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Abstract

Study of four-year broad access institutions (BAIs) is important given their influence on postsecondary educational opportunities and the continued importance of the bachelor's degree in earnings premiums and critical social and civic outcomes. Descriptive results add to current understanding regarding heterogeneity of four-year BAIs by identifying sizable differences within such public and private four-year institutions. Additionally, cluster analysis findings extend Carnegie's inclusiveness category by grouping public and private four-year BAIs into more meaningful categories. Results contribute evidence that the concept of "inclusivity" is important, complex, and must be considered through a multi-dimensional research and policy lens.

Keywords

broad access institutions, four-year, classification system, typology

Postsecondary education in the United States offers a growing range of colleges and universities designed to meet local, regional, national, and international needs and educate a diverse group of students who aspire to earn a variety of credentials (Prescott, 2011; Stevens, Proctor, Klasik, & Baker, 2011). Although a substantial amount of scholarly and public attention is paid to the most selective institutions that engage in high or very high levels of research activity (e.g., Kane, 1998; Kirst, Stevens, & Proctor, 2010), these institutions serve a small percentage of postsecondary students making up a mere five percent of degree granting, non- profit U.S. institutions in the 2010–11 academic year (Carnegie Classifications, n.d.). The majority of colleges and universities are more accessible, granting admission to all or the majority of applicants (Committee for Economic Development, 2012; Jenkins & Rodriquez, 2013). Within this sector, there is a growing number and proportion of bachelor degree granting institutions classified as for-profit or Minority Serving (Dervarics, 2014; Staklis, Bersudskaya, & Horn, 2011), resulting in a population of colleges and universities increasingly stratified in terms of resources, reputation, and racial/ethnic diversity (Carnevale & Strohl, 2013). In fact, in the past 50 years, at least half of colleges and universities have become more, rather than less accessible (Hoxby, 2009). [End Page 1374]

Colleges and universities are commonly classified as being more or less selective in their undergraduate admissions criteria, and the most accessible institutions have historically been referred to as non- or less-selective institutions (Kirst, Stevens, & Proctor, 2010). Although there is not one commonly accepted definition, scholars have begun to use the term "broad access" to describe the diversity of non-elite public and private colleges and universities that offer admission to the majority or even all students and/or offer no or few doctoral degrees (Crisp, Doran, & Salis Reyes, 2014; Doyle, 2010; Kirst, Stevens, & Proctor, 2010; Wellman, 2011). Currently, broad access institutions (BAIs) enroll about sixty percent of all students in postsecondary education, including the majority of low-income and non-traditional age students (Jenkins & Rodriguez, 2013). Although the majority of BAIs are classified as community colleges, a growing percentage of accessible institutions are four-year universities (Crisp, Doran, & Salis Reyes, 2014) with forty percent of all four-year students attending state universities that do not offer or offer few doctoral degrees (Selingo, 2015). BAIs are the "backbone of the nation's workforce development system, creators of human capital, and engines of economic growth" (Committee for Economic Development, 2012, p. 10). Accessible colleges and universities provide postsecondary access to millions of Americans who otherwise would not have the opportunity to earn a degree (Klempin & Karp, 2015). BAIs also serve the majority of Latina/o college students and enroll a disproportionate number of English-language learners (ELLs), undocumented students, and non- traditional age students (Hurtado, 2009). Moreover, BAIs play an increasingly critical role in national efforts to maintain college affordability (Kirst, Stevens, & Protor, 2010).

Efforts are increasing among the higher education and policy communities to describe BAIs (e.g., Kirst, Stevens, & Proctor, 2010) as well as to develop a classification scheme that meaningfully distinguishes different types of institutions (e.g., Núñez, Crisp, & Elizondo, 2016) and the students they serve (e.g., Bahr, 2010). Classification schemes or typologies of higher education institutions serve several purposes including identifying and/or ranking similar "peer" institutions and encouraging diversity within and between postsecondary institutions (Howells, Ramlogan, & Cheng, 2008). Further, institutional typologies are assumed to be useful in finding ways to improve institutional and student outcomes (e.g., Denham, 2005; Dolton & Makepeace, 1982; Marginson & van der Wende, 2007; Sanoff, Usher, Savino, & Clarke, 2007).

An early goal of the Carnegie classification system, the dominant and arguably default (McCormick & Zhao, 2005) way to describe, categorize, and characterize postsecondary institutions, was to promote diversity by encouraging the development of accessible two and four-year institutions (Ruef & Nag, 2011). A category within the Undergraduate Profile Classification is [End Page 1375] four-year institutions classified as "inclusive" (Carnegie Foundation, n.d.). It may be assumed that inclusive institutions have different value propositions and might be distinguished one from the other in different ways than other institutions (Stevens et al., 2011). However, the inclusiveness category currently provides little granularity in distinguishing BAIs. Further, empirical typology studies to date (e.g., Bernasconi, 2006; Fumasoli & Huisman, 2013; Huisman, 1998; Shin, 2009) have failed to give attention to distinguishing BAIs (Ruef & Nag, 2011. The absence of a typology to distinguish among 4-year BAIs is notable given recent descriptive findings (Crisp, Doran, & Salis Reyes, 2014) that highlight substantial variance within and between broad access four-year institutions on characteristics not accounted for by Carnegie or existing empirical work.

