Baccalaureate Expectations of Community College Students: Socio-Demographic, Motivational, and Contextual Influences
by Xueli Wang - 2013
Background/Context: Although much research has dealt with the factors that influence educational expectations, few studies have addressed recent high school graduates who attend community colleges as their first postsecondary institutions. As the costs associated with attending a four-year institution keep rising, community colleges increasingly serve as an affordable entry for many socioeconomically underprivileged students who aspire to earn a bachelor‘s degree and above. The question of sustaining these educational expectations—an essential precursor to the actualization of educational goals—becomes even more important knowledge to pursue.
Purpose/Objective/Research Question/Focus Of Study: This research investigates socio-demographic, motivational, and postsecondary contextual factors underlying community college students’ baccalaureate expectations. The study highlights various influences affecting these educational expectations of community college students, thus improving the understanding of the relationship among student backgrounds, motivational beliefs, college experience, and the development of baccalaureate expectations.
Population/Participants/Subjects: This study is based on a nationally representative sample of spring 2004 high school seniors who were part of the second follow-up study of the Education Longitudinal Study of 2002 (ELS: 2002) and who enrolled in a community college as their first postsecondary institution within two years of graduation from high school. Among the 12,500 students of the 2004 senior cohort who completed the second follow-up interview, roughly 3,000 students who attended community colleges as their first postsecondary institutions were selected as the study‘s sample.
Research Design: The proposed conceptual model was tested by using structural equation modeling (SEM) analysis. After fitting the SEM model for the entire sample and assessing its overall fit, a multiple group analysis was used to ascertain whether the structural model is invariant across gender groups.
Findings/Results: Results indicate that community college students‘ baccalaureate expectations two years after high school were directly and positively influenced by their initial baccalaureate expectations during the high school senior year and their academic integration during the first year of college, but were negatively associated with the number of subjects for remedial work they received. In addition, socio-demographic backgrounds, parental expectations, and motivational beliefs of students indirectly affected subsequent baccalaureate expectations by directly influencing initial expectations. Motivational beliefs also exerted a direct effect on college academic integration, which in turn contributed to students’ subsequent baccalaureate expectations.
Conclusions/Recommendations: This study illuminates the importance of cultivating positive motivational beliefs, promoting academic integration, and improving remedial practices to help community college students move further toward their educational goals. This knowledge should help community college leaders seek innovative ways to better streamline student choices in alignment with their educational expectations.
Among myriad factors that affect educational outcomes, educational expectations certainly have garnered a substantial amount of empirical interest. Numerous scholars have illuminated the importance of educational expectations in shaping long-term educational attainment (e.g., Astin, 1977; Carter, 1999; Duncan, Featherman, & Duncan, 1972; Epps, 1995; Pascarella & Terenzini, 1991, 2005; Sewell, Haller, & Ohlendorf, 1970; Sewell, Haller, & Portes, 1969; Sewell, Hauser, & Wolf, 1980; Teachman, 1987). Educational expectations influence attainment by exerting effects on a number of important factors closely correlated with educational attainment. Specifically, educational expectations have a positive impact on beliefs and attitudes toward schooling and motivate students to engage in academics (Dweck & Elliott 1983; Eccles, 1983). Educational expectations also have strong relationships with academic achievement (Astin, 1977; Epps, 1995) and students effort on studying (Domina, Conley, & Farkas, 2011). In addition, research on social stratification has suggested that educational expectations mediate the effect of social backgrounds on attainment (McCormick, 1997). In the literature on college student success, student commitment to educational expectations remains central in a variety of postsecondary persistence and attainment models (Bean & Metzner, 1985; Braxton & Hirschy, 2005; Nora, Barlow, & Crisp, 2005; Pascarella & Chapman, 1983; Reason, 2009; Swail, Redd, & Perna, 2003; Tinto, 1975, 1993).
