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A Multilevel Analysis of Community College Students' Transfer to Four-Year Institutions of Varying Selectivity


by Xueli Wang - 2016

Background/Context: Transfer from community colleges to selective four-year institutions is an issue that assumes great importance for the democratization of postsecondary education. Yet research on what influences transfer to selective four-year institutions is surprisingly sparse. Transfer research typically lumps four-year schools receiving community college transfers into one group. This approach neglects heterogeneity in institutional selectivity and fails to study forces underlying the varied pathways to four-year institutions.

Purpose: This research fills the gap in the literature by exploring the following question: What student and institutional factors are associated with transfer from community colleges to four-year institutions of varying selectivity? This study is aimed at identifying beneficial experiences to support community college students’ pathway to the baccalaureate, especially at selective institutions.

Research Design: This study drew upon several national data sources and a nationally representative sample of all first-time postsecondary students beginning at a public two-year college in 2003–2004. Based on the study’s conceptual framework that depicts the relationship between transfer and various individual and institutional factors, I analyzed the hypothesized relationships using a multilevel path model.

Findings: The study shows that few community college students transferred to highly selective institutions. In terms of individual factors that distinguish those who transfer to highly selective institutions from their counterparts who transfer to moderately or less selective schools, holding baccalaureate expectations and transfer intent seems to benefit those who transfer to selective institutions much more strongly than those who transfer to less selective ones. Similarly, rigorous course-taking distinguishes not only those who transfer from those who do not, but also those who transfer to highly selective institutions from their transfer counterparts headed toward moderately or less selective colleges. However, integrative experiences and first-term GPA show no significant relationship with upward transfer. As for institutional characteristics, percentage of certificates and vocational associate degrees awarded is negatively associated with transfer to highly and moderately selective institutions, while it does not particularly affect chances of transfer to less selective institutions. Furthermore, employment of part-time instructional faculty and staff does not benefit or hurt community college students’ chances of transfer, and, overall, proximity to selective institutions does not appear to be influential either.

Conclusions: This study’s findings reinforce persistent issues associated with access and transfer to selective institutions for community college students. Both education policy and research must continue to tackle challenges and create opportunities to help broaden community college student access to four-year institutions.



In recent years, public two-year institutions have gained increasing attention from policymakers for their pivotal status in the college completion agenda as a national priority (e.g., McPhail, 2011; The White House, 2011). Enrolling nearly 50% of the undergraduate population in the nation and a disproportionately large share of low-income, first-generation, and underrepresented racial minority students (Cohen, Brawer, & Kisker, 2014), community colleges play a unique and vital role in American postsecondary education. For many disadvantaged students attending community colleges, the transfer function serves as a gateway to a four-year degree. Nationally, approximately 24% of first-time students beginning at a community college transfer to four-year institutions within six years of initial postsecondary enrollment (National Center for Education Statistics, 2011).

While upward transfer has long been a core function of community colleges, and related research has been abundant, in recent years a more nuanced issue has emerged and gained increasing interest from policymakers, researchers, and practitioners concerned about community college student access to a baccalaureate education: transfer to selective four-year institutions. This topic holds great implications for the democratizing role played by community colleges, especially for their transfer-aspiring students, as attending more selective institutions is associated with better educational and career prospects (Carnevale & Rose, 2004; Dale & Krueger, 2011; Long, 2008; Thomas, 2003). Yet, for the greater part of higher education history, selectivity of the receiving institutions of community college transfer students has been an inconvenient topic largely neglected in both policy and research, especially considering the many structural, social, and academic struggles community college students traditionally face in pursuing the transfer route. However, as the higher education landscape enters the 21st century, and with the shifting socio-demographic profile of students beginning at community colleges (Kelsay & Zamani-Gallaher, 2014), this issue cannot be neglected any longer, as it assumes great importance and implications for access, equity, and democratization in postsecondary education.

To begin with, community colleges have received heightened attention from the federal government and numerous policy and education initiatives aimed at promoting the success of students served by these institutions (e.g., Achieving the Dream, n.d.; Complete College America, 2012; Completion by Design, n.d.; White House, 2011; U.S. Department of Education, 2015; U.S. Department of Labor, 2014). The influx of this support has sparked a renewed national dialogue surrounding the role and purpose of the American community college in the new century (Topper & Powers, 2013). In this discourse, community colleges are still lauded for broadening access to postsecondary education; however, there has been a marked shift in emphasis from broad access to equitable outcomes (Dowd, Pak, & Bensimon, 2013; Long & Kurlaender, 2009; Topper & Powers, 2013).

A step toward achieving equitable outcomes for students beginning at community colleges lies in the area of transfer access to selective four-year institutions. Historically overlooked in the transfer literature, selectivity of receiving institutions warrants particular empirical attention; research on upward transfer should not treat receiving institutions as a homogeneous group, since they offer distinct educational, social, and economic benefits based on their selectivity. As the selectivity of an institution increases, students’ likelihood of obtaining a degree may increase by 10% or more (Long, 2008). Students attending more selective institutions also have better chances of being accepted into advanced studies at the graduate or professional level (Carnevale & Rose, 2004) and enjoy higher post-graduation earnings (Dale & Krueger, 2011; Thomas, 2003). Overall, a fair amount of empirical evidence indicates that the benefits associated with attending more selective colleges extend beyond educational attainment and carry over into increased social status and mobility (Bastedo & Flaster, 2014). Of note, students from low-income families or members of racial/ethnic minorities benefit most from attending a selective four-year college (Dale & Krueger, 2002, 2011). Given these social and economic benefits of attending selective institutions, if community college students only transfer to institutions in the lowest stratum of selectivity, their upward mobility remains limited, and such disparate access to four-year institutions perpetuates educational and social inequity.

Corresponding with the emerging emphasis on equitable outcomes of community college students are the shifting socio-demographic profiles of students attending community colleges. In recent decades, increasing numbers of socially disadvantaged students have been more academically prepared than previous generations (Bastedo & Flaster, 2014), and some of them may begin at two-year institutions due to financial constraints (Adelman, 2006). In the meantime, with the rising costs associated with attending a four-year institution, many students from middle-class families have also shifted away from four-year institutions toward more affordable public two-year colleges for their initial postsecondary years (Sallie Mae, 2012; Snyder & Dillow, 2012). In fact, the enrollment of high-achieving, low-income students at community colleges has evolved to be one of the patterns of undermatching—meaning that these students do not apply to four-year colleges on par with their academic qualifications, but instead enroll at less selective institutions, including community colleges (Bowen, Chingos, & McPherson, 2009). There is evidence showing that many of these students could gain admission to highly selective four-year institutions if they were encouraged to apply (Hoxby & Avery, 2012; Radford, 2013). In addition, students who later transfer to selective institutions attain their baccalaureate degrees at similar rates to native students, and at higher rates than students beginning at less selective institutions (Bowen et al., 2009). Given the disparity in their resources, community colleges and highly selective institutions foster fundamentally different social outcomes for their graduates; therefore, broadening transfer access to selective institutions helps increase the social mobility of these students (Bastedo & Flaster, 2014).

A confluence of the increasing emphasis on equitable student outcomes by the nation’s community colleges and the changing body of community college students heightens the need to study and promote transfer access to selective institutions. Notwithstanding the importance of access to selective four-year institutions, community college student transfer to these institutions remains limited (Dowd, Cheslock, & Melguizo, 2008). This fact is disconcerting and warrants empirical work that examines what factors facilitate or hinder this process. As Handel (2014) forcefully and rightfully argued, the current effort to reduce inequitable access and outcomes of college students must include “those hardworking students who choose to attend a community college with the intention of transferring to one of America’s premier universities but in whose paths there are obstacles that we can and should remove” (p. 39).

Resonating with the ever-changing, ever-responsive nature of American community colleges, these emerging trends have already stimulated new inquiries about students’ transfer access to selective institutions, but most of this work is descriptive in nature (e.g., Dowd et al., 2008) or draws upon small-scale, qualitative designs that provide valuable insight but do not present nationally generalizable findings regarding factors associated with transfer to selective institutions (e.g., Dowd et al., 2013). Despite the numerous studies on transfer from community colleges to four-year institutions, research on what influences transfer to selective four-year institutions is surprisingly sparse. Transfer research lumps destination institutions (i.e., four-year schools receiving community college transfers) into one group and treats transfer as a binary outcome: whether students transfer to a four-year college or not. This approach neglects heterogeneity in institutional selectivity and fails to study forces underlying the varied pathways to four-year institutions. Also, prior studies either singularly focus on student attributes and experiences or emphasize institutional characteristics, without considering how these factors intertwine to influence transfer. Given these limitations, knowledge is scant about what student experiences and institutional characteristics influence transfer to selective institutions and how students’ experiences affecting transfer are shaped by institutional characteristics across community colleges.