According to Kirst, Stevens, and Proctor (2010), a top priority for educational researchers should be to describe BAIs to the same extent that more selective universities have been described. In particular, research is needed that extends Carnegie's inclusiveness category to cluster or group accessible institutions into more "meaningful, analytically manageable categories" (Prescott, 2011, p. 1). Within this, there is a need to separate out and better examine the diversity between four-year BAIs by key features already known to differentiate institutions, namely control (i.e., public and private). As such, this paper seeks to describe and classify four-year U.S. institutions that offer broad access to students by addressing the following research questions:

  1. (1). In what ways are public and private four-year broad access institutions diverse?

  2. (2). Uniquely among public and private colleges and universities, can accessible four-year institutions be separated into distinct types such that each institution is more similar to other institutions in its group than to institutions outside of the group?

Background and Related Literature

In the United States, the Carnegie Foundation for the Advancement of Teaching classification system has played a particularly important role in the typology of institutions. As their history describes, the framework, in existence for more than 40 years, "has been widely used in the study of higher education, both as a way to represent and control for institutional differences, and also in the design of research studies to ensure adequate representation of sampled institutions, students, or faculty" (Carnegie Classifications, n.d.). The Carnegie system also represents the most empirically based and extensive taxonomy for U.S. universities and colleges. At the same time, the present Carnegie system remains limited in fully accounting for heterogeneity among institutional types (Prescott, 2011). However, the Carnegie classification [End Page 1376] system continues to evolve and change to reflect the diversity of higher education institutions (Ruef & Nag, 2011). Among the current Carnegie classification systems1 is the Undergraduate Profile that includes a category for broad access four-year institutions termed "inclusive." Inclusive institutions are defined as colleges and universities that do not require applicants to submit standardized exam scores or "extend educational opportunity to a wide range of students with respect to academic preparation and achievement" (Carnegie Foundation, n.d.).

Although the Undergraduate Profile considers the percentage of full-time students and an institution's transfer in rate in distinguishing institutions by inclusiveness, it provides little ability to distinguish within and between four-year BAIs on other salient and differentiating characteristics (e.g., racial/ethnic background of students and faculty, finances). Ruef and Nag (2011) note that the "a priori" approach utilized by analysts to develop mutually exclusive categories that distinguish institutions may be ill-suited to capture new or emergent organizational forms. Moreover, a priori institutional classifications may hide internal variability within institutional types (Huisman, Lepori, Seeber, Frolich, & Scordato, 2015). As such, empirical work is recommended that allows data to drive the development of institutional types (Ruef & Nag, 2011). Unfortunately, although classification schemes have existed for well more than a century (Howells, Ramlogan, & Cheng, 2008), relatively little empirical attention has been given to the conceptualization and measurement of institutional diversity (Huisman et al., 2015). There are a growing number of books and articles to describe different types of Minority Serving Institutions (MSIs), many of which also provide broad access to students (e.g., Gasman, Baez, & Turner, 2008; Núñez, Hurtado, & Calderon Galdeano, 2015). Moreover, recently increasing attention is being given to classifying different types of broad access community colleges (i.e., Hardy & Katsinas, 2006; Katsinas, 2003; Merisotis & Shedd, 2003) and students (e.g., work by Bahr, 2010, 2011). However, bachelor's degree granting BAIs have failed to receive appropriate attention from scholars (Kirst, Stevens, & Proctor, 2010).

Within the broader line of empirical work that has sought to study the forms, purpose, and roles of typologies of universities (e.g., Bernasconi, 2006; Fumasoli & Huisman, 2013; Merisotis & Shedd, 2003; Shin, 2009; van Vught, 2008), there appears to be a relative amount of consensus that certain characteristics, such as enrollment size and control (public versus private) are important to consider and that the characteristics used to distinguish institutions should be directly related to the core functions of higher education institutions. However, by and large existing empirical typology work has shown a considerable amount of divergence in the use of characteristics [End Page 1377] used to distinguish institutions (Huisman et al., 2015). For instance, recent empirical work by Ruef and Nag (2011) utilized Latent Dirichlet Allocation (LDA) modeling to develop a new classification system for the population of American colleges and universities. They find that there is very little variance among less inclusive, elite research universities and yet a sizable amount of diversity among BAIs. Unfortunately, their work does not clearly define BAIs, distinguish between community colleges and four-year universities, or utilize diverse set of characteristics in classifying institutions.

Ruef and Nag (2011) note that institutional classifications have become decoupled from the organizational literature, which provides a range of theoretical perspectives and tools for understanding the diversity of colleges and universities. One exception is recent work by Núñez, Crisp, and Elizondo (2016) that provides an empirical typology of Hispanic Serving Institutions (HSIs) using a conceptual framework developed from Harris's dimensions of institutional diversity (2013), resource dependence theory (Pfeffer & Salancik, 1978), and empirical work specific to HSIs. Núñez et al. identified six types of HSIs, distinguished by five interrelated types or forms of diversity including (1) systemic, (2) programmatic, (3) constituential, (4) resource, and (5) environmental. Importantly, Núñez et al.'s work extends the Carnegie classification system in classifying HSIs by reflecting additional aspects of diversity shown to be salient to HSIs (e.g., resource diversity).

