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Open AccessArticle

Texas Rural vs. Nonrural School District Student Growth Trajectories on a High-Stakes Science Exam: A Multilevel Approach

1
Department of Educational Psychology, College of Education and Human Development, Texas A&M University, College Station, TX 77840, USA
2
Center for Research and Development in Dual Language and Literacy Acquisition, College of Education and Human Development, Texas A&M University, College Station, TX 77840, USA
*
Author to whom correspondence should be addressed.
Soc. Sci. 2019, 8(6), 166; https://doi.org/10.3390/socsci8060166
Received: 13 May 2019 / Revised: 28 May 2019 / Accepted: 29 May 2019 / Published: 31 May 2019
This study compares the science achievement growth trajectories of fifth-grade students in rural and nonrural school districts in Texas. Using a growth hierarchical linear model, we explored the effects of time, school location (rural vs. nonrural), and their interaction on students’ science performance as measured by the high-stakes State of Texas Assessment of Academic Readiness (STAAR) science test over five academic years. We found that rural school students lagged in science at the initial stage when STAAR was first administered in the 2011–2012 school year. With time, the gap between rural and nonrural district students’ science performance persisted. We further added eight district-level factors that might influence students’ academic performance into the model and found that three variables (i.e., student mobility rate, percentage of students identified ELs, and teacher turnover rate) constantly influenced students’ science scores. The implications for teaching pedagogy and research are discussed regarding science education in Texas rural districts. View Full-Text
Keywords: Texas rural school districts; science; academic achievement Texas rural school districts; science; academic achievement
MDPI and ACS Style

Wang, Z.; Tang, S.; Sutton-Jones, K. Texas Rural vs. Nonrural School District Student Growth Trajectories on a High-Stakes Science Exam: A Multilevel Approach. Soc. Sci. 2019, 8, 166.

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