In this study, I aim to fill these gaps in the literature by asking the following overarching question: What student and institutional factors are associated with transfer from community colleges to four-year institutions of varying selectivity? My study distinguishes destination institutions based on selectivity in order to uncover factors that may be uniquely associated with transfer to selective institutions. Taking into account the complexity of student transfer, this study informs institutions of policies and practices that develop beneficial experiences to support socially disadvantaged community college students’ pathway to the baccalaureate, especially at selective institutions.

PRIOR LITERATURE AND CONCEPTUAL FRAMEWORK

This research builds upon and extends existing research on upward transfer by addressing substantive and methodological limitations in previous studies and bringing together relevant conceptual lenses to account for the issue’s complexities. In this section, I discuss the empirical context in which this study is situated as well as the theoretical perspectives that inform the conceptualization of my study.

COMMUNITY COLLEGES: GATEWAY TO THE BACCALAUREATE

Scholars across disciplines have studied upward transfer, one of the key functions of community colleges. Two approaches to conceptualizing the problem have dominated research in this area. The first approach takes an evaluative stance on the effect of beginning at a community college, as opposed to beginning at a four-year institution, on subsequent baccalaureate completion. The second approach focuses on variations within the community college student population in seeking to understand what contributes to student transfer to four-year institutions.

Research concerning the effect of community college attendance on baccalaureate attainment is often discussed in conjunction with the democratization/diversion debate in which scholars contend with the “contradictory” roles community colleges play (Dougherty, 1994). On the one hand, given their physical proximity, the local presence of community colleges may provide affordable and open access to socioeconomically disadvantaged students who otherwise would not have pursued postsecondary education (Cohen et al., 2014), thus characterizing these colleges as democratizing institutions (Rouse, 1995). On the other hand, community colleges may channel students away from four-year institutions, changing their educational aspirations and plans, thus “diverting” students who would have attended college through any potential means away from pursuing a four-year education (Brint & Karabel, 1989). Essentially, community colleges may negate students’ educational aspirations, thus preventing them from transferring and attaining a bachelor’s degree.

Situated within the democratization/diversion discourse, a common empirical approach to testing the larger democratization or diversion effect rests with specifically focusing on the impact of community college attendance on baccalaureate attainment (e.g., Alba & Lavin, 1981; Alfonso, 2006; Brint & Karabel, 1989; Dougherty, 1987, 1994; Grubb, 1989, 1991; Leigh & Gill, 2003; Long & Kurlaender, 2009; Reynolds & DesJardins, 2009; Rouse, 1998; Stephan, Rosenbaum, & Person, 2009; Velez, 1985). Despite varying research designs, these studies largely point to the negative effect of beginning at community colleges on subsequent baccalaureate attainment, mainly because many baccalaureate-aspiring students fail to transfer (Pascarella & Terenzini, 2005). This disadvantage is troublesome, especially in light of recent compelling evidence indicating that once students do successfully transfer to a four-year institution, their success rates are comparable to those who start there as freshmen (Melguizo, 2009; Melguizo & Dowd, 2009; Melguizo, Kienzl, & Alfonso, 2011). This makes the study of transfer per se as a distinct outcome a perennially relevant and pressing topic, as it seems that, once students successfully transition from community colleges to four-year institutions, they enjoy equal chances of success.

Therefore, research is needed to explain the specific mechanisms that promote or hinder upward transfer. This focus underpins the second approach that looks within the community college to understand what factors influence student transfer. Research in this vein has addressed either institutional attributes or student characteristics.1 These studies uncovered a variety of influential factors, including institutional effects unique to community colleges, such as the vocational focus (e.g., Brint & Karabel, 1989; Dougherty, 1987, 1994; Roksa, 2006) and the employment of part-time faculty (e.g., Eagan & Jaeger, 2009). Student characteristics also come into play (e.g., Bailey, Jenkins, & Leinbach, 2005; Crisp & Núñez, 2014; Lee & Frank, 1990; Velez & Javalgi, 1987), given that the typical community college student possesses risk factors, such as poor academic preparation and part-time attendance, that decrease the likelihood of college success (Dougherty, 1992; Dougherty & Kienzl, 2006; Roksa & Calcagno, 2010). Moreover, students’ motivational attributes, including those related to personal goals (Laanan, 2003) and educational expectations (Wang, 2013), are of important value. In particular, after controlling for the noted risk factors, community college students’ motivational beliefs have been shown to positively impact later educational expectations (Wang, 2013) and increase transfer probabilities (Wang, 2012).

Both approaches inform this inquiry, but my study extends beyond the current literature by addressing important limitations of extant research. Revolving solely around the question of whether or not community colleges hinder baccalaureate attainment barely answers the questions of where potential points of intervention are and how improvements may be made. It is crucial to identify factors that facilitate or impede community college students’ upward transfer. While the second approach intends to serve this purpose, prior studies have singularly categorized all destination institutions, providing little insight into what factors underlie transfer access to institutions of varying selectivity. Also, the included variables are often limited to student “inputs” that scarcely address student experiences through college, let alone how these processes are structured by institutional characteristics and how they link student attributes to upward transfer.

TRANSFER ACCESS TO SELECTIVE INSTITUTIONS

Despite the large body of empirical work on upward transfer, little research has identified factors that influence transfer to selective institutions. Available work on the topic based on large-scale datasets is mainly descriptive and points to the limited access to selective institutions among community college students (e.g., Dowd et al., 2008; Dowd & Melguizo, 2008). Cheslock (2005) and Dowd et al. (2008) explored determinants of transfer enrollment at selective institutions, yet they focused on the relationship between selective four-year institutions’ characteristics and their overall enrollment of community college transfers—an important but different question from what my study tackles. Dowd et al. (2008) did include some student characteristics, such as socioeconomic status and academic preparation, but this only touches upon a few of the many potentially influential factors at the individual level. Other research has drawn upon case studies and single-institution data (e.g., Dowd et al., 2013; Gabbard et al., 2006; Laanan, 1996; Morphew, Twombly, & Wolf-Wendel, 2001; Townsend & Wilson, 2006). These analyses valuably examined practices or programs related to transfer to selective institutions but concentrated on students who had completed the transfer process, with little or no emphasis on the attributes of community colleges and student experiences prior to transfer.

The current study advances scholarship on community college transfer in several ways. First, this research places an intentional focus on upward transfer as a multi-categorical outcome, accounting for the selectivity of the receiving institutions, and thus investigates factors distinctively associated with varied transfer outcomes. Second, prior research adopts either a student-focused approach or an institution-focused one, but this study integrates both and considers student motivation and college experiences, thus accounting for the complexities within the transfer path. These distinct approaches can illuminate specific points of intervention for promoting access to selective institutions among underprivileged community college students.

CONCEPTUAL FRAMEWORK

The conceptual framework informing this study depicts the complex nature of upward transfer and articulates various dimensions that could shape the process. At the individual level, a psychological perspective is important to this study, as it takes resilience and motivation for community college students to navigate the often complex postsecondary pathways they follow (Wang, 2009, 2012). Motivational beliefs surrounding upward mobility have been shown to predict community college students’ baccalaureate expectations and intent, as well as how they engage with college (Wang, 2013). Therefore, it is plausible that students aspiring to upward mobility have a tendency to engage in college experiences that are conducive to future outcomes and to develop baccalaureate expectations and transfer intent, both of which are also essential motivational factors that help overcome barriers to upward transfer (Wang, 2012, 2013).

Also worth exploring is the role of students’ community college experiences, including integrative experiences as well as course-taking and academic performance. Recent research (e.g., Deil-Amen, 2011; Karp, Hughes, & O’Gara, 2010) has revealed the importance of socio-academically integrative experiences in community college student success. It should be noted that, unlike their four-year college counterparts, community college students encounter these “integrative moments” primarily within the classroom setting (Deil-Amen, 2011). This brings to light a dimension of the community college experience potentially even more central to the study’s focus: students’ course-taking and academic performance. Because students attending two-year institutions are mostly commuters and engage with college primarily through taking courses (Hagedorn & Kress, 2008), the nature, intensity, and rigor of their coursework are a key reflection of their college experience. As Hagedorn, Cypers, and Lester (2008) suggested, completing rigorous, particularly transfer-oriented coursework is the best way to prepare for transfer.

Apart from individual-level factors, there has also been increasing scholarly interest in how institutions’ context influences student outcomes (e.g., Titus, 2004). Recently, a small number of studies have shed light on the impact of community college attributes on student attainment and transfer (e.g., Bailey, Calcagno, Jenkins, Leinbach, & Kienzl, 2006; Calcagno, Bailey, Jenkins, Kienzl, & Leinbach, 2008; Crisp & Núñez, 2014). Building upon these studies, it is reasonable to argue that select community college characteristics, such as employment of part-time instructional faculty and staff (Calcagno et al., 2008; Eagan & Jaeger, 2009) and vocational focus (Arbona & Nora, 2007; Roksa, 2006), may influence student outcomes, particularly transfer. In addition, the study accounts for community colleges’ proximity to four-year institutions of varying selectivity as an institutional contextual factor. Furthermore, these community college factors may affect how integrative experiences are structured within specific institutional environments. Accordingly, this research connects integrative experiences with community college characteristics, offering a more contextualized picture of upward transfer.

