Project Activities
First, the researchers will conduct a systematic review of the research literature on the effects of completing college-level courses during high school on students' postsecondary outcomes that meet a pre-established set of inclusion criteria for the meta-analysis. Second, they will code each study for program type, institution level, sample selection, publication type, and additional pre-specified research design characteristics. After coding the constituent studies, they will examine and synthesize the findings from the included studies using advanced, up-to-date meta-analysis modeling techniques and will disseminate its findings to audiences of policymakers, practitioners, and researchers.
Structured Abstract
Setting
The meta-analysis will include studies of high school courses for college credit occurring in high schools, early colleges, colleges, and online settings located within the United States.
Sample
The meta-analytic sample will include studies of high school students who participated in high school courses for college credit and students who did not participate.
This project will focus on five categories of high school courses for college credit: dual enrollment, early college high school, Advanced Placement, International Baccalaureate, and Cambridge Advanced International Certificate of Education.
Research design and methods
The researchers will conduct a systematic review and meta-analysis. Eligible research designs for studies to be included in the meta-analysis include experimental designs, quasi-experimental designs, and any between-group design that accounts for baseline differences between the students in the intervention and comparison groups before they engaged in high school coursework for college credit. The research team will conduct an exhaustive search, including peer-reviewed and gray literature, using clear inclusion criteria and a two-stage screening process involving data entry tools and at least two screeners for every study that may be eligible for inclusion. All study coding and data extraction procedures, such as postsecondary outcome measures and calculating effect sizes, will align with the What Works Clearinghouse Transition to College Review Protocol and the Procedures and Standards Handbook, Version 5.0. The researchers will use a correlated and hierarchical effects model as the working model for the meta-analysis with robust variance estimation to guard against model misspecification.
Control condition
Control group students did not participate in high school courses for college credit.
Key measures
Key measures comprise three outcome domains. First, the researchers will measure college enrollment as a student attending a 2-year, 4-year, or any postsecondary institution after high school graduation. Second, they will measure persistence in college as a student who has remained enrolled for multiple semesters, with the number of semesters varying across studies. Third, they will measure degree completion as earning an associate degree or bachelor's degree, with the number of years until degree completion varying across studies.
Data analytic strategy
The goal of the research team's data analytic strategy will be to create a standardized measure (Hedges' g) of intervention effects and to synthesize findings across varying outcome measures and studies. The analytic strategy will prioritize preliminary analyses by outcome domain, with separate meta-analyses for college enrollment, persistence, and degree completion. Due to variation in postsecondary outcomes in eligible studies, the researchers will employ different strategies depending on whether the outcome is continuous or dichotomous. For linear models reporting continuous outcomes, they will extract an estimate of the adjusted difference between the two experimental groups from a linear model and compute Hedges' g with the unadjusted pooled standard deviation of the outcome measure. For studies reporting on dichotomous outcomes, they will prioritize extracting an odds ratio adjusted for any baseline differences between the two groups. For both sets of outcomes, the researchers will use meta-regression to explore effect size heterogeneity across studies, including program type, institution level, student sample, and research design variables.
People and institutions involved
IES program contact(s)
Project contributors
Products and publications
This project will result in synthetic evidence on the effectiveness of college-level courses taken during high school on postsecondary outcomes. The project will also result in a final dataset and analytic code to be shared, peer-reviewed publications and presentations, and additional dissemination products that reach education stakeholders such as practitioners and policymakers.
Publications:
ERIC Citations: Find available citations in ERIC for this award here
Related projects
Supplemental information
Co-Principal Investigators: Pigott, Therese; Hu, Xiaodan
Questions about this project?
To answer additional questions about this project or provide feedback, please contact the program officer.
