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A Multilevel Study of the Impact of District-Level Characteristics on Texas Student Growth Trajectories on a High-Stakes Math Exam

Author

Listed:
  • Shifang Tang

    (Center for Research & Development in Dual Language & Literacy Acquisition, College of Education and Human Development, Texas A&M University, College Station, TX 77840, USA)

  • Zhuoying Wang

    (Center for Research & Development in Dual Language & Literacy Acquisition, College of Education and Human Development, Texas A&M University, College Station, TX 77840, USA)

  • Kara L. Sutton-Jones

    (Center for Research & Development in Dual Language & Literacy Acquisition, College of Education and Human Development, Texas A&M University, College Station, TX 77840, USA)

Abstract

Mathematics is a core content area in the science, technology, engineering, and mathematics (STEM) fields and is vital to student learning in the other STEM subjects. The purpose of this study was to investigate the math performance of fifth- and eighth-grade students in 1170 Texas school districts. We conducted growth hierarchical linear modeling in SAS 9.4 in order to explore the effects of time, district-level characteristics, and their interaction on student performance as measured by the State of Texas Assessments of Academic Readiness (STAAR) math test across three performance levels (i.e., approaching, meeting, and mastering grade level) over three academic years: 2016–2019. The overall findings indicated that, over time, Texas school districts improved in the percentage of students who approached, met, and mastered grade-level performance on the STAAR math test. The results also indicated that five district-level variables consistently and significantly impacted Grade 5 and 8 students’ math achievement at three performance levels. Significant positive factors included the percentage of English learner students and principal years of experience; significant negative factors were the percentage of economically challenged students, student mobility rate, and teacher turnover rate.

Suggested Citation

  • Shifang Tang & Zhuoying Wang & Kara L. Sutton-Jones, 2020. "A Multilevel Study of the Impact of District-Level Characteristics on Texas Student Growth Trajectories on a High-Stakes Math Exam," Mathematics, MDPI, vol. 9(1), pages 1-13, December.
    • Handle: RePEc:gam:jmathe:v:9:y:2020:i:1:p:8-:d:466529
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    References listed on IDEAS

    as
    1. Zhuoying Wang & Shifang Tang & Kara Sutton-Jones, 2019. "Texas Rural vs. Nonrural School District Student Growth Trajectories on a High-Stakes Science Exam: A Multilevel Approach," Social Sciences, MDPI, vol. 8(6), pages 1-19, May.
    2. Sara B. Heller & Anuj K. Shah & Jonathan Guryan & Jens Ludwig & Sendhil Mullainathan & Harold A. Pollack, 2017. "Thinking, Fast and Slow? Some Field Experiments to Reduce Crime and Dropout in Chicago," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(1), pages 1-54.
    3. Helen F. Ladd & Lucy C. Sorensen, 2017. "Returns to Teacher Experience: Student Achievement and Motivation in Middle School," Education Finance and Policy, MIT Press, vol. 12(2), pages 241-279, Spring.
    4. Elizabeth Dhuey & Justin Smith, 2014. "How important are school principals in the production of student achievement?," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 47(2), pages 634-663, May.
    5. Schwerdt, Guido & West, Martin R., 2013. "The impact of alternative grade configurations on student outcomes through middle and high school," Journal of Public Economics, Elsevier, vol. 97(C), pages 308-326.
    6. Carol S. Parke & Gibbs Y. Kanyongo, 2012. "Student Attendance, Mobility, and Mathematics Achievement in an Urban School District," The Journal of Educational Research, Taylor & Francis Journals, vol. 105(3), pages 161-175, April.
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