Finally, a number of environmental factors speak to the external demands placed on community college students that may influence their upward transfer and should be accounted for when examining transfer to four-year institutions of varying selectivity (e.g., Anderson, Sun, & Alfonso, 2006; Crisp & Núñez, 2014; Dougherty & Kienzl, 2006; Nora, 2004; Wang, 2009, 2012). In particular, work commitment, enrollment intensity, and financial-aid receipt have demonstrated consistent influences on transfer outcomes and are thus included in the study’s conceptual framework. In addition to these environmental factors, student socio-demographic background characteristics such as gender, race, first-generation status, and family income should be taken into consideration. A graphic representation of this conceptual model is provided in Figure 1.

Figure 1. Conceptual model of the study
[39_21643.htm_g/00002.jpg]
RESEARCH DESIGN

DATA AND SAMPLE

This study drew upon several national data sources. To begin with, student-level data came from the 2004/09 Beginning Postsecondary Students Longitudinal Study (BPS:04/09) sponsored by the National Center for Education Statistics (NCES). BPS:04/09 followed a nationally representative sample of students who began postsecondary education for the first time in 2003–2004. Respondents were interviewed during their first, third, and sixth year of college. Data were collected on students’ background characteristics, motivational beliefs, and college experiences and outcomes. Also, for the first time ever in the BPS series of studies, the Postsecondary Education Transcript Study (PETS:09) was conducted. Transcript data were collected from all postsecondary institutions attended by the respondents over a six-year period, providing reliable information on students’ course-taking patterns, persistence, transfer, and degree attainment. Together, BPS:04/09 and PETS:09 provided all student-level variables used in this study.

Also critical to this study were institution-level characteristics. I used data from NCES-Barron’s Admissions Competitiveness Index to identify the selectivity of the destination four-year institutions attended by community college transfers. I also employed data from the Integrated Postsecondary Education Data System (IPEDS) to identify institutional characteristics of the community colleges attended as the first postsecondary institutions by the study’s sample. The institutions’ IPEDS UnitIDs, which are uniquely assigned to each institution by NCES, are included in all data files, thus making it possible to merge relevant data from these four sources into one analytic file for the study.
I restricted the study’s sample to students who began at public two-year colleges in 2003–2004 with valid (non-blank) first institution IPEDS UnitID and corresponding first institutions’ term enrollment records in the PETS:09 transcript data files. After applying these restrictions, the analytical sample contained slightly over 5,000 BPS respondents beginning at 385 community colleges. After appropriate weighting (using BPS panel weight WTD000), the sample was representative of all first-time postsecondary students beginning at public two-year colleges in 2003–2004, or a weighted 38.9% of all beginning postsecondary students.

MEASURES

The dependent measure of the study was a multinomial variable indicating whether, as of 2009, students (a) had transferred to a highly selective four-year institution, (b) had transferred to a moderately selective four-year institution, (c) had transferred to a less selective four-year institution, or (d) had not transferred to a four-year institution. According to the definitions provided by BPS and PETS, an institutional transfer occurred when a student left the originating institution and enrolled at the destination institution for four or more months. Based on NCES-Barron’s Index, receiving institutions were grouped into three categories: Institutions ranked as “most” or “highly” competitive in the NCES-Barron’s Index were coded “highly selective,” those ranked “very competitive” or “competitive” were coded “moderately selective,” and those ranked otherwise were coded “less selective.” In the scenario where a student transferred to multiple four-year institutions at different times, the very first four-year institution to which the student transferred from the community college was selected and its NCES-Barron’s Index was used. Students who did not have any transcript record indicating transfer to a four-year institution or who only had incidental (less than four months’) transfer records were assigned the “no transfer” outcome category.

Guided by the conceptual model displayed in Figure 1, I included a set of student- and institution-level variables that may explain upward transfer. Individual-level variables included the following groups: First, community college students’ motivation and intent, indicated by perceived importance of upward mobility, baccalaureate expectations, and transfer intent.2 Second, college integrative experiences are measured on a scale constructed by NCES staff based on the frequency with which students talked to faculty about social and academic matters, participated in study groups, and met with academic advisors. Third, course-taking variables include percentage of earned credits out of total attempted credits during the first term, ratio of remedial courses to all courses during the first term, and variables representing rigor of course-taking in students’ academic history as indicated in transcripts, such as total credits received for Advanced Placement (AP),3 credits earned from advanced math/calculus during the first year of college, and credits earned from writing beyond English composition during the first year of college. In addition, first-term grade point average (GPA) was included to indicate academic performance. Fourth, environmental factors were represented by first-year enrollment intensity, work hours per week, whether students worked off-campus, and amount of financial aid received in the form of work-study, grants, and loans. Finally, student background characteristics include gender, race, age, first-generation status, and family income.

With regard to community college characteristics, I constructed the following variables using IPEDS data: (a) percentage of part-time instructional faculty and staff; (b) vocational focus, measured by percentage of certificates out of the total number of certificates and associate’s degrees awarded, and percentage of vocational associate’s degrees out of the total number of associate’s degrees awarded;4 and (c) proximity to four-year institutions, measured by three dummy indicators each representing the existence of four-year institutions in the three selectivity categories in the same county where the attended community college is located. A detailed description of these variables is provided in Table 1.

Table 1. List of Variables Used in the Study

Variable name

Description

 

Data source

Key dependent variable

 

Upward transfer outcome

Categories of dependent variable:

a) Transferred to a highly selective institution

b) Transferred to a moderately selective institution

c) Transferred to a less selective institution

d) Did not transfer

Derived from BPS:04/09 & PETS:09

Selectivity coded using NCES-Barron’s Admissions Competitiveness Index

Student-level variables

 

Motivation and intent

  

Motivation for upward mobility

Measuring whether the listed item was an important personal goal for the respondent (1 = yes, 0 = no)

Importance 2004: Being community leader

BPS:04/09

Importance 2004: Being financially well off

BPS:04/09

Importance 2004: Influence political structure

BPS:04/09

Baccalaureate expectations

Whether student expected to earn at least a bachelor's degree (1 = yes, 0 = no)

 

BPS:04/09

Transfer intent: Enrolled in transfer program

Whether student was enrolled in a four-year transfer program at a community college (1 = yes, 0 = no)

 

BPS:04/09

Integrative experiences

A scale ranging from 0 to 8, recalculated from the original index (0 to 200 in step size of 25), to make the variable more aligned with the scales of other variables

 

BPS:04/09

Course-taking and academic performance

Ratio of earned to attempted credits

Ratio of credits earned to credits attempted

PETS:09

Remediation

Ratio of remedial courses to all courses

PETS:09

AP credits

Total credits received for Advanced Placement

PETS:09

Advanced English credits earned

Writing beyond English composition

PETS:09

Advanced math/calculus credits earned

Advanced math/calculus

PETS:09

Academic performance

Transcript GPA in first term of attendance

PETS:09

Environmental factors

  

Enrollment intensity

Attendance intensity pattern in 2003–04
(1 = always full-time, 0 = otherwise)

BPS:04/09

Hours worked per week

Job while enrolled 2004: Hours worked per week (excluding work study)

BPS:04/09

Worked off campus

Whether student worked primarily off campus (1 = work off-campus, 0 = otherwise)

BPS:04/09

Total work-study

Total work-study 2003–04 (in $1000)

BPS:04/09

Total grants

Total grants 2003–04 (in $1000)

BPS:04/09

Total loans

Total loans 2003–04 (in $1000)

BPS:04/09

Student background

Respondent’s age

Age at first year enrolled at community college

BPS:04/09

Respondent’s gender

Respondent’s gender (1 = female, 0 = male)

BPS:04/09

First-generation college student

Whether respondent is a first-generation student, recoded from parents’ highest level of education (1 = yes, 0 = no)

BPS:04/09

Whether student is a member of underrepresented racial minority (URM) group

Underrepresented minority includes African American, Hispanic or Latino, American Indian or Alaska Native, Native Hawaiian/other Pacific Islander, and those who reported “other” or “more than one race.” (1 = yes, 0 = no)

BPS:04/09

Family income

Income group in 2003–04 (1 = low, 2 = low middle, 3 = high middle, 4 = high). Recode into a series of 3 indicator variables with lowest income quartile as the omitted reference category.

