STEM SCHOOLS VS. NON-STEM SCHOOLS: COMPARING STUDENTS MATHEMATICS STATE BASED TEST PERFORMANCE

Authors

  • Ali Bicer TEXAS A&M University, United States
  • Bilgin Navruz TEXAS A&M University, United States
  • Robert M. Capraro TEXAS A&M University, United States
  • Mary M. Capraro TEXAS A&M University, United States

Abstract

The purpose of this study is to determine how students who participated in T-STEM schools performed on the Texas Assessment of Knowledge and Skills (TAKS) mathematics test compared to their corresponding peers who participated in traditional public schools in Texas. The present study included 18 T-STEM schools, and 18 matched non-STEM schools. The sample for this study is 1887 studentswho were in 11th grade in 2011. A hierarchical linear modeling (HLM) was used to compare students’ mathematics scores.This study also investigates if students who come from traditionally underserved subpopulations increase their mathematics score by participating in T-STEM schools. Results revealed that the mean mathematics scores on TAKS of STEM and non-STEM school students were not statistically significantly different from each other, but participating in STEMschools resulted in a statistically significantly increase on Hispanic students’ mean mathematics score relative to the reference group (White, male, high-SES, non-STEM).

Key Words: STEM, T-STEM academies, Inclusive STEM schools, TAKS, TEA.

References

Beiber, M. E. (2008). Literature overview: Motivational factors in STEM: Interest and self-concept. SWE-AWE CASEE Overviews. Retrieved fromhttp://www.engr.psu.edu/awe/misc/ARPs/ARP_SelfConcept_Overview_122208.pdf

Buxton, C. (2001). Exploring science-literacy-in-practice: Implementations for scientific literacy      from an anthropological perspectives. Electronic Journal in Science and Literacy Education, 1(1). Retrieved from http://sweeneyhall.sjsu.edu/ejlts/

Calkins, L. N., &Welki, A. (2006). Factors that influence choice of major: Why some studentsnever consider economics. International Journal of Social Economics, 33(8), 547-564.

Chapa, J., & De La Rosa, B. (2006).The problematic pipeline demographic trends and Latino participation in graduate Science, Technology, Engineering, and Mathematics programs.Journal of Hispanic Higher Education, 5(3), 203-221.

Cole, D., & Espinoza, A. (2008).Examining the academic success of Latino students in sciencetechnology engineering and mathematics (STEM) majors.Journal of College Student Development, 49(4), 285-300.

Crisp, G., Nora, A., & Taggart, A. (2009). Student characteristics, pre-college, college, and environmental factors as predictors of majoring in and earning a stem degree: Ananalysis of students attending a Hispanic serving institution. American Educational Research Journal, 46(4), 924-942.

Executive Office of the President.(2009). Women and girls in science, technology, engineering,and math (STEM). Retrieved from http://www.whitehouse.gov/ostp/women

Gainen, J. (1995). Barriers to success in quantitative gatekeeper courses. In J. Gainen& E. W. Willemson (Eds.), Fostering student success in quantitative gateway courses (New Directionfor Teaching and Learning, 61). San Francisco: Jossey-Bass.

Gourgey, H., Asiabanpour, B., Crawford, R., Grasso, A., & Herbert, K. (2009).Case study of manor new tech high school: promising practices for comprehensive high schools.Retrieved from http://www.newtechnetwork.org/sites/default/files/dr/manornewtechcasestudy.pdf

Gonzalez, H. B., &Kuenzi, J. J. (2012).Science, technology, engineering, and mathematics (STEM) education: A primer. Congressional Research Service. Retrieved from http://www.fas.org/sgp/crs/misc/R42642.pdf

Hurtado, S. , Cerna, O. S., Chang, J. C., Saenz, V. B., Lopez, L. R., Mosqueda, C., et al. (2006). Aspiring scientist: Characteristics of college freshman interested in the biomedical and behavioral sciences. Los Angeles: Higher Education Research Institute.

Hill, C. J., Bloom, H. S., Black, A. R., &Lipsey, M. W. (2008). Empirical benchmarks forinterpreting effect sizes in research. Child Development Perspectives, 2(3), 172-177.

International Technology Education Association.(1999). Technology for all Americans. Reston, VA: Author.

Kuechler, W. L., McLeod, A., &Simkin, M. G. (2009). Why don’t more students major in IS? Decision Sciences Journal of Innovative Education, 7(2), 463-488.

Lacey, T. A., & Wright, B. (2009).Occupational employment projections to 2018.Monthly Labor Review, 432(11), 82-123.

National Academy of Science, National Academy of Engineering, and Institute of Medicine (2007).Rising above the gathering storm: Energizing and employing America for a brighter economic future. Washington, DC: The National Academies Press.

National Research Council. (2009). Successful K-12 STEM education:Identifying effective approaches in science, technology, engineering, and mathematics. Washington, DC: NAP.

National Research Council.(1996). National science education standards. Washington, DC: National Academy Press.

National Science Board. (2007). National action plan: For addressing the critical needs of the U.S. science, technology, engineering, and mathematics education system. Retrieved from http://www.nsf.gov/nsb/documents/2007/stem_action.pdf

National Science Foundation.(2010). Integrated postsecondary education data system completions survey. Retrieved from https://caspar.nsf.gov/

National Research Council. (2011). Successful K-12 STEM education: Identifying effective approaches in science, technology, engineering, and mathematics. Washington, DC: NAP.

President’s Council of Advisors on Science and Technology. (2010). Prepare and inspire: K-12 education in science, technology, engineering, and math (STEM) for America’s future. Washington, DC. Retrieved from http://www.whitehouse.gov/sites/default/files/microsites/ostp/pcast-stem-ed-final.pdf

Sahin, A., Erdogan, N., Morgan, J., Capraro, M. M., &Capraro, R. M. (2013). The effects of high school course taking and SAT scores on college major selection. Sakarya University Journal of Education, 2(3), 96-109.

Sahin, A. (2013). STEM clubs and science fair competitions: Effects on post-secondary matriculation. Journal of STEM Education: Innovations & Research, 14(1), 5-11.

Schmidt, W. H. (2011, May). STEM reform: Which way to go? Paper presented at the National Research Council Workshop on Successful STEM Education in K-12 Schools. Retrieved from http://www7.nationalacademies.org/bose/STEM_Schools_Workshop_Paper_Schmidt.pdf

U.S. Department of Labor. (2007). The STEM workforce challenge:The role of the public workforce system in a national solution for a competitive science, technology, engineering, and mathematics (STEM) workforce. Washington, DC: Author. Retrieved from http://www.doleta.gov/youth_services/pdf/STEM_Report_4%2007.pdf

Young, H. (2005). Secondary education systematic issues: Addressing possible contributors to a leak in the science education pipeline and potential solutions. Journal of ScienceEducation & Technology, 14(2), 205-216.

Young, V. M., House, A., Wang, H., Singleton, C., & Klopfenstein, K. (2011, May).Inclusive STEMschools: Early promise in Texas and unanswered questions. Paper presented at theNational Research Council Workshop on Successful STEM Education in K-12Schools. Retrieved from http://www7.nationalacademies.org/bose/STEMSchools_Workshop_Paper_Young.pdf         

Downloads

Published

2014-07-31

Issue

Section

Research Article