The critical role of educational expectations in the educational attainment process lends themselves to focused empirical investigation in their own right. Although much research has dealt with the factors that influence educational expectations, these studies typically concentrate on the secondary rather than postsecondary level. This choice seems legitimate, given that in the K-12 setting, understanding the process in which educational expectations are developed will arguably inform educators about college application and enrollment behavior (Domina, et al., 2011; Eccles & Wigfield, 2002; Jencks, Crouse, & Mueser, 1983; Morgan, 2004; Museus, Harper, & Nichols, 2010; Sewell et al., 1970). After students enroll in college, especially at four-year institutions, persistence and attainment dominate the attention of researchers and policymakers alike.
However, the educational expectations of a distinct college student populationthe many recent high school graduates who attend community colleges as their first postsecondary institutionsstill warrant careful and focused analysis. Educating nearly half of all undergraduate students in the nation, community colleges are critical to achieving President Obamas goal of increasing the proportion of adults ages 25-35 with college degrees from 20% to 40% by 2020 (Remarks of President Barack Obama, 2009). In addition, a disproportionally large number of first-generation students and underrepresented minorities attend community colleges (Cohen & Brawer, 2008). In fact, for the majority of these students, community colleges, when viewed as an alternative route to the bachelors degree, represent the hope and attainability of a baccalaureate education. Nationally, two-thirds to four-fifths of community college entrants expect to earn a bachelors degree or above (Bailey & Morest, 2006; Hoachlander, Sikora, Horn, & Carroll, 2003). However, access does not necessarily translate into attainment that aligns with ones expectation (Heller, 1997). After baccalaureate-aspiring students complete the necessary first step of gaining postsecondary entry, persistence in their educational expectations is what truly dictates their eventual educational attainment (e.g., Reynolds, Stewart, MacDonald, & Sischo, 2006; Rosenbaum, 2001).
It should be noted that in focusing on baccalaureate expectations, this study does not imply that community colleges should solely serve as pathways to four-year institutions and that other student outcomes and community college functions are not important. Indeed, the missions and functions of community colleges have historically been comprehensive. In addition to serving students who intend to transfer, vocational and technical education, continuing education, remediation, and community services have all been valuable institutional emphases for community colleges (Vaughan, 2000). The varying student characteristics and motivations for attending community colleges underscore the need for acknowledging and measuring community college student success in many different ways, and this paper deals with only one element of what makes for success, i.e., baccalaureate expectations.
Yet, baccalaureate expectations of community college students still remain an important topic of inquiry. As the costs associated with attending a four-year institution keep rising, community colleges increasingly serve as an affordable entry for many socioeconomically underprivileged students who aspire to earn a bachelors degree and above (Wang, 2009, 2012). Research has found that comparatively, four-year institutions tend to support higher degree goals than two-year institutions (Brint & Karabel, 1989; Carter 1999). The odds that community college students will adopt or maintain baccalaureate expectations are about 60% lower than those for four-year college students (Cohen & Brawer, 2008). On the other hand, once community college students move further toward their baccalaureate expectations by means of transfer, they seem to achieve an equivalent level of educational attainment compared with their four-year beginning counterparts (Melguizo, Kienzl, & Alfonso, 2011).
So exactly what underlies baccalaureate expectations among community college students? The debate over whether community colleges cool out baccalaureate aspirations has inspired a great deal of research that investigates the returns of a community college education (e.g., Kane & Rouse, 1995; Leigh & Gill, 2004; Long & Kurlaender, 2009; Melguizo & Dowd, 2009; Roksa, 2006). Indeed, many studies employ educational expectations as an independent or control variable (Adelman, 1999, 2006; Alfonso, 2006; Cabrera, Burkum, & La Nasa, 2005; Calcagno & Long, 2008). However, little systematic, longitudinal work has examined the mechanism through which community college students baccalaureate expectations develop or change over time. As community colleges progressively have become an entry point to a bachelors degree for many socioeconomically disadvantaged students, the question of sustaining these expectationsan essential precursor to the actualization of educational goalsbecomes even more important knowledge to pursue.