Although the majority of four-year broad access institutions are not HSIs or MSIs (Crisp, Doran, & Salis Reyes, 2017), nearly all four-year HSIs are classified as baccalaureate or master's institutions and admit the majority of applicants (Núñez & Elizondo, 2015). As such, Núñez, Crisp, and Elizondo's (2016) framework may be assumed to be useful and relevant in developing an empirical typology for the broader group of four-year broad access institutions.

Although little is known regarding the diversity of four-year broad access institutions, descriptive work suggests that four-year BAIs are heterogeneous and can be meaningfully distinguished from more selective institutions. To begin with, institutional control (i.e., whether an institution is public or private) and enrollment size have been shown to be salient measures of "systemic diversity" (Harris, 2013) within the higher education system as well as specifically for four-year BAIs. Many private institutions have small enrollments and are relatively well funded, while the majority of public institutions are large and disproportionately rely on financial support from state governments. However, there are numerous exceptions in both directions (Claar & Scott, 2003). Crisp, Doran, and Salis Reyes, 2014 found public institutions to be significantly overrepresented among four-year BAIs when compared to other, more selective four-year colleges and universities. At the same time, findings showed that small universities (enrolling 1,000 or [End Page 1378] fewer students) were overrepresented among four-year BAIs. Crisp et al.'s (2014) work also suggests that religious affiliation may be a relevant form of systemic diversity when classifying four-year BAIs, as 19 percent of BAIs are faith-based compared to a mere three percent of more selective institutions.

Four-year BAIs have been shown to enroll a higher proportion of students who are not prepared for college-level coursework and who enroll in developmental classes (Arum & Roksa, 2015; Committee for Economic Development, 2012), making institutional remedial services an important form of "programmatic diversity" (Harris, 2013) to consider in developing an empirically derived typology. As well, although not currently emphasized by the Carnegie system, empirical evidence suggests that students, institutional staff, and faculty, referred to as "constituential diversity" by Harris (2013), may be particularly salient to understanding variance within and between four-year BAIs. Broad access institutions have been shown to enroll an increasingly diverse student body (Deil-Amen, 2015). Moreover, Minority Serving Institutions (MSIs) and enrollment of Latina/o students in particular, have been shown to be overrepresented among four-year BAIs when compared to more selective institutions (Crisp, Doran, & Salis Reyes, 2014). Students attending BAIs are more often the first members of their family to attend college, attend part- time, and/or struggle to manage both coursework and family responsibilities (Committee for Economic Development, 2012). Four-year BAIs have also been found to serve a significantly older student population and a higher percentage of students receiving federal Pell Grant support when compared to more selective institutions (Crisp et al., 2014). It may be anticipated that graduation rates are in general lower at BAIs when compared to other universities (Alon & Tienda, 2005; Arum & Roksa, 2015; Melguizo, 2008). However, large variance has been documented between the graduation rates at four-year BAIs (Crisp, Doran, & Salis Reyes, 2017), making student outcomes an important form of constituential diversity to consider in describing and differentiating four-year BAIs.

Resource dependency theory (Pfeffer & Salancik, 1978) and empirical research focused on BAIs further support the value of considering environmental and resource diversity (Núñez, Crisp, & Elizondo, 2016) in distinguishing four-year BAIs. There is limited but compelling evidence to suggest that county characteristics surrounding broad access institutions may be useful in developing a typology, as findings by Crisp, Doran, and Salis Reyes, (2014) indicated that four-year BAIs were overrepresented in rural areas and were slightly less prevalent when compared to other four-year institutions in towns. Four-year BAIs have also been found to be significantly under-resourced when compared to more selective institutions (Carnevale & Strohl, 2013; Crisp, Doran, & Salis Reyes, 2017), and disparities in resources for students have significantly grown over time (Hoxby, 2009). On the whole, both public and [End Page 1379] private institutions that are more selective have more resources (e.g., higher tuition, endowments) when compared to BAIs. For instance, public BAIs (both two- and four-year) have been documented as being more dependent on local and state revenues when compared to other institutional types including, but not limited to, private four-year institutions that have access to large endowments (Committee for Economic Development, 2012; Wellman, 2011). Carnevale and Strohl (2013) found that the 468 most selective institutions spend twice as much per student on instruction when compared to BAIs. Additionally, more selective institutions have been shown to provide substantially more support to students in terms of access to full-time faculty and graduate schools. Further, Crisp, Doran, and Salis Reyes, (2014) found that the average salary of full-time faculty at four-year BAIs on average was significantly lower than salaries at more selective four-year universities.

At the same time, numerous financial issues/characteristics further differentiate public and private BAIs including governance, independence, state funding, and final budget approval (Claar & Scott, 2003). Public BAIs have been found to be relatively more affordable, with significantly lower tuition and fees when compared to other public universities (Crisp, Doran, & Salis Reyes, 2014). Additionally, tuition and fees at four-year private BAIs have been shown to be substantially less than at more selective four-year private universities (16,000 dollars per year compared to over 26,000 dollars). Similarly, more selective private institutions were found to spend significantly more on instruction, academics, and student services per full-time student when compared to private BAIs (Crisp, Doran, & Salis Reyes, 2014). Together, these differences provide support for considering public and private institutions separately (particularly with regard to resources) in developing a typology of four-year BAIs.

