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Rheta E. Lanehart

University of South Florida



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Patricia Rodríguez de Gil

University of South Florida



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Maressa Dixon

University of South Florida



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Jeffrey D. Kromrey

University of South Florida



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Gladis Kersaint

University of South Florida



475 – Statistical Analysis of Educational Data: Challenges and Opportunities

The Impact of Career Academies on STEM Coursetaking: Moving to the Next Level

Sponsor: Social Statistics Section
Keywords: Propensity scores, Observational studies, ITEST ePEP, HSLS:09

Rheta E. Lanehart

University of South Florida

Patricia Rodríguez de Gil

University of South Florida

Maressa Dixon

University of South Florida

Jeffrey D. Kromrey

University of South Florida

Gladis Kersaint

University of South Florida

Propensity score (PS) methods provide viable strategies for reducing selection bias in nonexperimental (observational) studies. An NSF funded project previously used propensity score analysis to examine the impact of special educational programs on advanced mathematics course enrollment (Rodriguez de Gil et al., 2012). Results indicated that students who enrolled in career academies were almost twice as likely to enroll in a Calculus course. Encouraged by the findings from the previous study, we are currently using PS and survival analyses to investigate rigorous high school STEM/ICT coursetaking for students in a southern state who identified an interest in STEM or ICT careers as part of their 8th grade electronic Personal Education Planners (ePEPs) and the persistence of STEM coursetaking through high school. Comparison of rigorous STEM coursetaking trends and persistence with national data (High School Longitudinal Study: HSLS09) will be made. This study reports on correlates of 8th and 9th grade coursetaking and procedures used to identify the initial STEM cohort from the HSLS09 national dataset.

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