As a step in that direction, this study investigates socio-demographic, motivational, and postsecondary contextual factors underlying community college students baccalaureate expectations. This study adds to the literature on community college students educational expectations, highlighting various influences affecting those expectations, thus improving the understanding of the relationship among student backgrounds, motivational beliefs, college experience, and the development of baccalaureate expectations.
REVIEW OF THE LITERATURE
This section focuses on existing scholarship and empirical research surrounding educational expectations and aspirations. Although educational expectations and educational aspirations often are used interchangeably, it should be noted that these are two distinct constructs (Museus et al., 2010; Wang, 2012). Educational expectations speak to individuals assessment of their future attainment, which often takes into consideration external constraints (Museus & Hendel, 2005); whereas educational aspirations reflect individuals desired educational outcomes without reference to environmental constraints or limitations on resources (Hauser & Anderson, 1991). On the other hand, educational aspirations and their associated social constraints are fundamental components of students educational expectations (Museus et al., 2010). In addition, given the few formal constraints in American education (McCormick, 1997), educational aspirations and expectations may often be indistinguishable. Therefore, this study reviews literature dealing with both educational aspirations and educational expectations. For the purpose of consistency, this article primarily uses the term educational expectations.
THE ROLE OF EDUCATIONAL EXPECTATIONS IN EDUCATIONAL ATTAINMENT MODELS
Educational expectations and their link to student effort and attainment have been highlighted in sociological, psychological, and educational literature that attempts to explain educational attainment. The educational and early occupational status attainment process, or the Wisconsin model, introduced by Sewell et al. (1969), is one of the oldest and most prominent theories that accounts for the importance of educational expectations in educational attainment. Asserting that educational expectations are a vital part of educational attainment, the status attainment model stipulates that students family backgrounds and mental abilities influence both their educational performance and the educational advice they receive. Performance and advice together shape educational and occupational expectations, which then directly influence educational and occupational attainment. This model has been replicated and validated using nationally representative data and is widely accepted in sociology (Domina et al., 2011; Jencks et al., 1983; Sewell et al., 1970). While a number of scholars have questioned the causal relationship between educational expectations and educational attainment and argued that a students perception of costs and benefits associated with educational attainment, instead of educational expectations per se, determines attainment levels (Alexander & Cook, 1979; Jencks et al. 1983; Manski & Wise, 1983), educational expectations in this context may still represent important proxy measures of these cost/benefit perceptions (Domina et al., 2011).
From a psychological perspective, educational expectations shape a students beliefs and behaviors, which in turn determine educational attainment (Eccles & Wigfield, 2002). Tintos (1975) model of college student attrition also recognizes the importance of having and being committed to the goal of completing college as one of many interrelated factors that predict educational persistence. Similarly, youth who hold aspirations to attend college are significantly more likely to enroll in college (Morgan, 1998; Reynolds et al., 2006), and for those who do enroll, educational expectations may influence attainment (e.g., Adelman, 2006).
FACTORS THAT INFLUENCE EDUCATIONAL EXPECTATIONS
A number of empirical studies have explored factors that influence educational expectations. Students demographic background is found to play an important role in shaping educational expectations. In regard to gender, contrary to findings from earlier research (1991 and earlier) that found males to have higher expectations and aspirations, more recent studies have found that females are likely to have higher educational expectations than males in the 8th, 10th, and 12th grades as well as two years past high school (e.g., Mello, 2008). Race/ethnicity also matters. African American and Hispanic males have higher expectations than White males, but they are less likely to maintain these expectations over time (Behnke, Piercy, & Diversi, 2004; Carter, 1999). In addition, the influence of expectations on attainment seems to be greater for White students compared to African American students (Morgan, 2004). Expectations change after high school at a higher rate for African American students compared to White students, which may indicate a larger influence of higher education institutional experiences (Carter, 1999). Meanwhile, Asian students tend to have higher family educational expectations than other racial groups that, in turn, improve their educational attainment (Kao & Tienda, 1995).
