An Analysis of Binghamton University Undergraduate Students
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Our reference: ECOEDU 1118 P-authorquery-v7 AUTHOR QUERY FORM Journal: ECOEDU Please e-mail or fax your responses and any corrections to: E-mail: [email protected] Article Number: 1118 Fax: +353 6170 9272 Dear Author, Any queries or remarks that have arisen during the processing of your manuscript are listed below and highlighted by flags in the proof. Please check your proof carefully and mark all corrections at the appropriate place in the proof (e.g., by using on-screen annotation in the PDF file) or compile them in a separate list. For correction or revision of any artwork, please consult http://www.elsevier.com/artworkinstructions. Articles in Special Issues: Please ensure that the words ‘this issue’ are added (in the list and text) to any references to other articles in this Special Issue. Uncited references: References that occur in the reference list but not in the text – please position each reference in the text or delete it from the list. Missing references: References listed below were noted in the text but are missing from the reference list – please make the list complete or remove the references from the text. Location in Query / remark article Please insert your reply or correction at the corresponding line in the proof Q1 Please check the missing reference: Bean (1980). Q2 Please set the ‘appendix section.’ Electronic file usage Sometimes we are unable to process the electronic file of your article and/or artwork. If this is the case, we have proceeded by: Scanning (parts of) your article Rekeying (parts of) your article Scanning the artwork Thank you for your assistance. G Model ECOEDU 1118 1–12 ARTICLE IN PRESS Economics of Education Review xxx (2010) xxx–xxx 1 Contents lists available at ScienceDirect Economics of Education Review journal homepage: www.elsevier.com/locate/econedurev 1 Who succeeds in STEM studies? An analysis of Binghamton University 2 undergraduate students a,∗ b,1 2 Edward C. Kokkelenberg , Esha Sinha 3 a Department of Economics, SUNY at Binghamton, and School of Industrial and Labor Relations, Cornell University, Ithaca, NY, 14850, USA 4 b Committee on National Statistics, National Academy of Science, Washington, DC, 20001, USA 5 6 a rticle info abstract 7 8 Article history: Using student level data, the characteristics of STEM and Non-STEM students are examined 9 Received 28 June 2010 for attributes associated with academic success. We use fixed effects models to analyze the 10 Accepted 29 June 2010 variables’ role in attaining graduation and college GPA and find preparation and ability, as 11 evidenced by Advanced Placement course work, mathematical ability, gender, ethnicity, 12 JEL classification: high school GPA and college experience are all statistically significant indicators of success. 13 C23 These attributes may confer a comparative advantage to STEM students. The engineers have 14 I20 statistically significant differing response elasticities than the non-engineers, and show 15 I23 evidence of persistence that may arise from learning-by-doing. A successful engineering 16 Keywords: STEM major at Binghamton has good mathematics preparation, and disproportionately is 17 STEM preparation of Asian ethnicity. Women are few in numbers as engineers. Other STEM fields see less 18 Fixed effect models emphasis on mathematics preparation, but more emphasis on the presence of AP course 19 Women in STEM fields work. Women have the same presence in these other STEM fields as in the whole university. 20 Comparative advantage 21 Learning-by-doing © 2010 Published by Elsevier Ltd. 22 1. Introduction 1995–96. But from 1996–97 to 2001–02 all the engineer- 35 ing fields declined (National Academies, 2006; Snyder & 36 23 The question of academic success is important for Amer- Dillow, 2010; US Department of Education, 2009). 37 24 ican society and the apparent paucity of STEM students is If one looks at the history of people who are successful 38 25 of national concern. As an example, the number of under- in the arts such as music or dance, or one considers people 39 26 graduate students earning a degree in engineering and who are successful in highly technical fields such as astro- 40 27 engineering technologies has fallen about 16 percent over a physics, we find these individuals often had an interest in 41 28 twenty-year period (1985–86 to 2005–06). The first fifteen their area since early childhood or at the least, since middle 42 29 of these years saw a decline of 25%. But, the last five saw school. So it should be no surprise that the successful stu- 43 30 the number of degrees conferred in engineering and engi- dents in STEM courses probably had an interest in STEM 44 31 neering technologies increase 12%, though the numbers did fields for many years before college. Is this early interest 45 32 not reach the level of 1985–86. The decline was uneven evidence of a comparative advantage? Or does this early 46 33 when specific fields are considered. For example, Chemical experience provide learning-by-doing? 