest education achieved. The authors also include a measure of how many books are in the students’ homes. This is coded on an ordinal scale with five categories, ranging from “none or few” to “three or more bookcases full of books.”

The authors also included measures of educational expectations on an ordinal scale according to students’ responses about how far they expect to go in school. Furthermore, they control for students’ general (rather than subject-specific) attitudes toward school by including a dichotomous variable indicating whether the student strongly agrees (vs. all other responses) with the statement, “I like being in school.” Finally, students’ race/ethnicity and gender are self-reported.

Theoretical Framework:
Relevance:Factors Related to STEM Readiness
Archives: K-16 STEM Abstracts