BPS:04/09

Institution-level independent variables

 

Employment of part-time instructors

Percentage of part-time instructional faculty and staff

IPEDS

Vocational focus

Percentage of certificates out of the total number of certificates and associate’s degrees awarded by institution

Percentage of vocational associate’s degrees out of the total number of associate’s degrees awarded by institution

IPEDS

Proximity to institutions of different selectivity

Proximity to four-year institutions of different selectivity, measured by (for each level of selectivity) whether there are highly, moderately, or less selective four-year institutions in the county where the community college is located (1 = yes, 0 = no). The selectivity of a four-year institution is based on NCES-Barron’s Admissions Competitiveness Index. The county where each institution is located is retrieved from IPEDS institution characteristics.

Three indicator variables (1 = yes, 0 = no):

Proximity to highly selective institutions

Proximity to moderately selective institutions

Proximity to less selective institutions

IPEDS


DATA ANALYSIS

After merging, cleaning, and recoding data from the four sources previously outlined, I analyzed the hypothesized relationships between upward transfer and student and institutional variables using a multilevel path model. Due to the use of hierarchically structured data with students nested within community colleges, along with the specifications of students’ experiences at community colleges mediating the potential influence of students’ motivation on upward transfer, the multilevel path modeling strategy is the appropriate methodological approach to answering my research questions, as it can capture the structural complexity within and between institutions (Kaplan, 2009). Since only the first postsecondary institution of each student was identified and used in the second-level of the data hierarchy, the nested data structure was clear and without overlapping.5

Model specification

This analysis was a two-level path model with a multi-categorical outcome variable (transferred to highly selective institutions, transferred to moderately selective institutions, transferred to less selective institutions, or did not transfer). Based on the theoretical model delineated earlier, at the individual level, upward transfer outcomes were hypothesized to be directly related to baccalaureate expectations, transfer intent (demonstrated by enrollment in transfer-oriented programs), integrative experiences, course-taking and academic performance, as well as environmental factors and students’ demographic background. Among these, baccalaureate expectations, transfer intent, and integrative experiences were also assumed to mediate the relationship between students’ motivation for upward mobility and their transfer outcomes. At the institutional level, I specified that selected community college characteristics (percentage of part-time instructional faculty and staff, vocational focus, and proximity to four-year institutions of varying selectivity) exert contextual influences on students’ upward transfer and their integrative experiences at community colleges. Therefore, in the within-college model, the intercepts of upward transfer and integrative experiences were modeled as random effects that were allowed to vary across community colleges and depicted as solid dark circles in Figure 2. In the between-college model, these random intercepts were further regressed on the institution-level exogenous variables.

The following expresses this two-level path model in simplified regression equations. To illustrate: In the within-college model, for individual student i nested in community college j, the log odds of the student’s transfer to a highly selective four-year institution [39_21643.htm_g/00004.jpg] relative to no transfer [39_21643.htm_g/00006.jpg] can be expressed by the following function:


[39_21643.htm_g/00008.jpg]

where [39_21643.htm_g/00010.jpg] is the aforementioned random intercept of Upward Transfer being regressed on Integrative Experiences and other student-level variables regarding one of the transfer outcomes (here, transferred to highly selective institutions) versus the reference category (did not transfer). [39_21643.htm_g/00012.jpg][39_21643.htm_g/00014.jpg] to [39_21643.htm_g/00016.jpg] are row vectors of coefficients of academic, environmental, and demographic variables respectively, which are denoted as column vectors in square brackets in equation [1]. Then, [39_21643.htm_g/00018.jpg] in equation [2] is the derived random intercept of Integrative Experiences when regressed on a set of student motivation variables. Here, Integrative Experiences is one of the mediating variables that convey the effects of student motivation variables to Upward Transfer in the model. The other mediating variables, Baccalaureate Expectations and Transfer Intent are specified to be associated with student motivation variables without random effect in equations [3] and [4], where [39_21643.htm_g/00020.jpg] and [39_21643.htm_g/00022.jpg] are the threshold of Baccalaureate Expectations and Transfer Intent (both binary variables) and [39_21643.htm_g/00024.jpg] and [39_21643.htm_g/00026.jpg] are row vectors of coefficients of the column vector of student motivation variables, respectively.

Next, in the between-college model, the above derived random intercepts of log odds of upward transfer and random intercepts of integrative experiences for institution j were regressed on the institution-level variables. For community college j, the second-level model can be expressed as follows:


[39_21643.htm_g/00028.jpg]


Where [39_21643.htm_g/00030.jpg] and [39_21643.htm_g/00032.jpg] are the second-level intercepts (i.e., constant terms) and [39_21643.htm_g/00034.jpg] and [39_21643.htm_g/00036.jpg] are row vectors of coefficients of the column vector of institution-level variables in equations [5] and [6]. The other sets of regression equations regarding the other two transfer outcomes (i.e., transferred to moderately selective and less selective four-year institutions) versus the reference category (i.e., did not transfer) were set up similarly.


All continuous and ordinal variables in the within-college model were centered at the grand mean and the dummy variables were not centered. Thus, the intercept of Upward Transfer in the within-college model, [39_21643.htm_g/00038.jpg], can be interpreted as the adjusted mean of log odds, [39_21643.htm_g/00040.jpg], of upward transfer for an “average performing” non-first-generation, white male student from a low-income family in community college j (i.e., when all student-level continuous variables were held at their grand mean values and all dummy variables were held at the value of 0). Hence, in equation [1], holding other variables constant, when a continuous variable deviates one unit from its grand mean (or when a dummy variable changes from 0 to 1), the corresponding coefficient of the variable indicates the increase or decrease in the institution’s mean log odds, [39_21643.htm_g/00042.jpg], from the grand mean log odds, [39_21643.htm_g/00044.jpg], of the corresponding upward transfer outcome versus no transfer.

In the between-college model, the constant terms (second-level model intercepts) represent the average effect of institutions on the corresponding level-one variable (i.e., the log odds of upward transfer or integrative experiences) while holding all institution-level variables at zero. Then, after entering each institution’s specific set of values/characteristics, the between-college regression result shows the estimated deviation of each college from the overall average. That is, the between-college variation emerges as college characteristics vary.

Missing-data handling

The missing values in both student- and institution-level data were separately imputed through the multiple imputation technique (Schafer & Graham, 2002). Using Stata, five imputed datasets were generated and then fed into Mplus 7.11, statistical software that can be used to perform multilevel path analysis and appropriately adjusts for complex survey features such as clustering and sampling weights in the BPS and PETS data.

LIMITATIONS AND CAVEATS

Given the scope of the study and the secondary data analysis involved, a few caveats and limitations must be taken into consideration when interpreting the findings. First, transfer is a complex process that involves actions of individual students and institutional dynamics surrounding transfer at both the sending and receiving colleges. While, to the extent possible, this study accounted for the complexities from the angles of individual students and community colleges, it did not explore the receiving end, e.g., four-year institutions’ receptivity of community college transfer students.

Relatedly, this study was not able to capture the intricacies of community college students’ decision-making process as they explore transfer options. For example, students’ transfer application behaviors, perceptions of selective four-year institutions’ receptivity of community college transfers, proximity of more selective institutions to students’ home, and impact of students’ experiences at the community college on their future educational aspirations to attend a selective four-year school could all be complex factors influencing transfer outcomes. These are highly intertwined and fluid dynamics that cannot be tackled within the study’s scope and should be explored through future research.

Equally important to note as a caveat is that the multilevel path model approach I adopted for this study does not establish causal relationships. While the findings should not be interpreted as causal, this methodological approach is indeed appropriate given the study’s focus on identifying the relationship between a number of individual and institutional level variables (instead of a single “treatment” variable) and transfer outcomes. As discussed earlier, the issue of transfer to selective institutions has already started to gain traction, and this line of inquiry is likely to grow. However, existing research is limited in scope and descriptive in nature, and there exist no published studies that rely on inferential statistics using nationally generalizable data to reveal the complex relationship between upward transfer and student and institutional factors as specified in the study. What is missing, then, is a national picture of how a holistic set of factors contribute to or hinder transfer to institutions of varying selectivity. Once there is a clear picture of these relationships, more targeted research can start delving into the potentially malleable factors to promote true interventions.

Finally, due to the small number of minority students transferring to four-year institutions, underrepresented minority students were combined into one group in the analysis. It would be ideal to disaggregate these groups with larger subsample sizes distributed across the outcome categories. Unfortunately, this is not the case in the BPS data.

SUMMARY OF THE RESULTS

Of the study sample members, 42% were male, 58% were female, 34% were members of underrepresented minority groups, and 47% were first-generation college students. For a more detailed description of the sample’s distribution across different transfer outcome categories, see Table 2. To highlight a few notable findings, 1.9% of the sample transferred to a highly selective four-year institution, 14.6% transferred to a moderately selective four-year institution, 7.7% transferred to a less selective four-year institution, and the remaining 75.9% did not transfer to any four-year institution.