Family backgrounds also play an important role in developing educational expectations. There is evidence suggesting that family socioeconomic status (SES) is positively related to educational expectations (Hanson, 1994). On a related note, parental education also has been shown to positively impact student expectations (Hossler & Stage, 1992; Turley, Santos, & Ceja, 2007). In addition, Hossler, Schmit, and Vesper (1999) found that independent of SES, the level of parents expectations for their childrens education is positively related to the level of student educational expectations.
A number of high school factors also are related to educational expectations. For example, high school academic performance, one of the strongest predictors of future academic attainment (Adelman, 2006; Tinto, 1975), has been found to have a distinct positive impact on educational expectations (Hanson, 1994; Kao & Tienda, 1995). Also, high school involvement in extracurricular activities like sports or clubs is associated with higher educational aspirations (Lipscomb, 2007). The characteristics of high schools may also influence student expectations. Students at private schools tend to have higher educational aspirations (Coleman & Hoffer, 1987; Corton & Dronkers, 2006). School average SES is positively associated with student expectations and achievement (Marsh, 1991), and average neighborhood SES is positively related to student expectations as well (Ainsworth, 2002). School location matters too: Rural students tend to have lower educational expectations while suburban students tend to have higher expectations and outcomes (Herzog & Pittman, 1995; Karen, 2002). A more recent study (Lowman & Elliott, 2010) found three school characteristics that are positively related to educational expectations: (1) size, (2) favorable school climate, and (3) being private or Catholic.
DEVELOPMENT OF EDUCATIONAL EXPECTATIONS AFTER HIGH SCHOOL
Although limited, studies also have explored factors that affect educational expectations of young adults after high school. Not surprisingly, initial expectations and family backgrounds are among the strong predictors for future expectations (Kanouse Haggstrom, Blaschke, Kahan, Lisowski, & Morrison, 1980). Educational expectations do change after high school, although expectations of young adults tend to be stable, and the most significant predictor of postsecondary expectations is initial expectations in high school (Carter, 1999; Kanouse et al., 1980; McCormick, 1997). The changes that do occur are more likely to be a decline, rather than an increase, in expectations of attainment when considering all high school graduates (Alexander, Bozick, & Entwisle, 2008; Carter, 1999). These changes are influenced by institution type, initial educational expectations, background characteristics, high school preparation, measured ability, and academic achievement (McCormick, 1997). Research regarding the impact of an institutions size is mixed. Astin (1993) found that institutional size was negatively associated with degree expectations, while Carter (1999) found that larger institutions seem to facilitate higher educational expectations.
EDUCATIONAL EXPECTATIONS OF COMMUNITY COLLEGE STUDENTS
Of particular relevance to this study is the role played by the level of postsecondary education (i.e., two-year versus four-year) in the development of degree expectations of college students. Some theoretical grounding, including Clarks (1960) cooling-out thesis and Rosenbaums (2001) college-for-all argument, maintains that educational expectations will decline as students progress in the educational process, especially for disadvantaged students with high initial expectations who attend community colleges where resources are limited. Traditionally, these students are from low-income families and underrepresented minority groups in higher education, and their prospects for completing college are often precarious. Burton Clark (1960) discussed the cooling out process in community colleges where students whose academic aspirations were considered unrealistic by counselors were channeled out of transfer programs and into sub-baccalaureate terminal programs.
This criticism, however, has been challenged in a number of recent studies, which have found that, net of demographic and academic measures, community colleges do not necessarily cool out students aspirations toward a bachelors degree (e.g., Alexander et al., 2008; Roksa, 2006). In particular, Alexander et al. (2008) found that disadvantaged students with limited resources do not experience significant decreases in expectations once in college compared to other students. In fact, the authors found that, after controlling for other background characteristics, two-year college attendance is associated with warming up to the idea of earning a college degree among students who did not expect to complete college. In addition, a recent study by Melguizo, Kienzl, and Alfonso (2011) found no statistical difference in terms of educational attainment between transfer and rising junior (traditional baccalaureate) students. Community college transfer students earn equivalent numbers of non-remedial credits and attain baccalaureate degrees at similar rates as four-year rising juniors. The authors concluded that community colleges have the potential to prepare students for success at a four-year college. Taken together, these studies reiterate the importance of understanding what helps sustain baccalaureate expectations in community colleges.