In summary, the relatively modest extant literature suggests that additional empirical work is needed to better describe and differentiate between four-year broad access institutions. Although Carnegie currently has a category to identify inclusive institutions, existing literature highlights the value in utilizing an empirical approach to development of a typology that considers a broader set of theoretically grounded characteristics. In particular, the above-referenced theory and empirical work supports utilizing a model that considers multiple forms of diversity shown to be salient to broad access institutions (i.e., systemic, constituential, programmatic, resource, and environmental).

Method

Data/Sample

Data were drawn from the Integrated Postsecondary Education Data System (IPEDS) for 2014–15 as well as from U.S. Census Data in the 2008–2012 [End Page 1380] American Community Survey (National Center for Education Statistics, n.d.). Our sample was drawn from the entire population of accredited, active, public, Title IV, private not-for-profit, and private for-profit four-year institutions. The sample provided an extremely diverse group of institutions offering bachelor's degrees including but not limited to liberal arts colleges, private religiously affiliated colleges, the lesser number of accredited bachelor's degree granting for-profit institutions, the growing number of colleges that now offer baccalaureate degrees but that were founded as "junior colleges" or "community colleges," and the relatively small number of regional and state universities2 that admitted 80 percent or more of applicants (n =1,073).

Variables

As shown in Appendix A, our model considered a broad range of systemic diversity characteristics including institutional control, whether an institution was classified as for-profit or non-profit, acceptance rate, if the institution was religiously affiliated, the total undergraduate enrollment size in 2014, the highest degree offered by the institution, and degree focus (Harris, 2013). Degree focus was operationally defined from the IPEDS institutional category variable that distinguishes institutions labeled as "degree-granting, not primarily baccalaureate or above" from institutions labeled as "degree-granting, primarily baccalaureate or above." According to IPEDS, the total number of degrees/certificates at or above the bachelor's level awarded divided by the total number of degrees/certificates awarded must be less than or equal to 50 percent for an institution to identify as "not primarily baccalaureate or above."

Our model also considered remedial and distance education services as a form of institutional programmatic diversity as well as a broad range of constituential diversity characteristics considered in the Carnegie classification system that were assumed to influence and differentiate four-year accessible institutions (Harris, 2013). Specifically, we included the ratio of part- to full-time students, the percent of non-White students, and the percentage of undergraduate students receiving Pell grant support (as a rough proxy for socio-economic status). Institutional second year retention rates for the full-time cohort and six-year bachelor's degree completion rates for first-time, full-time degree seeking students were also included as descriptors of the student body. Similar to Núñez, Crisp, and Elizondo's (2016) model, we also included resource and environmental diversity in classifying four-year BAIs. We considered several measures of resources including academic support expenses, total revenue from tuition and fees per student, and average [End Page 1381] salary for full-time faculty. Finally, our model considered three characteristics of the county surrounding the institution that are assumed to influence and differentiate four-year accessible institutions. Environmental diversity measures include urbanicity (location in a city, suburb, town, or rural area) and county characteristics including the percentage of residents who were unemployed and median salary.

Analytical Approach

To answer the research questions of interest, the study presents a robust descriptive representation of the institutions included, carefully attending not only to the central tendencies but, importantly, to the distributional characteristics as well. We used cluster analysis to classify institutions into groups based on measured characteristics (Kaufman & Rousseeuw, 1990; Kogan, 2007). Cluster analysis was the appropriate strategy in this case given the exploratory nature of the research questions and our interest in understanding in more nuanced ways the associations among institutions. Specifically, we used SPSS Two-Step clustering that, in the first step, constructs a modified cluster feature tree using both categorical and continuous variables. The second step takes sub-clusters resulting from the first step as input and groups using the agglomerative hierarchical clustering method. The analysis tests number of clusters using the automatic option, with maximum of 15. Public and private institutions were analyzed separately, running each three times after a random sort for each of the clustering criterion (AIC/BIC) option. Following the recommendation of Hair, Tatham, Anderson and Black (2009), we also ran the models with only the important variables to examine the extent to which the more parsimonious model improved the fit of the clusters.

Prior to analysis, data for public and private BAIs were screened for multicollinearity, missing data, outliers, normality, and appropriateness of inclusion. The percentage of minority faculty was shown to have too much missing data and was therefore excluded. Moreover, although we had intended to use a fuller set of county characteristics, many were shown to be highly correlated, which would give the group of characteristics too much weight in the cluster analysis. As such, we selected to use the unemployment rate and median housing price as these variables were thought to be representative of the characteristics of interest. Retained variables were not found to have variance inflation factors (VIF) greater than 2.688. Extreme cases (e.g., institutions with an enrollment of 0 or 1) were excluded. Further, Mahalanobis distance values were evaluated to identify additional outliers to be removed (n = 121). Box Cox transformations were used to address normalization issues for several variables including undergraduate enrollment, percent of students awarded Pell grants, tuition and fees, and median earnings. The final datasets were shown to have very small amounts of missing data with the majority of [End Page 1382] variables not missing any data (highest percentage of missing data was 4%). Multiple Imputation (MI) was used to impute data that were assumed to be missing at random (MAR) (Manly & Wells, 2015).