Table 2. Descriptive Summary of the Sample




Transfer to

Transfer to

Transfer to

No transfer

Total

highly selective

moderately selective

less selective

 

N

WgtN

W%

N

WgtN

W%

N

WgtN

W%

N

WgtN

W%

N

WgtN

W%

Total

80

27,287

1.9%

850

211,892

14.6%

430

111,890

7.7%

3690

1,103,528

75.9%

5,060

1,454,597

100%

Baccalaureate expectations

            

Yes

80

26,946

2.3%

820

202,428

17.2%

380

99,712

8.5%

2800

850,095

72.1%

4080

1,179,181

100%

No

0

34

0.1%

30

9,464

3.4%

50

12,179

4.4%

890

253,433

92.0%

980

275,416

100%

Transfer intent

            

Yes

60

22,772

3.3%

570

155,232

22.4%

240

66,917

9.7%

1,510

448,025

64.7%

2,370

692,945

100.0%

No

30

4,516

0.6%

280

56,660

7.4%

190

44,973

5.9%

2,190

655,503

86.1%

2,680

761,652

100.0%

Gender

               

Male

40

15,156

2.4%

360

89,786

14.3%

170

47,773

7.6%

1550

473,530

75.6%

2,130

626,245

100%

Female

40

12,131

1.5%

490

122,106

14.7%

260

64,117

7.7%

2140

629,998

76.1%

2,930

828,352

100%

First generation

              

Yes

30

10,956

1.5%

270

64,320

9.1%

170

43,571

6.1%

1920

589,817

83.2%

2,390

708,664

100%

No

50

16,331

2.2%

590

147,572

19.8%

260

68,319

9.2%

1770

513,711

68.9%

2,670

745,933

100%

Race

               

White

50

13,423

1.6%

590

143,557

16.6%

230

62,016

7.2%

2250

644,936

74.7%

3,120

863,932

100%

Black

10

1,510

0.7%

100

21,808

10.1%

80

21,444

10.0%

630

170,305

79.2%

820

215,066

100%

Hispanic

10

1,980

0.9%

80

23,439

10.1%

70

18,314

7.9%

500

187,461

81.1%

650

231,193

100%

Asian

20

7,951

11.7%

40

11,746

17.3%

20

5,256

7.8%

120

42,786

63.2%

200

67,738

100%

Other

10

2,424

3.2%

50

11,342

14.8%

20

4,861

6.3%

200

58,040

75.7%

270

76,668

100%

Underrepresented minority

            

Yes

20

5,914

1.1%

220

56,589

10.8%

170

44,619

8.5%

1330

415,806

79.5%

1,740

522,928

100%

No

60

21,374

2.3%

640

155,303

16.7%

260

67,272

7.2%

2370

687,722

73.8%

3,320

931,669

100%

Family income group

             

Lowest Quartile

20

7,296

1.9%

220

50,253

13.3%

130

29,679

7.9%

1120

289,443

76.8%

1,490

376,672

100%

2nd Quartile

20

8,020

2.2%

240

58,944

15.9%

110

28,338

7.6%

1000

275,842

74.3%

1,370

371,145

100%

3rd Quartile

20

6,096

1.6%

220

58,339

15.6%

110

29,518

7.9%

880

279,287

74.8%

1,220

373,240

100%

Highest Quartile

20

5,875

1.8%

180

44,355

13.3%

80

24,356

7.3%

690

258,956

77.6%

980

333,541

100%

 

Average

 

Average

 

Average

 

Average

 

Total

 

1st-term GPA

3.27

  

3.03

  

2.89

  

2.68

  

2.77

 

AP credits

1.41

  

0.15

  

0.15

  

0.03

  

0.08

 

Adv. English cr.

0.62

  

0.54

  

0.35

  

0.25

  

0.32

 

Adv. math cr.

1.22

  

0.48

  

0.18

  

0.06

  

0.16

 

% Credit earned

95.6%

  

88.0%

  

81.0%

  

70.0%

  

74.3%

 

% Remedial Courses

2.0%

  

2.6%

  

4.0%

  

7.0%

 

 

5.9%

 

Note. N = Analytical count rounded to the nearest tens as required by IES; therefore, the sum of subgroups within certain categories (such as race and transfer intent) may not add up to the total. WgtN = weighted count. W% = weighted percentage by using sampling weight.



Table 3 presents findings from the multilevel path analysis. The upper section of Table 3 reports the path coefficients of the within-college model, and the lower section of the table displays the estimates from the between-college model. Estimates of students’ likelihood of transferring to four-year institutions of varying selectivity versus no transfer are reported side by side. In order to provide the effect sizes of the estimated relationships, in addition to the path coefficients, relative risk ratios (RRR) are also reported. Obtained by taking the exponential of the multinomial logit coefficients, RRRs provide an alternative method of describing the relationship between a particular predictor and the dependent variable in terms of odds. An RRR of one implies that the predictor has no effect on the risk of the outcome occurring. RRRs greater than one indicate that the likelihood of the outcome occurring tends to increase as the predictor increases by one unit. Conversely, when RRRs are less than one, they indicate that the odds of the outcome occurring tend to decrease as the predictor increases by one unit.

Findings pertaining to the three mediating variables—baccalaureate expectations, transfer intent, and integrative experiences—are reported in Rows 24 through 33 of Table 3.

Table 3. Multilevel Path Model Results

Transfer outcome

Highly selective vs.
Did not transfer

Moderately selective vs.
Did not transfer

Less selective vs.
Did not transfer

#

b

se

RRR

b

se

RRR

b

se

RRR

 

Within-institution

         
 

Upward transfer ON

         

1

Intercept β0 (random)

         

2

Baccalaureate expectations

2.426**

0.836

11.314

1.451***

0.245

4.267

0.358

0.225

1.430

3

Transfer intent

1.246***

0.388

3.476

0.825***

0.119

2.282

0.577***

0.155

1.781

4

Integrative experiences

0.012

0.091

1.012

0.049

0.036

1.050

0.021

0.034

1.021

5

Ratio of earned to attempted

0.090***

0.015

1.094

0.035***

0.006

1.036

0.020***

0.003

1.020

6

Remediation

−0.101*

0.042

0.904

−0.107***

0.018

0.899

 −0.045***

0.013

0.956

7

AP credits

0.235***

0.056

1.265

0.096†

0.056

1.101

0.122*

0.055

1.130

8

Adv. English credits earned

−0.043

0.115

0.958

0.003

0.059

1.003

 −0.108

0.075

0.898

9

Adv. math/calculus credits

0.150†

0.082

1.162

0.075

0.060

1.078

0.066

0.070

1.068

10

Academic performance

0.310

0.277

1.363

0.141

0.092

1.151

0.103

0.085

1.108

11

Full-time

−0.583†

0.323

0.558

0.312†

0.166

1.366

0.373*

0.155

1.452

12

Hours worked per week

−0.027†

0.015

0.973

−0.012

0.009

0.988

0.000

0.006

1.000

13

Work off campus

0.345

0.526

1.412

0.134

0.223

1.143

 −0.039

0.228

0.962

14

Total work study

−0.383

0.592

0.682

0.032

0.100

1.033

0.110

0.115

1.116

15

Total grants

0.137*

0.060

1.147

0.087***

0.025

1.091

0.053†

0.031

1.054

16

Total loans

0.027

0.063

1.027

0.016

0.035

1.016

0.024

0.030

1.024

17

Age

−0.148*

0.062

0.862

−0.104***

0.017

0.901

 −0.057***

0.017

0.945

18

Female

−0.421

0.368

0.656

0.168

0.118

1.183

0.121

0.135

1.129

19

First generation

0.046

0.285

1.047

−0.530***

0.118

0.589

 −0.323*

0.141

0.724

20

Underrepresented minority

−0.552

0.377

0.576

−0.101

0.146

0.904

0.419*

0.169

1.520

21

Income in 2nd quartile

0.360

0.351

1.433

0.178

0.147

1.195

0.058

0.189

1.060

22

Income in 3rd quartile

−0.246

0.418

0.782

0.141

0.181

1.151

0.194

0.205

1.214

23

Income in 4th quartile

0.058

0.489

1.060

0.205

0.192

1.228

0.228

0.219

1.256

           
 

Baccalaureate expectations ON

         

24

IMPT: Community leader

0.457***

0.105

1.579

0.457***

0.105

1.579

0.457***

0.105

1.579

25

IMPT: Financially well off

0.118

0.124

1.125

0.118

0.124

1.125

0.118

0.124

1.125

26

IMPT: Political influence

0.366**

0.140

1.442

0.366**

0.140

1.442

0.366**

0.140

1.442

           
 

Transfer Intent ON

         

27

IMPT: Community leader

0.312***

0.083

1.366

0.312***

0.083

1.366

0.312***

0.083

1.366

28

IMPT: Financially well off

0.116

0.104

1.123

0.116

0.104

1.123

0.116

0.104

1.123

29

IMPT: Political influence

0.139

0.105

1.149

0.139

0.105

1.149

0.139

0.105

1.149

           
 

