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Who succeeds in STEM studies? An analysis of Binghamton University undergraduate students

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  • Kokkelenberg, Edward C.
  • Sinha, Esha

Abstract

Using student level data, the characteristics of STEM and Non-STEM students are examined for attributes associated with academic success. We use fixed effects models to analyze the variables' role in attaining graduation and college GPA and find preparation and ability, as evidenced by Advanced Placement course work, mathematical ability, gender, ethnicity, high school GPA and college experience are all statistically significant indicators of success. These attributes may confer a comparative advantage to STEM students. The engineers have statistically significant differing response elasticities than the non-engineers, and show evidence of persistence that may arise from learning-by-doing. A successful engineering STEM major at Binghamton has good mathematics preparation, and disproportionately is of Asian ethnicity. Women are few in numbers as engineers. Other STEM fields see less emphasis on mathematics preparation, but more emphasis on the presence of AP course work. Women have the same presence in these other STEM fields as in the whole university.

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Bibliographic Info

Article provided by Elsevier in its journal Economics of Education Review.

Volume (Year): 29 (2010)
Issue (Month): 6 (December)
Pages: 935-946

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Handle: RePEc:eee:ecoedu:v:29:y:2010:i:6:p:935-946

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Web page: http://www.elsevier.com/locate/econedurev

Related research

Keywords: STEM preparation Fixed effect models Women in STEM fields Comparative advantage Learning-by-doing;

References

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  1. Montmarquette, Claude & Cannings, Kathy & Mahseredjian, Sophie, 2002. "How do young people choose college majors?," Economics of Education Review, Elsevier, vol. 21(6), pages 543-556, December.
  2. Calcagno, Juan Carlos & Bailey, Thomas & Jenkins, Davis & Kienzl, Gregory & Leinbach, Timothy, 2008. "Community college student success: What institutional characteristics make a difference?," Economics of Education Review, Elsevier, vol. 27(6), pages 632-645, December.
  3. Robert B. Archibald & David H. Feldman, 2008. "How to Think About Changes in Higher Education Affordability," Working Papers 76, Department of Economics, College of William and Mary.
  4. Cohn, Elchanan & Cohn, Sharon & Balch, Donald C. & Bradley, James Jr., 2004. "Determinants of undergraduate GPAs: SAT scores, high-school GPA and high-school rank," Economics of Education Review, Elsevier, vol. 23(6), pages 577-586, December.
  5. Kokkelenberg, Edward C. & Dillon, Michael & Christy, Sean M., 2008. "The effects of class size on student grades at a public university," Economics of Education Review, Elsevier, vol. 27(2), pages 221-233, April.
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Cited by:
  1. David L. Sjoquist & John V. Winters, 2013. "State Merit-Aid Programs and College Major: A Focus on Stem," Economics Working Paper Series 1406, Oklahoma State University, Department of Economics and Legal Studies in Business.
  2. Ehrenberg, Ronald G., 2010. "Analyzing the factors that influence persistence rates in STEM field, majors: Introduction to the symposium," Economics of Education Review, Elsevier, vol. 29(6), pages 888-891, December.
  3. Winters, John V., 2013. "STEM Graduates, Human Capital Externalities, and Wages in the U.S," IZA Discussion Papers 7830, Institute for the Study of Labor (IZA).

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