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2012 - Pathways to a STEMM Profession

Attribution: Miller, Jon D., & Kimmel, Linda G.
Researchers: Jon D. MillerLinda G. Kimmel
University Affiliation: University of Michigan
Email: jondmiller@umich.edu
Research Question:
This analysis focuses on differences in pathways to a science, technology, engineering, mathematics, and medicine (STEMM) professions.
Published: Yes
Journal Name or Institutional Affiliation: Peabody Journal of Education
Journal Entry: Vol. 87, No. 1, Pp. 26-45
Year: 2012
Findings:

– Mathematics continues to be a primary gateway for STEMM professions, beginning with algebra track placement in grade eight and continuing through high school and college calculus courses.
– The completion of a calculus course in high school and the number of college calculus courses taken by students were two of the strongest predictors of STEMM employment in young adulthood.
– Home and family factors such as parent education and parent encouragement of science and mathematics during secondary school also enhanced the likelihood of entering a STEMM profession.
– Parents with higher levels of educational attainment were more likely to encourage their child to do well in science and mathematics in high school than parents with lower levels of education.
– High school boys were more likely to report that they liked math than were girls.
– High school boys reported slightly more parental encouragement in science and mathematics than girls, but high school girls scored higher on reading tests than male students. In the postsecondary model, female students were more likely to earn a baccalaureate than male students, but male college students were slightly more likely to earn a baccalaureate, graduate, or professional degree in a STEMM field than female students.

* Factors that impact attraction to STEM.

Scholarship Types: Journal Article Reporting Empirical ResearchKeywords: Academic AchievementEmploymentGenderParental EducationSTEMRegions: NationalMethodologies: QuantitativeResearch Designs: Secondary Survey DataAnalysis Methods: Descriptive StatisticsStructural Equation Modeling Sampling Frame:STEMM students
Sampling Types: Nationally RepresentativeAnalysis Units: StudentData Types: Quantitative-Longitudinal
Data Description:

Using data from the 23-year record of the Longitudinal Study of American Youth (LSAY). The LSAY began collecting data from a national probability sample of seventh- and 10th-grade students in 50 public school systems in the United States in the fall of 1987. This analysis utilizes a consolidated file that includes data from 3,945 participants (77% of the eligible sample) who completed the 2007 survey.

DVs:
– Plans to major in a STEMM field in college
– Enrollment in a STEMM major
– Employment in a STEMM profession

IVs:
– demographic variables,
– Parent college push: measured on a 5 level ordinal scale from low to high. The basic questions ask parents how much education that they would like their student to complete and how disappointed they would be if the student did not complete that level of education.
– Parent science-math push: measured on a 6 level ordinal scale from low to high. This reflects student reports about various parent activities and behaviors encouraging science or mathematics.
– When they took Algebra 1 in school
– Achievement in math, science, and reading
– Home science learning resources: This seven-level ordinal variable is a count of the number of science learning resources that each student reported were available in his or her home.
– Math teacher push
– Science teacher push
– Attitude towards math
– Attitude towards science
– Took a calculus course in high school
– Number of college engineering courses taken (only for measuring employment in STEMM)
– Number of college calculus courses taken (only for measuring employment in STEMM)
– A graduate or professional degree in STEMM

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