Although prior research has investigated the effect of community colleges on educational expectations, often by comparing community colleges with four-year institutions, only very few studies have specifically looked within the community college student population and explored factors associated with these students educational expectations. Based on data from the Cooperative Institutional Research Program (CIRP), Laanan (2003) analyzed the association between educational expectations and a set of background, high school, and affective factors of first-time, full-time freshmen attending public and private two-year colleges in fall 1996. Given the cross-sectional nature of the study and that degree expectations were measured only once upon postsecondary entry, Laanans findings are limited in that they do not account for the developmental process of educational expectations as well as the potential influence of postsecondary factors on those expectations. In a recent study, Wang (2012) examined factors that predict the stability of baccalaureate expectations of a nationally representative sample of recent high school graduates entering community colleges. The study showed that after accounting for background characteristics, persistence in students baccalaureate expectations two years following high school graduation is related to various aspects of their community college experience, such as interaction with faculty and financial aid receipt. Focusing on baccalaureate aspirants only, Wang (2012) did not include students who expect less than a bachelors degree when beginning at community colleges and who may later increase their degree expectations to a baccalaureate.
In summary, existing literature indicates that postsecondary success is largely dependent on students commitment to their educational expectations. This is particularly true for recent high school graduates who access postsecondary education through a community college; many of these students aspire to the baccalaureate, but enrolling in a community college does not necessarily translate into successful transfer and the eventual attainment of a bachelors degree. On the other hand, there exists very limited knowledge as to how community college entrants socio-demographic backgrounds, motivational beliefs, and academic experiences affect their baccalaureate expectations. Thus focusing on these dynamics, the current study contributes to the small line of research that seeks to understand the mechanism underlying baccalaureate expectations among community college students. Building upon relevant scholarship on the topic (e.g., Laanan 2003; Wang, 2012), this study also extends beyond previous research by integrating higher education literature with pertinent sociological and psychological lenses as well as by modeling the interactive, longitudinal process in which various personal and educational factors interrelate to shape baccalaureate expectations of community college students.
THEORETICAL FRAMEWORK OF THE STUDY
The conceptual framework guiding this study draws on the status attainment model, social capital theory, and college persistence literature. As mentioned previously, the status attainment model highlights the importance of SES (Barr & Dreeben, 1983) and the influence of significant others in shaping educational expectations (Mau, 1995). This model has particularly informed prior research on educational expectations of community college students (Laanan, 2003; Wang, 2012). Although the original status attainment model also emphasizes the role of mental abilities and academic performance, in recent years, the college-for-all ethos has pervasively encouraged high levels of educational expectations apart from consideration of academic preparedness (Alexander et al., 2008). Therefore, when studying recent high school graduates, these variables may not be as relevant as they were in the 60s and 70s.
Another appropriate theoretical perspective is the social capital theory (Coleman, 1988), which argues that interactions and networks of interactions among individuals that facilitate productive activities constitute social capital. In the context of education, social capital in the form of these relations and networks becomes an important resource that aids students in achieving their educational goals (Coleman, 1998; Tierney & Venegas, 2006). In postsecondary education, social capital may be developed through academically focused interaction with faculty, advisors, and other types of socialization sources, and these dimensions may influence the development of educational expectations of community college students (Wang, 2012).
Although the status attainment model and social capital theory have been largely validated through research on students educational expectations, especially at the secondary level (e.g., Domina et al., 2011; Jencks et al., 1983; Sewell et al., 1970), these two theoretical frameworks do not account for the potential role of students personally held values and beliefs or postsecondary supports and barriers in studying educational expectations among community college students. This limitation can be remedied by utilizing relevant postsecondary persistence models, especially those appropriate in a community college context. Over the past few decades, numerous models of college persistence have been advanced to guide research that attempts to unravel the factors underlying college student departure (e.g., Bean, 1980; Swail et al., 2003; Tinto, 1975, 1993). Most of these models, however, were developed with the traditional four-year student population in mind (Hirschy, Bremer, & Castellano, 2011). For example, Tintos model received little empirical support in research on commuter students (Braxton, Sullivan, & Johnson, 1997).
