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Viewing access and persistence in engineering through a socioeconomic lens
chapterposted on 06.12.2017, 00:00 by Matthew OhlandMatthew Ohland, M Orr, V Lundy-Wagner, C Veenstra, R Long
“Education, then, beyond all other devices of human origin, is a great equalizer of conditions of man—the balance wheel of the social machinery. . . . It does better than to disarm the poor of their hostility toward the rich; it prevents being poor.” In contrast to Horace Mann’s inspirational words (1848, p. 669), writers from such varying perspectives as Bourdieu and Passeron (1977), Bowles and Gintis (1976), Bernstein (1990), Livingstone (1987), and Giroux (1983) describe various processes by which social class reproduces through the process of education. In this work, we explore the forces promoting social class reproduction by limiting access to and success in college. Because engineering promises high earnings and the first professional degree is the bachelor’s, access to and success in an engineering degree are of particular interest.Graduation rates of engineering students are discussed as they are related to pre-college measures, institution, race/ethnicity, gender, and socioeconomic status (SES). Researchers often have difficulty identifying the contributions of race and ethnicity to degree attainment and separately the role of family background and income (e.g., Corbett, Hill, & St, Rose, 2008; Tinto, 2006). As we look at the dynamics of access and success for students from all backgrounds, there is an urgent need to identify the relationship between economic conditions, gender, and race/ethnicity both to understand and improve engineering student success. With the economic crisis of 2008 and a shift in the past decade from need-based to merit-based aid, financial challenges to low SES students may be even greater, increasing the urgency of this research.This work expands on the research of Ohland and others (e.g., Ohland et al., 2008) using the Multiple-Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD). MIDFIELD includes student data from 12 engineering colleges, including seven of the 50 largest US undergraduate engineering programs (American Society for Engineering Education, 2010). This discussion will center on social justice and the equality of opportunity, especially for minorities and students attending high-poverty high schools. A socioeconomic lens will be defined in terms of SES, “a measure of an individual or family’s relative economic and social ranking” (Donaldson, Lichtenstein, & Sheppard, 2008). While socioeconomic status was borne through the early work of Marx by identifying social classes via property ownership, notions of class also take Bourdieuian form in their attention to power and culture (Collins, 1994), accounting for economic, but also human, cultural, and social capital. While not considered synonymous, SES is often used as a proxy for social class status, although sociologists agree that notions of class have largely gone unresolved (Lareau & Conley, 2008). In social theory, education is both seen as a “great equalizer” and simultaneously as a location for promoting social stratification. That is, individuals from higher social classes will have relatively higher economic, human, cultural, and social capital that will be rewarded in schools, resulting in higher achievement. In educationalresearch, SES is often operationalized as a composite measure of parent education levels, parent occupations, and family income or wealth. In this study, we define our socioeconomic lens in terms of eligibility for free lunch (Harwell & LeBeau, 2010), which is thefourth most common measure for SES, after parental education, occupation, and income (Sirin, 2005). Free lunch eligibility, which is granted if family income is at or less than 130% of the poverty line, is used as a proxy for economic and social ranking. That is, we assume that free lunch eligibility is indirectly related to family income, but directly related to housing and schooling patterns, and accordingly the socioeconomic background of students in particular high schools. From our database, we plan to show the relationship between a student’s socioeconomic background, gender, and race/ethnicity as it relates to college access and graduation rates in our sample of engineering undergraduates.