Limitations

Several limitations bound our study findings. First, although a limited amount of data were shown to be missing, the imputation procedure may have had a meaningful impact on the study findings. Additionally, there were several variables of interest (e.g., percentage of classes taught online, percentage of full-time faculty, specific program offerings, transfer focus) that were not used in the cluster analysis due to a lack of availability in IPEDS, multicollinearity (i.e., VIF values higher than 10), and/or missing data issues. This exclusion of variables may impact our findings and/or interpretation of the findings, as cluster analysis is highly sensitive to variable selection. Additionally, the student enrollment variables in the 2014–15 IPEDS data collection largely excluded transfer and part-time students that are served by accessible 4-year institutions. It is notable that for-profit institutions were slightly overrepresented among the outliers and cases with high amounts of missing data. Finally, the present study is limited in that it only considers data from a single year, which only statically captures what, in many cases, are arguably much more dynamic contributors to institutional classification.

Results Description of Public Broad Access Institutions

As shown in Tables 1 and 2, descriptive results reveal a great deal of variation within and between accredited public (n = 266) and private (n = 807) four-year BAIs in 2014. Among public institutions, 43 percent had an open admissions policy while the remaining 57 percent of public colleges and universities offered admission to at least 80 percent of applicants. Tremendous heterogeneity was shown with regard to enrollment size at public BAIs, with institutions enrolling anywhere between 287 and over 66,000 undergraduate students (SD = 8,709). A third of institutions did not primarily offer four-year degrees (i.e., community colleges that offered some bachelor's degrees) while the majority of public 4-year BAIs primarily offered 4-year degrees. Similarly, about a third of institutions offered bachelor's degree as the highest degree, while 31 percent offered master's degrees or certificates and only 35 percent of 4-year BAIs offered doctoral degrees.

Eighty nine percent of public BAIs were found to offer remedial services to students while nearly all (99%) institutions offered distance education courses. The average public BAI served a student body that was 24 percent non-White, although the percentage of non-White students varied between 4 and 99 percent. The ratio of part- to full-time enrollment was .51, with [End Page 1383] substantial variation between institutions (SD = .35). On average, 47 percent of public BAI students received Pell Grants, although the percentage ranged as low as 13 percent and as high as 97 percent (SD = 16). Large variance was also shown with regard to retention and graduation rates. The average one-year retention rate was 68 percent, although some institutions only retained 42 percent of students while others retained 91 percent to year two (SD = 9). Similarly, although the mean six-year graduation rate at public BAIs was 39 percent, some universities graduated as few as four percent of students while other BAIs successfully graduated 76 percent of students within six academic years (SD = 15).

Variation was also shown regarding resources and the characteristics of the county surrounding public BAIs. The average BAI spent 11 percent of core expenses on academic services and generated $6,942 per student in tuition and fees. However, tuition and fees ranged between $2,378 and $16,552 (SD = $2,954). Tremendous variation was also shown with regard to faculty salaries. The average salary at public BAIs was $64,751 although some institutions paid faculty a mean salary of just $38,934 while others provided a more generous average salary of $98,523 per year. The majority of public BAIs were located in cities and suburbs (60%), roughly a third (29%) were in towns, and the remaining institutions were found in rural areas. In terms of county characteristics, large differences were shown in terms of unemployment rates and median salaries. Some public BAIs were located in counties with a median annual salary of just $11,378 dollars while others were situated in more affluent counties with that had a median annual salary of $65,147 dollars (M = 30,445; SD = 6,639).

Description of Private Broad Access Institutions

Similar to public broad access institutions, private colleges and universities were shown to be remarkably diverse. Roughly half (47%) of private institutions in our sample were non- profits and just over one fourth (27%) were religiously affiliated. To begin with, 66 percent of institutions offered open admission while the remaining 34 percent of institutions admitted at least 80 percent of applicants. When compared to public BAIs, privates were noticeably smaller with an average undergraduate enrollment of 1,307 students. It is notable however that some private institutions served just 13 students while others enrolled over 45,348 students (SD = 2,693). Private universities were found to offer relatively fewer masters and doctoral degrees when compared to public institutions. Slightly more than a third (38%) of privates did not primarily offer four-year degrees. Roughly half (47%) of private institutions offered bachelor's degree as the highest degree, while about a third offered master's degrees or certificates and just 17 percent of 4-year BAIs offered doctoral degrees. [End Page 1384]

Table 1. V 4- P B A I ( = 266) *IPEDS definitions exclude transfer and part-time students and values likely do not accurately reflect all students. **Median used account for extreme salaries Totals may not sum to 100% due to rounding. Data Sources: IPEDS 2014-15 data and U.S. Census (2008-12 American Community Survey)
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Table 1.

Variation among 4-year Public Broad Access Institutions (n = 266)

*IPEDS definitions exclude transfer and part-time students and values likely do not accurately reflect all students.

**Median used account for extreme salaries

Totals may not sum to 100% due to rounding.

Data Sources: IPEDS 2014-15 data and U.S. Census (2008-12 American Community Survey)

[End Page 1385]

Only 73 percent of private institutions provided remedial services to students (compared to 89% of publics). Similarly, only 75 percent of private colleges offered distance education courses. On the whole, private broad access institutions were more likely to serve non-White students on their campuses (M = 37%) when compared to public institutions. However, tremendous variation was found, with some private institutions having a student body with no students of Color or as many as 100 percent of students who were non-White. Though on average, private BAIs enrolled more full-time students when compared to publics, large differences were shown in full-time versus part-time enrollment across institutions. On average, private institutions that offered broad access to students had 64 percent of their student body that received Pell grants (SD = 23). Like public BAIs, private universities showed large variance in terms of institutional outcomes. The mean retention rate at private institutions was 61 percent, although large variation was shown in retention (SD = 21). Private institutions graduated an average of 40 percent of students within six years, though institutions failed to graduate any students and others graduated all students (SD = 20).