In response to this limitation, Braxton, Hirschy, and McClendon (2004) proposed a model that incorporates multidisciplinary perspectives and focuses on commuter institutions. This model, later updated by Braxton and Hirschy (2005), maintains that a students decision to persist is influenced by the students entry characteristics, environments external and internal to the campus, and academic integration. Of particular note, among many traditional measures of student entry characteristics, such as gender and race, the model also highlights the importance of motivational beliefs in understanding students decision to persist. Although the focal outcome of this model is not educational expectations, given the close relationship between expectations and attainment, elements of this model should be of value in examining educational expectations among community college students. A number of studies (e.g., Laanan, 2003; Wang, 2009, in press) have found that motivational beliefs are important factors in community college student outcomes such as transfer, academic performance, and postsecondary persistence. In particular, students perceived value of education and career success may be especially relevant, given that individuals perceived value of education and anticipation of future career attainment will influence their cognitive and motivational process through their educational experience (Eccles & Wigfield, 2002).
Integrating these theoretical lenses and prior literature, this study develops a conceptual framework for understanding the baccalaureate expectations of community college students. The model hypothesizes that baccalaureate expectations of community college students are influenced by their entry characteristics and postsecondary contextual factors after they enroll in community colleges. Entry characteristics include those pinpointed by the status attainment model (e.g., SES and parental influence). They also include motivational attributes that are underscored by Braxton and Hirschy (2005) and Bean and Eaton (2000). Informed by the social capital theory (Coleman, 1988) and recent empirical evidence on baccalaureate expectations of community college students (Wang, 2012), postsecondary contextual factors include academic integration, which represents the most likely opportunities for gaining social capital, especially through interactions with faculty and academic advisors. Also relevant are experiences that are external to the college setting, such as hours of employment and family responsibilities. These factors are modeled as external demands affecting students baccalaureate expectations. In addition, a number of other postsecondary contextual factors may come into play, such as remediation, financial aid receipt, and enrollment intensity. It is assumed that these sets of variables jointly influence the development of baccalaureate expectations of community college students. This model is depicted by Figure 1.
Figure 1. Theoretical model of the study
Specifically, students subsequent baccalaureate expectations in college are hypothesized to be affected by both prior baccalaureate expectations during high school senior year and a set of postsecondary contextual factors. The conceptual framework also hypothesizes that parental expectations and students motivational beliefs have carryover effects and thus influence students subsequent baccalaureate expectations. In addition, students initial baccalaureate expectations and motivational beliefs also affect their academic integration in community colleges. This hypothesized relationship is based on the psychological perspective suggesting that students are inclined to pursue certain activities during college, which in turn influences their educational outcomes (Kuh 1999; Olsen et al., 1998). This study seeks to understand the direct and indirect influence of these various socio-demographic, motivational, and contextual factors on community college students baccalaureate expectations.
DATA AND SAMPLE
The study draws upon the first and second follow-up interviews of the Education Longitudinal Study of 2002 (ELS:2002), sponsored by the National Center for Education Statistics. Focusing on the secondary-postsecondary transition, ELS:2002 followed a national sample of high school students who were sophomores in 2002. The first follow-up was conducted in 2004 and the sample was augmented to represent high school seniors. The second follow-up took place in 2006 and collected data on student access to postsecondary education and various aspects of college experience. Student educational expectations were measured in both 2004 and 2006.
