An Analysis of Female STEM Faculty at Public Two-Year Institutions
Author(s) -
David Koonce,
Valerie Martin Conley,
Dyah A. Hening,
Cynthia Anderson
Publication year - 2020
Publication title -
2011 asee annual conference and exposition proceedings
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--17442
Subject(s) - salary , higher education , institution , statistics education , statistical analysis , public institution , medical education , psychology , mathematics education , statistics , political science , sociology , mathematics , medicine , social science , law
Compared to four-year institutions, limited research exists on the careers of female faculty teaching STEM at public two-year institutions. Unfortunately, the mission and structure of twoyear schools differs greatly from their well-studied counterparts. Thus the explanatory power of STEM career success and advancement outcomes of female faculty in the four-year sector cannot explain how female faculties succeed at public, two-year schools. For example, female STEM faculty hold near parity in the percents achieving the ranks of professor or associate professor at public two-year schools, while they are half as likely to rise to those levels at fouryear schools. This paper presents a quantitative analysis on career success and employment outcomes in STEM fields using data from National Study of Postsecondary Faculty (NSOPF), with focus on the most recent survey in 2003-4. The analysis will be based on the hypothesis of the effect of gender on salary, rank, part-time status, highest degree and field of teaching for faculty in twoyear institution compare to four-year institution. Prediction models were built on statistical analysis tools provided by the National Center of Education Statistics (NCES); DAS and Powerstats. The factors associated with advancement and employment outcomes were investigated and preliminary outcomes was confirmed by the qualitative analysis. Due to differences of STEM definition, this paper will also present a clear definition of STEM, using CIP and NSOPF codes. Major definitions of STEM will be mapped into the major classification codes including CIP, BLS Occupational Codes and NSF. Further research on this study is based on the comparison of the result of this paper and the actual data collected.
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