Integrative experiences ON

         

30

Intercept α0 (random)

         

31

IMPT: Community leader

0.446***

0.069

1.562

0.446***

0.069

1.562

0.446***

0.069

1.562

32

IMPT: Financially well off

0.068

0.073

1.070

0.068

0.073

1.070

0.068

0.073

1.070

33

IMPT: Political influence

0.218*

0.085

1.244

0.218*

0.085

1.244

0.218*

0.085

1.244

 

Between-institution

         
 

“Random Intercept (β0)” ON

         

34

_Constant γ00

−7.099***

1.265

0.001

−3.233***

0.704

0.039

−2.956***

0.492

0.052

35

% Part-time instructors

0.011

0.015

1.011

0.005

0.006

1.005

0.000

0.005

1.000

36

% Cert. awarded

−0.025**

0.010

0.975

−0.018***

0.005

0.982

−0.006†

0.004

0.994

37

% Vocational AA awarded

−0.027***

0.007

0.973

−0.009*

0.004

0.991

0.000

0.004

1.000

38

Nearby highly selective

0.440

0.362

1.553

−0.027

0.164

0.973

 −0.166

0.219

0.847

39

Nearby moderately selective

−1.029†

0.558

0.357

−0.185

0.208

0.831

 −0.272

0.193

0.762

40

Nearby less selective

0.684

0.571

1.982

-0.075

0.195

0.928

0.324

0.204

1.383

           
 

“Random Intercept (α0)” ON

         

41

_Constant γ10

−0.058

0.210

0.944

−0.058

0.210

0.944

−0.058

0.210

0.944

42

% Part-time instructors

−0.001

0.003

0.999

−0.001

0.003

0.999

−0.001

0.003

0.999

43

% Cert. awarded

−0.006***

0.002

0.994

−0.006***

0.002

0.994

−0.006***

0.002

0.994

44

% Vocational AA awarded

0.000

0.002

1.000

0.000

0.002

1.000

0.000

0.002

1.000

Note: b = Unstandardized estimates, se = Standard error, RRR = Relative risk ratio. Variables measured in percentages (i.e., Remedial courses ratio, % Credits earned, % Part-time instructors, % Cert. awarded, and % Vocational AA awarded) are in scales of 0 to 100.

*** p < .001. ** p < .01. * p < .05. † < .10.The constant term γ00 (Row 34 of Table 3) represents the estimated overall average log odds of upward transfer versus no transfer while holding all institution-level variables at zero and all student-level variables at their grand means (or at zero for dummy variables). The negative values of γ00 indicate that the likelihood of community college beginners transferring upward was significantly smaller than the likelihood of their reporting no upward transfer. The likelihood of transferring to a highly or moderately selective institution is particularly small (RRR = .001).

At the student level, holding baccalaureate expectations increased the likelihood of transfer to highly and moderately selective institutions. Other things being equal, holding baccalaureate expectations increased the likelihood of transfer to a highly selective institution by a factor of 11.314 and to a moderately selective institution by a factor of 4.267. Also, compared with their counterparts not enrolled in a transfer-directed program, students showing transfer intent by enrolling in such programs were 3.476 times more likely to transfer to highly selective institutions, 2.282 times more likely to transfer to moderately selective institutions, and 1.781 times more likely to transfer to less selective institutions.

In regard to student experiences within community colleges, although the signs of the multinomial regression coefficients were all positive, integrative experiences did not show a significant relationship to upward transfer in any of the selectivity categories. By comparison, a number of course-taking variables demonstrated significant, varying links with transfer to four-year institutions of varying selectivity. Specifically, percentage of credits earned versus credits attempted was positively and statistically significantly associated with the likelihood of upward transfer in any scenario. For each percentage point increase in credits earned versus credits attempted, students were 1.094 times more likely to transfer to highly selective institutions, 1.036 times more likely to transfer to moderately selective schools, and 1.020 times more likely to transfer to less selective institutions, again all as opposed to no transfer to any four-year institution. On the other hand, looking at academic readiness from the perspective of the need for remedial courses, the larger the percentage of remedial courses students were enrolled in, the less likely that they transferred to four-year institutions of any level of selectivity (RRR = .904, .899, and .956 respectively). In terms of the rigor of course-taking, earning AP credits during high school positively contributed to the likelihood of transfer to four-year institutions of any level of selectivity. Earning advanced math/calculus college credits was only conducive to transfer to highly selective schools, with a marginally significant regression coefficient. Earning advanced English writing credits did not increase or decrease the likelihood of upward transfer to any type of four-year institutions. Controlling for these and other variables in the model, academic performance, as indicated by first-term GPA, did not matter much for upward transfer.

Among environmental factors, full-time enrollment during the first year did not contribute to the likelihood of transfer to highly selective institutions, but it increased the likelihood of transfer to moderately and less selective institutions. As for employment obligations, number of work hours had a marginally significant negative relationship with transfer to a highly selective institution while exerting no influence on transfer to moderately or less selective institutions. Working off-campus did not show any relationship with upward transfer. Regarding financial aid received, the only type of aid that helped increase the likelihood of upward transfer was grants. A $1,000 increase in grants received was associated with an increase in the likelihood of transfer to a highly selective institution by a factor of 1.147 and to a moderately selective institution by a factor of 1.091. The relationship between the amount of grants received and transfer to less selective institutions was marginally significant in the positive direction.

In terms of demographic background, being older and being a first-generation college student were both associated with decreased likelihood of transfer to four-year institutions of any level of selectivity. In the presence of these background controls, family income and being female did not emerge as statistically significant factors predicting transfer, regardless of the selectivity of destination schools. Being an underrepresented minority student increased the likelihood of transfer to less selective institutions.

Baccalaureate expectations, transfer intent, and integrative experiences were influenced in part by students’ motivational beliefs about upward mobility. Specifically, students’ perceived importance of being a community leader was significantly and positively related to their demonstrating transfer intent by enrolling in a transfer-directed program. Perceived importance of being a community leader and influencing political structure both positively shaped students’ baccalaureate expectations and integrative experiences at community colleges.

In regard to the relationship between institutional characteristics and upward transfer, the more strongly vocationally focused the community colleges were, the less likely their students were to transfer to highly or moderately selective four-year institutions. Neither the percentage of part-time instructional faculty and staff nor the presence of selective four-year colleges nearby was influential in students’ likelihood of upward transfer, except that having moderately selective institutions nearby reduced the likelihood of transfer to highly selective institutions as compared with no transfer.

Do community college characteristics shape students’ integrative experiences? Among those institutional factors explored in the study, only one aspect of the vocational focus of community colleges, i.e., percentage of certificates awarded, exerted a significant negative impact on integrative experiences (Line 43, Table 3). For a more intuitive depiction of the model’s results, see Figure 2.

Figure 2. Multilevel path model diagrams

[39_21643.htm_g/00046.jpg]


H = Highly selective, M = Moderately selective, L = Less selective. Non-significant paths and factors are denoted in gray color. Only unstandardized estimates achieving statistical significance are reported.

*** p< .001.  ** p< .01.  * p< .05.  †< .10.

DISCUSSION OF THE RESULTS

In this study modeling upward transfer, I account for the differential selectivity of the receiving institutions along with a wide array of student socio-demographic background characteristics and academic experiences. The path model results show that first-generation and older students have a lower likelihood of upward transfer. These results are not surprising in light of prior literature (e.g., Bailey et al., 2005; Dougherty & Kienzl, 2006).6 However, the most troublesome finding is the sheer fact that, descriptively, very few community college students transferred to highly selective institutions. In this sense, upward transfer access is still not equitable, especially considering the sizable differences in the social and economic returns from attending selective institutions and attending less selective ones (Dale & Krueger, 2011). Both education policy and research must continue to tackle challenges and create opportunities to help broaden community college student access to four-year institutions. I now turn to a discussion of the study’s results outlined above and offer explanations of these findings in light of theory and prior literature. Where appropriate, I highlight the results’ implications for policy and future research.

TRANSFER: THE ROLE OF MOTIVATION AND COMMUNITY COLLEGE EXPERIENCES

Among the holistic set of individual-level characteristics I examined in this study, two things stand out: students’ motivation and intent regarding their future education and the academic momentum they build through coursework. More specifically, upward transfer is positively associated with students’ expectations of earning at least a baccalaureate degree and transfer intent as shown by enrollment in a transfer-oriented program. By measuring both the motivational (expecting to earn at least a bachelor’s degree) and behavioral (enrolling in a transfer-directed program) dimensions of transfer aspirations and finding that both matter to transfer outcomes, this study reconciles the sometimes opposing views about how to authentically capture community college students’ educational intent. This study illuminates the importance of and need for engaging both students’ motivations and their actual behaviors in order to best prepare them for transfer.