In terms of resource and environmental diversity, private BAIs were found to be extremely heterogeneous. When compared to public institutions, private institutions were well resourced with mean tuition and fee revenue of more than $17,000 (SD = 8,105), spending on average 10 percent of the core expenses on academic services (SD = 8). Like public institutions, large variance was shown with regard to faculty salaries (M = 45,643), with some institutions having a mean salary of as little as $4,797, whereas other private universities had an average salary of nearly $100,000 dollars per year. When compared to public BAIs, private institutions were found to be even more heavily located in the city or suburbs (89%). Also like public institutions, private BAIs were shown to be diverse in terms of the county characteristics (i.e., unemployment, median salaries) surrounding institutions. Collectively, these descriptive findings highlight the variance within and between four-year institutions that offer broad access to students and provide evidence that BAIs may be separated into meaningful groups.

Typology of Broad Access Institutions

Findings show that public and private institutions that offer broad access to students can be separated into four clusters or institutional types. The following section describes the four- cluster solution (2 public and 2 private clusters) and highlights defining characteristics of each institutional type from the analysis. [End Page 1386]

Table 2. V 4- P B A I ( = 807) *IPEDS definitions exclude transfer and part-time students and values likely do not accurately reflect all students. **Median used account for extreme salaries Totals may not sum to 100% due to rounding. Data Sources: IPEDS 2014-15 data and U.S. Census (2008-12 American Community Survey)
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Table 2.

Variation among 4-year Private Broad Access Institutions (n = 807)

*IPEDS definitions exclude transfer and part-time students and values likely do not accurately reflect all students.

**Median used account for extreme salaries

Totals may not sum to 100% due to rounding.

Data Sources: IPEDS 2014-15 data and U.S. Census (2008-12 American Community Survey)

[End Page 1387]

Table 3. P D C BAI *IPEDS definitions exclude transfer and part-time students and values likely do not accurately reflect all students. **Median used account for extreme salaries Totals may not sum to 100% due to rounding. Data Sources: IPEDS 2014-15 data and U.S. Census (2008–12 American Community Survey)
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Table 3.

Profile Description of Clusters for BAIs

*IPEDS definitions exclude transfer and part-time students and values likely do not accurately reflect all students.

**Median used account for extreme salaries

Totals may not sum to 100% due to rounding.

Data Sources: IPEDS 2014-15 data and U.S. Census (2008–12 American Community Survey)

[End Page 1389]

Cluster 1: Low-cost, open access public colleges

The first cluster included 120 colleges, representing just 11 percent of the BAIs and 45 percent of the public institutions. On the whole, institutions in this cluster were shown to have characteristics that are similar to community colleges and many of these institutions had historically been titled a "junior" or "community college." However, none of the colleges currently had "community college" in the title and all of them offered bachelor's degrees. Colleges in Cluster 1 were predominately open access institutions, with the majority of institutions (69%) primarily offering associate's degrees. Sixty six percent of institutions offered bachelor's degrees or post-bachelor's certificates as the highest degree, and only 34 percent of institutions in this cluster offered master's and/or doctoral degrees. It is notable that the institutions in Cluster 1 all offered remedial services. Institutions served a diverse student body, with an average of 31 percent of the student body identifying as non-White. Cluster 1 institutions served the highest proportion of part-time students (average of 75%). Institutions in this cluster were also the most affordable, offering the lowest tuition and fees on average of all the institutions. Cluster 1 institutions were geographically diverse, with the majority in cities and suburbs (57%), a fourth in towns, and the remaining 18 percent in rural areas. Institutions in this cluster had lower average second-year retention (61%) and six-year bachelor's degree graduation rates (27%) than the other cluster of public institutions (second lowest retention and graduation rates of all of the clusters). An example of a BAI that represents institutions in this cluster is Columbia Basin College in Washington.

Cluster 2: Striving regional and state universities

Cluster 2 included 146 institutions, representing 14 percent of the BAIs and 55 percent of the accessible public institutions. As a group, the institutions in this cluster were the least accessible of the clusters with only two percent having open admission policies. Institutions in Cluster 2 were also distinguished by the relatively high percentage of universities that offered masters and/or doctoral degrees and certificates (93%). Institutions in Cluster 2 were also on whole less racially diverse than the other clusters. An average of 39 percent of students received Pell grant aid. Students were also more likely in this cluster to attend full-time when compared to the other types of BAIs. The universities in this cluster had the highest retention and graduation rates of the clusters (average 74% retention rate and 48% graduation rate) and relatively large enrollments. Both the institutions and students in Cluster 2 were well resourced when compared to the colleges in Cluster 1. Cluster 2 also had the highest average faculty salaries of all of the clusters and tuition rates that were on average nearly double that of institutions in Cluster 1. Like Cluster 1, institutions were geographically diverse, with a disproportionate number located in towns (i.e., college towns) across the country. Cluster 2 institutions [End Page 1390] were also on average located in counties with lower median salaries when compared to the other clusters. A four-year broad access institution that represents this cluster is Youngstown State University in Ohio.

