Effectiveness of Inclusive STEM High Schools

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Project Citation:

Means, Barbara. Effectiveness of Inclusive STEM High Schools. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-11-29. https://doi.org/10.3886/E115783V1

Project Description

Summary: Inclusive STEM high schools have been heavily promoted in a number of states as a strategy for broadening participation in STEM studies and careers. This study addressed the question of whether these high schools improve the odds that their graduates will pursue a STEM major in college. State higher education records were obtained for students surveyed as seniors in 23 inclusive STEM high schools and 19 comparison schools without a STEM focus. Propensity score weighting was used to ensure that students in the comparison school sample were very similar to those in the inclusive STEM school sample in terms of demographic characteristics and grade 8 achievement. Students overall and from underrepresented groups who had attended inclusive STEM high schools were significantly more likely to be in a STEM bachelor’s degree program two years after high school graduation. For students who entered two-year colleges, on the other hand, attending an inclusive STEM high school was not associated with entry into STEM majors.

Funding Sources: National Science Foundation (DRL1817513); National Science Foundation (DRL 1316920)

Scope of Project

Subject Terms: [high school; , STEM; , postsecondary; , equity; , equity; , equity; , equity; , equity; , equity; , equity; , equity; ]

Geographic Coverage: Texas

Time Period(s): 8/1/2010 – 6/30/2016 ( )

Collection Date(s): 3/1/2014 – 6/30/2014 (Spring 2014 Grade 12 Survey); 7/1/2014 – 7/31/2017 (Extraction of K-12 and higher education data records at Education Research Center)

Universe:

Texas public high school graduating 12th graders in the Class of 2014

Data Type(s): administrative records data; survey data

Methodology

Response Rate: 68% for Grade 12 Survey administered in inclusive STEM high schools and 63% for the survey administered in comparison high schools serving similar students.

Sampling: Sample of 27 inclusive STEM high schools recruited from the 42 T-STEM high schools with a senior class that were located in districts accepting applications to conduct research. Comparison samples of 9 non-STEM small schools of choice and 10 regular non-STEM high schools agreeing to participate and administering the Grade 12 survey.
See " Broadening participation in STEM college majors: Effects of attending a STEM-focused high school.” Means, B., Wang, H., Wei, X., Iwatani, E., & Peters, V. (2018). AERA Open, 4(4), 1-17, for a fuller description of school sampling and recruiting.

Data Source: Investigator-administered Grade 12 Student Survey and administrative data from the Texas Education Research Center at University of Texas, Austin.

Collection Mode(s): record abstracts; web-based survey

Scales: Several Likert types scales were used. See full description of the survey scales in Means, B., Wang, H., Wei, X., Lynch, S., Peters, V., Young, V., & Allen, C. (2017). Expanding STEM opportunities through inclusive STEM-focused high schools. Science Education, 101(5), 681-715. doi:10.1002/sce21281

Weights:

Two sets of propensity score weights were applied to create comparison school samples as similar as possible to the ISHS student sample in terms of eight demographic variables (including gender, ethnicity, English proficiency, parents’ education, and parent employment in STEm) and five achievement variables (mainly Grade 8 achievement test scores). The first set of propensity score weights was applied to the 1,997 comparison school students in the Grade 12 Student Survey Sample. Using the same procedures, a second set of propensity score weights was developed for the 1,313 comparison school students with records in the Texas higher education data system (i.e., the College-going Sample). The objective of this two-step process was to make sure that among those students with higher education records the demographics and Grade 8 achievement levels of the comparison group were well- matched with those of the ISHS students, despite possible variations attributable to different college-going rates. When the analysis moved to student subgroups (Hispanic, female, economically disadvantaged), we followed the same proce- dure to compute propensity score weights to create equiva- lent ISHS and comparison school samples.

Unit(s) of Observation: Student

Geographic Unit: State

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V1 [2019-11-29]

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