This study also unveils the value of conceptualizing and constructing the community college academic experience from a momentum-building perspective (Wang, Chan, Phelps, & Washbon, 2015). Given the complex and often muddy nature of course-taking at community colleges, it is more pressing to assist students in transitioning into and through program and course pathways aligned with their interests than to focus on academic performance narrowly conceived in the form of GPA. This study’s results concerning students’ course-taking and academic performance in relation to upward transfer illustrate this point well: It is earning credits at a high speed, enrolling in transfer programs, and having rigorous coursework in both high school and the community college—factors boosting academic momentum, instead of a narrow measure of GPA—that are significantly associated with the likelihood of upward transfer. Given the relatively high educational aspirations, in contrast to low transfer rates, among the study sample, it is even more critical to cultivate early academic momentum among transfer-aspiring students by guiding them through well-sequenced, rigorous coursework, as well as capitalizing on any momentum carried over from high school (Wang et al., 2015). Interventions such as the City University of New York’s Accelerated Study in Associate Programs that help place community college students in accelerated pathways while providing a holistic set of support services (Scrivener et al., 2015) represent promising approaches to achieving these goals.

In addition, some more nuanced results are particularly noteworthy when examining what individual factors distinguish those who transfer to highly selective institutions from their counterparts who transfer to moderately or less selective schools. In particular, holding baccalaureate expectations and transfer intent seem to benefit those who transfer to selective institutions much more strongly than those who transfer to less selective ones. Similarly, rigorous course-taking, in the form of both achieving AP credits and having taken advanced math courses at community colleges, distinguishes not only those who transfer from those who do not, but also those who transfer to highly selective institutions from their transfer counterparts headed toward moderately or less selective colleges. Analogously to the empirical evidence suggesting that rigorous course-taking and curricular behaviors may increase high school students’ likelihood of being admitted into selective institutions (Attewell & Domina, 2008), individuals who engage in more rigorous coursework at community colleges also have a greater chance of transferring to a more selective four-year institution.

However, this additive, linear “boosting” effect exerted by student motivation and course-taking that promotes momentum on transfer outcomes is no longer applicable to integrative experiences and first-term GPA, both of which show no significant influence on upward transfer. Considered in light of one another, these findings suggest that the actual intensity and progress in academic course-taking truly underlie differential transfer outcomes among community college students. These academic behavioral characteristics may represent salient markers speaking to community college students’ fit with four-year institutions of varying selectivity. This is similar to past literature describing students’ choice of academic environments compatible with their personality (Smart, Feldman, & Ethington, 2000). Based on ability and interest, students may select an environment that is congruent with their abilities and interests (Porter & Umbach, 2006).

The finding that integrative experiences did not contribute to upward transfer needs further exploration. For example, recent research (e.g., Deil-Amen, 2011; Karp et al., 2010) has shown that community college students integrate themselves into the postsecondary environment through participation in information networks, which allow them to navigate the campus environment and create a sense of belonging, consequently leading them to feel that their academic wellbeing is valued. Thus, students who are highly integrated into community colleges may create a bond between themselves and a postsecondary environment that is less competitive, which may or may not encourage them to transfer upward. These findings suggest that, as community colleges continue efforts to find innovative ways to integrate their largely commuting student body in support of upward transfer, they should recognize that integration alone is not enough to broaden transfer access to four-year colleges. Community college educators must place an intentional focus on assisting transfer-aspiring students in identifying academic pathways through rigorous coursework consistent with and additive toward their long-term educational goals, helping them stay on track, and promoting efficient academic progress. Future research that collects targeted data to delve deeper into how to build an institutional culture of success where integrative experiences and rigorous course taking are both cultivated to facilitate each other will greatly inform this effort.

Also worth considering with regard to advising transfer students is the finding that the importance students attach to being a community leader positively shapes their baccalaureate expectations, transfer intent, and integrative experiences; in addition, the importance they place on being able to influence political structure seems to promote their baccalaureate expectations and integrative experiences. This may be especially true for students who culturally have a strong sense of and belonging to a community (Crisp & Nora, 2010). Moreover, previous research (Laanan, 2003; Wang, 2009, 2012) indicated the central role that motivational beliefs play in community college student outcomes such as transfer, without much explicit knowledge as to how motivational beliefs work to enhance student outcomes. Using a path analysis, this study is able to discern that beliefs about upward mobility seem to enhance transfer outcomes by sustaining students’ baccalaureate expectations and motivating them to enroll in a directed transfer program. This suggests that it is critically important for community colleges to intentionally engage and cultivate positive motivational beliefs and tap into students’ attitudes of community when advising and supporting individuals in carving out a viable transfer pathway. Future empirical endeavors, especially qualitative work, will help illuminate specific approaches and strategies to achieve this purpose.

TRANSFER AND COMMUNITY COLLEGE CHARACTERISTICS

Unlike most previous studies on transfer, which largely relied on individual-level data (for exceptions, see Crisp & Núñez, 2014; Eagan & Jaeger, 2009), this study delves into a number of institutional characteristics that are most theoretically salient in their potential to influence student transfer to four-year institutions of varying selectivity. While both measures of the vocational focus of community colleges, i.e., percentage of certificates awarded and percentage of vocational associate’s degrees awarded, are negatively associated with transfer to highly and moderately selective institutions, they do not particularly affect chances of transfer to less selective institutions. This finding adds to the mixed empirical evidence on the impact of vocational focus on community college student transfer (e.g., Porchea, Allen, Robbins, & Phelps, 2010; Roksa, 2006). Unlike previous research, where the outcome was transfer to any four-year institution regardless of selectivity, this study differentiates the transfer outcome based on the selectivity of receiving four-year institutions. Therefore, the potential influence of community colleges’ vocational focus on transfer is assessed in a more nuanced way.

Given their institutional focus on career and technical education, vocationally oriented community colleges may emphasize programs and offerings that serve the needs of local businesses, thus redirecting resources from general education and building and maintaining effective articulation agreements with selective four-year institutions (Dougherty, 2002; Gumport, 2003). I should note that, in light of their different mission from that of liberal arts/transfer-oriented community colleges, this finding is expected and is not meant as an unjust criticism of vocationally focused community colleges. On the other hand, it is intriguing to uncover that the vocational orientation does not necessarily discourage students from transferring to less selective institutions. Considering that many of these less selective institutions are broad-access institutions (Crisp, Horn, Dizinno, & Barlow, 2013; Kirst, Stevens, & Proctor, 2010; Núñez, Hurtado, & Galdeano, 2015), this finding may reflect the democratizing function shared by community colleges and broad-access four-year institutions. An additional explanation may reside in the fact that many non-selective, broad-access institutions were established with an unambiguous occupational focus (Grubb & Lazerson, 2005) and may thus serve as an alternative to immediate workforce participation for community college students enrolled at vocationally oriented community colleges. On a related note, as the “new vocationalism” is on the rise and employers are demanding more advanced skills and competencies from graduating students (Bragg, 2001; Grubb, 1996), it has become critical that higher education better equip students with the skillsets needed to succeed in the workforce. This has resulted in efforts to combine academic and vocational curricula from primary all the way through postsecondary education (Bragg, 2001). Considering that community colleges with a vocational focus are already set up to provide students with the appropriate preparation to enter a particular field, these institutions could also serve as an excellent stepping stone to a four-year institution, particularly for employers who seek workers with higher degrees such as the baccalaureate, along with adequate occupational training.

This study suggests that employment of part-time instructional faculty and staff neither benefits nor hurts community college students’ chances of upward transfer. This result differs from those of other studies that indicated a negative association between the proportion of part-time faculty and students’ upward transfer (e.g., Bailey et al., 2005; Eagan & Jaeger, 2009). For example, Eagan and Jaeger (2009) pointed out that part-time faculty may help alleviate institutional costs at the expense of community college student success. On the one hand, such deviations in findings may be attributed to the different datasets and samples used in different studies. On the other hand, the results of this current study may illuminate other underlying, unobservable factors that may actually counter the potentially negative impacts of part-time faculty. Although part-time faculty may have less time to devote to their students (Lundberg, 2014), especially outside of class, recent research has shown that, for community college students, it is what happens inside the classroom that truly makes a difference (Deil-Amen, 2011). This means that even if part-time instructors are unable to give students adequate attention outside of class, as long as they provide quality academic and social experiences or integration inside the classroom, students may be just as likely to transfer regardless of the employment status of community college faculty.

Contrary to what was expected, overall, proximity to selective institutions does not appear to be influential in upward transfer. This result suggests that the sheer physical presence of selective four-year institutions in the vicinities of community colleges does not contribute to students’ transfer chances. What truly matters, in addition to the significant student and institutional factors revealed by the study, may include institution-level articulation agreements between community colleges and their nearby four-year partners that negotiate the requirements to facilitate student flow from two- to four-year institutions (Anderson et al., 2006). An even larger and deeper issue may reside with the receiving end: There are potentially structural, social, and political factors that pose barriers to transfer from a community college to an elite institution. Although community colleges have opened doors to postsecondary education for those who might otherwise not have had an opportunity to attend college, the expansion of access may have also allowed four-year institutions to reinforce selectivity and social stratification in higher education (Karabel, 1972). Furthermore, highly selective institutions may present themselves or be perceived as less welcoming and receptive environments for transfer-aspiring community college students and limit their access to these institutions, especially when efforts to recruit transfer students have been disturbingly lacking (Dowd et al., 2008).