47 34 and Civil Engineering had positive growth from 1985–86 to Following that line of thought, researchers have con- 48 sidered STEM precursors in K-12 schools. For example, 49 various international surveys on high school students’ sci- 50 ence and mathematics performance are conducted (Baldi, 51 ∗ Corresponding author. Tel.: +1 607 273 0882. Jin, Skemer, Green, & Herget, 2007; Gonzales et al., 2008). 52 E-mail addresses: [email protected] (E.C. Kokkelenberg), However, less attention has been focused on the prob- 53 [email protected] (E. Sinha). 54 1 Tel.: +1 202 334 3946. lem in higher education and the observed high drop-out 0272-7757/$ – see front matter © 2010 Published by Elsevier Ltd. doi:10.1016/j.econedurev.2010.06.016 Please cite this article in press as: Kokkelenberg, E. C., & Sinha, E. Who succeeds in STEM studies? An analysis of Binghamton University undergraduate students. Economics of Education Review (2010), doi:10.1016/j.econedurev.2010.06.016 G Model ECOEDU 1118 1–12 ARTICLE IN PRESS 2 E.C. Kokkelenberg, E. Sinha / Economics of Education Review xxx (2010) xxx–xxx 55 rates from science and mathematics majors. Women formally drop out of STEM studies but are better trained 111 56 and/or non-white students opt out of STEM majors at dis- individuals for their academic experience. We are not able 112 57 proportionate rates. And US universities have not kept pace to follow such a student or drop-out with our data and thus 113 58 with rest of the world in the production of STEM graduates. this issue is not addressed. 114 59 Even though a young student’s interest in a STEM career A further criticism of graduation or grades as a measure 115 60 may start before she enters college or a university, it’s the of a successful outcome is that they do not reflect the qual- 116 61 postsecondary education that creates the career path and ity of the education of the student. The time students spend 117 62 prepares the student for work in a STEM occupation. Hence, in exploring different majors and taking elective courses 118 63 it is important to analyze the university/college experience may better prepare them to be life-long learners and better 119 64 with STEM courses and the reasons for the high attrition citizens. From this perspective, measures of the educational 120 65 rates from STEM majors. output are the intelligence, the existence of a breadth of 121 66 Our paper examines the characteristics of STEM stu- knowledge, understanding, their ability to adapt and learn 122 67 dents at Binghamton University (State University of New on the job and thus become more productive, and personal 123 68 York at Binghamton) and explores the differences between satisfaction of the citizenry as well as their contribution to 124 69 STEM students and Non-STEM students in an attempt to the commonweal. 125 70 shed light on the question of academic success. We also We use both Grade Point Average and graduation rates 126 71 test the validity of some of the hypotheses that have been as measures of success in this paper. We do note there 127 72 offered to explain the gap between intended and completed are limitations to both; Bretz (1989), using Meta analy- 128 73 STEM field majors. We must caution the reader that we sis, found success in a field is weakly related to GPA for 129 74 have not found a clear answer to these questions, but we some fields (e.g. teaching) but not related to success in most 130 75 have found some things that are important including the fields. Further, graduation rates are partially controlled by 131 76 differential of the correlates of a student’s academic success institutional characteristics, particularly funding. A good 132 77 in various STEM and Non-STEM fields. introduction to modern research on this issue together 133 78 In the following sections, we first consider some def- with a good bibliography is given in Calcagno, Bailey, 134 79 initional issues, and next discuss STEM research. This is Jenkins, Keens, and Leinbach (2008). Also see DesJardins, 135 80 followed by a description of our model for subsequent Kim, and Rzonca (2002–2003) and Braxton and Hirschy 136 81 econometric analysis. The fifth section is a description of (2004, 2005). Many of the issues are identified in Habley 137 82 Binghamton data and the sixth section gives the results of and McClanahan (2004). Adelman (1999) is also useful. 138 83 the econometric analysis. Finally, we discuss and conclude. Neither the use of grades nor that of graduation, consid- 139 ers variations in the length of a degree program.