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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.

Suggested Citation

  • Kokkelenberg, Edward C. & Sinha, Esha, 2010. "Who succeeds in STEM studies? An analysis of Binghamton University undergraduate students," Economics of Education Review, Elsevier, vol. 29(6), pages 935-946, December.
  • Handle: RePEc:eee:ecoedu:v:29:y:2010:i:6:p:935-946
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
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    Cited by:

    1. David L. Sjoquist & John V. Winters, 2015. "State Merit Aid Programs and College Major: A Focus on STEM," Journal of Labor Economics, University of Chicago Press, vol. 33(4), pages 973-1006.
    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., 2014. "STEM graduates, human capital externalities, and wages in the U.S," Regional Science and Urban Economics, Elsevier, vol. 48(C), pages 190-198.
    4. Bottia, Martha Cecilia & Stearns, Elizabeth & Mickelson, Roslyn Arlin & Moller, Stephanie & Valentino, Lauren, 2015. "Growing the roots of STEM majors: Female math and science high school faculty and the participation of students in STEM," Economics of Education Review, Elsevier, vol. 45(C), pages 14-27.

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