Due to the scope of the study and data constraints, this study cannot explore the effect of these nuances, such as specific articulation agreements, enacted or unwritten policies regarding transfer admission at selective four-year institutions that may hinder community college students’ access, or perceptions of selective institutions’ climate and receptivity among community college students. It should be noted that, while statewide articulation agreements do not necessarily result in an increased probability of transfer (Anderson et al., 2006; Roksa, 2009; Roksa & Keith, 2008), a community college partnership model (Amey, Eddy, & Campbell, 2010) that encourages genuine partnerships among high schools, community colleges, and four-year institutions would help build social and organizational capital that contributes to the long-term success of students, institutions, and states engaging in collaborative efforts. This is particularly pertinent considering the recent creation of the American Honors network, one such program aimed at recruiting and enrolling community college transfer students in partnering selective four-year institutions (Lederman, 2013). Given the small number of community college transfer students at selective four-year institutions, indicated by both prior research and this study, such initiatives are needed to target and engage selective four-year institutions in encouraging transfer access.

OTHER NOTABLE FINDINGS

The study uncovers a few other findings that warrant additional discussion. The first is the result patterns around financial-aid receipt. Differentiating between both the types of aid and institutional selectivity, this research pinpoints the importance of receiving grants instead of other types of financial aid. such as work-study and loans, in boosting chances of transfer to more selective institutions. In light of the substantial financial barriers that hinder access to selective institutions (Dowd et al., 2008), receiving grants that students do not need to repay greatly relieves the financial burden—or the perception thereof—often associated with attending selective schools. Work-study opportunities impose obligations outside of academics, which is particularly unattractive to community college students, who tend to be more debt-averse and may already be employed while enrolled at college (McKinney, Scicchitano, & Johns, 2014). This study suggests that the offer of loans or work-study rather than grants would not necessarily remove the perceived or existing financial barriers to upward transfer.

In addition, while integrative experiences did not seem to influence upward transfer, in answering the question of how community college characteristics shape integrative experiences within community colleges, this study shows that only percentage of certificates awarded negatively influences integrative experiences. Given that certificates tend to be short-term programs, a community college with a high ratio of such short-term programs may feature an institutional environment that focuses on speedy completion and credentialing at the possible expense of time and space for student interaction with faculty, advisors, and peers. Also, considering the utilitarian approach to education adopted by many community college students seeking short-term certificates (Cox, 2009), community colleges where these students concentrate would not necessarily see rich integrative experiences. This may be especially true if students’ focus is not only on utility, but also on efficiency (Cox, 2009). Community colleges and students alike may pursue certificate programs and forgo any potential integrative experiences for the sake of practicality and quick attainment. This finding, in conjunction with the fact that percentage of vocational associate’s degrees and percentage of part-time instructional faculty and staff do not deter students from engaging in integrative experiences, may suggest that the influence of institutional characteristics included in the study on student integration is quite limited. Future research should consider practices and strategies that go beyond the structural context of community colleges to truly understand and promote their students’ experiences that lead to desirable transfer outcomes.

CONCLUSION

This study’s findings reinforce persistent issues associated with access and transfer to selective institutions for community college students, which points back to the larger problem of equity in higher education. In light of this social issue, findings from this study make it imperative that educational practices better target improvements for equitable transfer outcomes of the many socioeconomically disadvantaged students attending community colleges who aspire to transfer and earn a bachelor’s degree.

Conceptually and methodologically, this research expands upon existing scholarly work examining transfer by taking into account the heterogeneity of receiving four-year institutions. In addition, the multilevel path model employed in this study helps illuminate not only the extent to which key student and institutional variables influence upward transfer, like previous theoretical and empirical work, but also how this impact is exerted with respect to transfer to selective institutions. This study thus provides nuanced information on institutional and individual effects on upward transfer to four-year colleges of varying selectivity. More specifically, this study demonstrates the significance of motivation and course-taking behaviors and how differently they can ultimately impact transfer to selective and less selective institutions. Being careful to also consider the role of institutional characteristics, this research adds to the mixed results of previous work on transfer, particularly with regard to the influence of part-time faculty on upward transfer. Furthermore, the finding that proximity to selective institutions had no influence on transfer points to other potential underlying factors such as structures, politics, and articulation agreements.

Scholars have long argued that socio-academically disadvantaged students can benefit more from enrolling at elite institutions as compared with their high-performing peers (Bowen et al., 2009; Hoxby & Turner, 2013; McPherson & Shapiro, 1990). This makes it even more critical that practitioners and researchers develop a better understanding of what facilitates upward transfer to selective institutions among the many traditionally underserved students beginning at community colleges. As Bastedo and Flaster (2014) rightfully argued, systematic change that helps resolve inequality resulting from undermatching must be enacted through strong interventions aimed at increasing resources to support students, as well as improving admission and enrollment policies and practices at selective colleges. Taken together, this study’s findings advance our understanding of the complexities of the transfer process and inform postsecondary policy and practice to better serve traditionally disadvantaged community college students in an effort to resolve the potential social inequality in their transfer process.

Notes

1. A few studies also examined state transfer and articulation policies (e.g., Anderson, Sun, & Alfonso, 2006; Roksa, 2009; Roksa & Keith, 2008), but results largely point to little or no impact of these policies on transfer. Roksa and Keith (2008) argued that articulation agreements are primarily designed to prevent loss of credits after students transferred and thus do not directly influence transfer. Furthermore, a substantial number of selective institutions are private institutions that are not subject to statewide articulation polices that focus on public institutions (Ignash & Townsend, 2001; Roksa, 2009). Also, it is only appropriate to consider statewide articulation polices if students transfer to in-state institutions. This is not the case in the context of this study, which is based on a national sample that includes students who transfer across state borders. Therefore, while acknowledging the importance of these statewide policies on post-transfer outcomes, this study does not include these state-level variables in the analysis.
2. Note that transfer intent was measured by actual enrollment in transfer-directed programs; in this sense, this variable also represented one component of student academic behaviors.
3. It would be ideal to include a more comprehensive set of variables measuring the rigor of high school course-taking, but the BPS dataset does not contain high school academic variables for students older than 24 when they started college. Instead, I was able to utilize the postsecondary transcript data to capture the rigor of course-taking at the college level in math and English, as well as using AP credits as a proxy for the rigor of course-taking during high school.
4. For the classification of fields of study into vocational versus non-vocational (i.e., liberal arts), refer to the Appendix.
5. The BPS data were collected through a complex survey design that involved stratification, clustering, and disproportionate sampling. Adopting a model-based approach (Thomas & Heck, 2001), the multilevel path model used in this study directly incorporates the clustering into the analysis by partitioning the variance of the dependent variable into within- and between-group variances explained by the independent variables at each level (Raudenbush & Bryk, 2002). School UnitIDs were specified as the cluster within which students were nested. Disproportionate sampling was addressed through application of the weight variable WTD000.
6. It should be noted that family income was not statistically significantly related to transfer outcomes. This result deviates from prior literature that indicates disparate transfer rates based on students’ family income (e.g., Dowd & Melguizo, 2008). Based on the descriptive data of the study sample (Table 2), weighted percentages indicate a fairly equal distribution of students across different transfer outcome categories. This suggests that in this recent national sample of postsecondary students, student background based on family income is no longer a key determinant in the transfer process, and other background information such as first-generation status serves as a more salient factor associated with transfer.

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APPENDIX

List of Fields of Studies by CIP

[39_21643.htm_g/00047.jpg]


Note: CIP = Classification of Instructional Programs




Cite This Article as: Teachers College Record Volume 118 Number 12, 2016, p. 1-44
https://www.tcrecord.org ID Number: 21643, Date Accessed: 10/23/2021 8:39:01 PM

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About the Author
  • Xueli Wang
    University of Wisconsin-Madison
    E-mail Author
    XUELI WANG is an associate professor in the Department of Educational Leadership and Policy Analysis at the University of Wisconsin-Madison. Her research deals with community college students’ access to, transitioning into, and attainment at 4-year institutions, as well as students’ participation in STEM fields of study. Wang’s recent work includes studies such as “Baccalaureate Expectations of Community College Students: Socio-Demographic, Motivational, and Contextual Influences,” published in Teachers College Record, and “Pathway to a Baccalaureate in STEM fields: Are Community Colleges a Viable Route and Does Early STEM Momentum Matter?” published in Educational Evaluation and Policy Analysis.
 
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