Cluster 3: Private accessible liberal arts and religious colleges

The third cluster of BAIs included 355 private institutions, representing 33 percent of the institutions and roughly half (44%) of the accessible privates. It is notable that all religious colleges are included in Cluster 3 (62% of institutions) and that 99 percent of the colleges are non-profit. On the whole, institutions in Cluster 3 had small undergraduate enrollments. Colleges in this cluster were a combination of open access and accessible colleges that predominately offered four-year degrees or higher (91%). Cluster 3 institutions offered a range of degrees and certificates, with 25 percent of institutions offering only bachelor's degrees and the majority offering master's and/or doctoral degrees as the highest degree. Institutions in Cluster 3 were shown to have the highest tuition and fees when compared to the other clusters (average over $20,000 per year). Institutions in Cluster 3 were least likely to offer remedial services or distance learning courses when compared to the other clusters. Relatedly, Cluster 3 colleges and universities had relatively high retention (70%) and graduation rates (46%). Similar to the first two clusters, the majority of institutions in Cluster 3 were located in cities and suburbs. Albertus Magnus College in New Haven, Connecticut is a representative four-year BAI in this cluster.

Cluster 4: Accessible minority-serving private colleges

The fourth and largest cluster included 452 BAIs, representing 42 percent of all accessible institutions and 56 percent of the private institutions. None of the private institutions are religiously affiliated. Cluster 4 institutions were more accessible than private institutions in Cluster 3, with 91 percent of institutions classified as open access institutions. The majority of institutions offered a combination of associate's and bachelor's degrees, with only 8 percent offering doctoral degrees. Institutions in Cluster 4 were distinguished by the diversity of the student body--on the whole serving the highest percentage of non-White students (45%). Also, Cluster 4 colleges included the smallest institutions when compared to the other clusters. Relative to the other private cluster, institutions in Cluster 4 were more affordable and served a high percentage of part-time students. Cluster 4 colleges also on average had the lowest faculty salaries when compared to the other clusters. Finally, institutions in Cluster 4 were distinguished by location, as 96 percent of colleges were located in cities (60%) or suburbs (36%). Relatedly, institutions in Cluster 4 were on average located in more affluent counties (i.e., higher median salaries) when compared to institutions in other clusters. An example of a BAI in this cluster is The Art Institute of Austin. [End Page 1391]

Discussion of Findings

Further study of four-year broad access institutions is important and timely given their influence on postsecondary educational opportunities as well as the continued importance of the bachelor's degree in both earnings premiums and other critical social and civic outcomes (Baum, Ma, & Payea, 2013). A more robust understanding of the diversity of four-year BAIs provided by the present study both aligns with and contributes to the growing literature focused on four-year BAIs. More specifically, our descriptive results add to current understanding regarding the heterogeneity of four-year BAIs by identifying sizable differences within public and private four- year institutions that offer admission to the majority of applicants. Additionally, our cluster analysis findings extend Carnegie's inclusiveness category by grouping public and private four- year BAIs into more meaningful and manageable categories (Prescott, 2011).

Descriptive findings highlight large variance within public four-year BAIs on numerous characteristics that warrant additional attention and consideration. Most notably, sizable differences in retention rates and graduation rates were found between four-year BAIs with some institutions reporting higher graduation rates than some more selective four-years (Crisp, Doran, & Salis Reyes, 2017), while other BAIs retained or graduated very few students. Additionally, descriptive findings highlight substantial variance with regard to resources within and between public and private four-year BAIs in terms of tuition and fee revenue and faculty salaries. Further, present findings add to the scarce information regarding the county characteristics surrounding four-year BAIs, demonstrating the diversity of environments within which BAIs are situated, with some four-year BAIs located in well-educated and affluent counties and others located in low-income areas with relatively little access to postsecondary education.

Cluster analysis findings suggest that the often-monolithic description of inclusive colleges is erroneous and potentially masks important within-group distinctions. Specifically, we find that four-year BAIs might be meaningfully separated into four types of institutions.

Although the cluster analysis findings likely present more questions than answers about four- year BAIs, several key observations/conclusions can be made from the empirical clustering. First and foremost, descriptive and cluster analysis findings suggest that not all accessible institutions are Minority Serving. At the same time, it is notable that low-cost, open access public colleges (Cluster 1) and accessible minority-serving private colleges (Cluster 4) were the most accessible and also served on average the highest proportion of non-White students. Results also indicate that there may be distinct types of four-year BAIs (i.e., striving regional and state universities and private accessible liberal arts and religious colleges) that serve less diverse student [End Page 1392] bodies that more closely resemble students attending selective universities (e.g., White, affluent, students attend full-time).

Second, we note that Striving regional and state universities may be a distinct form of BAI that includes accessible universities that are "striving" (O'Meara, 2007) to have institutional characteristics that closely resemble more selective institutions. Third, it is notable that a large number of BAIs are in fact private faith-based institutions. As expected, religiously oriented four-year BAIs clustered together in Cluster 3 although also with other colleges, suggesting that accessible religious institutions are both meaningfully distinct and yet similar to other four-year BAIs. Finally, cluster analysis findings more broadly add to our understanding regarding the diversity within and between other types of higher education institutions. For instance, results of the cluster analysis call into consideration whether more selective private institutions might also be more meaningfully distinguished by considering alternate or a broader set of institutional characteristics including student characteristics, religious affiliation and resources.

Study Implications

Classification structures, including Carnegie, continue to bear substantial influence on policy decisions and related resource allocations for institutions, including those that offer broad access to students. As accountability for student success becomes increasingly important as a substantive goal and a condition for funding, development of increasingly nuanced classification systems also becomes essential. Such efforts offer new insights to supplement our knowledge and understanding of the diversity of higher education institutions (Prescott, 2011) that may yield numerous potential benefits for research, policy and practice. Additionally, our work provides an emerging framework for policy discussions related to college access and success, comparisons of institutional effectiveness, and funding allocation.

Results also contribute evidence that the concept of "inclusivity" is important, complex, and must be considered through a multi-dimensional research and policy lens. Recognizing the ways in which this concept influences and bounds the decisions of campuses and their student and community outcomes is critical. Additionally, as scholars and policy makers alike continue to seek to understand the student outcomes associated with this important group of colleges and universities, findings identify that care needs to be taken to understand campus influence on those results in an increasingly nuanced way. Treating broad access institutions as monolithic in nature hampers capacity to effectively understand and support this critical group. Finally, study findings suggest that institutions whose mission is one of access might be well-served in understanding their peer institutions in refined ways in order to increase the success of programmatic and advocacy efforts. [End Page 1393]

Such efforts are critical, particularly given current federal interest in distinguishing colleges and universities around dimensions of access and success. Efforts to describe and distinguish four-year BAIs are important for institutional leaders as they provide opportunities to identify and benchmark their efforts with well-aligned peers. Said differently,

a 'one size fits all' policy strategy with regard to universities and colleges still seems to be highlighted in government policy statements across the developed (and indeed developing) world, which certainly does not readily align itself to this overall recognition of, and need for, diversity in higher education institutions and their responses.

Our findings also lay important groundwork for future empirical and theoretical studies in that results challenge the utility of commonly used classification strategies as reflective of meaningful distinctions among and between broad access institutions. In sum, this study lays the groundwork for longer-term efforts to create an enhanced classification scheme that may provide policy makers, institutional leaders, and researchers with a better understanding of the diversity of institutions. In particular, we suggest that present findings be used as a foundation for future empirical and theoretical work to look more closely at how the concept of access is operationalized and the ways those shifts might further usefully differentiate among institutions. Future studies might also seek to understand how patterns among broad access institutional characteristics have changed over time and the extent to which external factors such as policy, advocacy, and funding efforts have influenced that change. Moreover, research might study striving regional and state universities that move into or out of a broad access classification from or to a more elite institutional status over time, what prompts those moves, and what the implications are of such efforts for the students traditionally served. [End Page 1394]

Gloria Crisp

Gloria Crisp is a Professor of Adult and Higher Education at Oregon State University. Her scholarship is grounded by her personal and professional experiences at institutions that provide broad access to students. She has a diversity of professional experiences working with both community colleges and 4-year accessible institution as an institutional researcher and faculty member. Her work has been supported by The National Science Foundation, The Association for Institutional Research, and The Hispanic Association of Colleges and Universities.

Catherine L. Horn

Catherine Horn is a Professor of Educational Leadership and Policy Studies and Executive Director of the Institute for Educational Policy Research and Evaluation at the University of Houston. She is also the Director for the Center for Research and Advancement of Teacher Education and the University of Houston Education Research Center. Dr. Horn, who received her PhD from Boston College, focuses on the systemic influences of secondary and postsecondary assessment and related policies on the learning trajectories of students especially for students traditionally underserved by the education and social sectors.

Margaret Kuczynski

Margaret Kuczynski, Co-Director of the University of Houston College of Education Office of Institutional Effectiveness, has a master's degree in statistics and has been with the college for five years. Formerly she taught introductory statistics at the community college level and was employed as a statistical analyst at iDatassist.com. Margaret served as treasurer of the Houston chapter of the American Statistical Association and has done volunteer statistical work for the Houston Arboretum.

Qiong Zhou

Qiong (June) Zhou received her Ph.D. in Research, Measurement and Statistics in 2013 from Texas A&M University-College Station. She is the Coordinator of Office of Institutional Effectiveness in College of Education, University of Houston. She has over 10 years of academic and professional experience of managing and analyzing large-scale database in the field of higher education, K-12 education, special education, and public health education.

Elizabeth Cook

Elizabeth Bowers Cook is an independent scholar in southeast Asia, who centers her work in race & social justice advocacy through research with Black faculty recruitment and retention, equity for women in doctoral pipelines, and motherscholarship/academic motherhood. She earned her Doctorate from the University of Texas at San Antonio.

Appendix A

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Definitions of Measures and Variables

Data Sources: IPEDS 2014-15 data and U.S. Census (2008-12 American Community Survey)

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Footnotes

* A previous version of this paper was presented at the American Educational Research Association Conference

1. Basic, Undergraduate Program, Graduate Program, Undergraduate Profile, Enrollment Profile, Size and Setting, and Community Engagement

2. Note only 24.5 percent of the 106 U.S. Land Grant institutions were defined as broadly accessible. Seventy five percent of Land Grant institutions are not included in this study because they accepted less than 80 percent of applicants in the 2014–15 academic year.

Additional Information

ISSN
1090-7009
Print ISSN
0162-5748
Pages
1373-1400
Launched on MUSE
2019-07-12
Open Access
No
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