This studys sample is the ELS spring 2004 high school seniors who were part of the second follow-up study and who enrolled in a community college as their first postsecondary institution within two years of graduation from high school. Among the 12,500 students of the 2004 senior cohort who completed the second follow-up interview, slightly over 3,000 students attended community colleges as their first postsecondary institutions. After appropriate weighting using the panel weight (F2F1WT), this sample generalizes to the population of spring 2004 high school graduates who accessed postsecondary education through a community college.
The key dependent variable is respondents baccalaureate expectations in 2006, a binary variable coded 1 if the student expected to earn a bachelors degree or above and zero otherwise. This variable was derived from the survey item pertaining to students educational expectations measured in 2006two years after high school graduation.
In the model, the key independent variables include two exogenous latent factors upon postsecondary entry: (1) parental expectations, measured by how far in school respondents mothers and fathers, respectively, want the respondents to achieve in education; and (2) respondents motivational beliefs, constructed by four survey items on 3-point Likert scales that address respondents attitudes toward work and education, including their perceived importance of being successful in a line of work, being able to find steady work, being an expert in field of work, and getting a good education. Also included are social background measures such as race/ethnicity, SES, and first-generation status.
There are two mediating variables: one observed measure at the high school level and one latent variable at the college level. The high school mediating variable, students initial baccalaureate expectations, is a binary variable measured by whether the respondents expected to earn a bachelors degree or above during high school senior year. The college latent mediating variable is respondents academic integration at community colleges, which is represented by the following four survey items (each on a 3-point Likert scale): (1) talking with faculty about academic matters outside of class, (2) meeting with an advisor about academic plans, (3) working on coursework at a school library, and (4) using the web to access a school library for coursework.
Aside from academic integration, postsecondary contextual variables also include the following: remediation, external demands, receipt of financial aid, enrollment intensity, and hours of work. Remediation is measured by the number of subject areas in which students took remedial courses to improve their basic skills. External demands that may weaken students baccalaureate expectations are factored by variables of being married and having biological children. The receipt of financial aid is a binary variable based on a students first-year financial aid status. Enrollment intensity indicates a students full-time/part-time status, and hours of work measure a students weekly hours spent in occupational work.
Table 1 describes all endogenous, exogenous, observed, and latent variables used in the study.
Table 1. List of Variables in the Proposed Model
Note. Latent variables are indicated by *.
The proposed conceptual model was tested by using structural equation modeling (SEM) analysis. Taking into consideration measurement errors that are often inherent in survey data, SEM defines latent, multidimensional constructs (e.g., parents expectations, students motivational beliefs) and observed variables (e.g., baccalaureate expectations) while testing the theoretical links and their directions among the key variables in the study. Rooted in psychology, psychometrics, and econometrics, SEM is an appropriate approach to testing whether an a priori structural model fits the observed data grounded in relevant literature and theory (Kaplan, 2000). By and large a confirmatory (i.e., hypothesis testing) technique, SEM consists of two parts: (1) a measurement model based on a confirmatory factor analysis that connects latent variables to observed indicator variables; and (2) a structural model that uses path analysis that accounts for relationships among endogenous, exogenous, and latent variables according to the a priori theoretical framework (Kaplan, 2000; Schreiber, Stage, King, Nora, & Barlow, 2006). Figure 2 describes the SEM diagram based on the theoretical model in Figure 1.
Figure 2. SEM model
The structural part of SEM can be considered as a series of regressions applied to data (Schumacker & Lomax, 2004). In practice, the following regression analyses are performed: the first analysis investigates how students prior baccalaureate expectations upon entering community colleges (EdExpF1) are affected by parental expectations (ParntExp), students motivational beliefs (Motiv), as well as socioeconomic (SES), race/ethnicity, and first-generation status (FirstGen). The second equation hypothesizes that students postsecondary academic integration (Aca) is influenced by their prior baccalaureate expectations (EdExpF1) and their motivational beliefs (Motiv). Finally, the third equation examines how students baccalaureate expectations in community colleges (EdExpF2) are affected by prior expectations (EdExpF1), parental expectations (ParntExp), motivational beliefs (Motiv), postsecondary academic integration (Aca), socioeconomic status (SES), and other postsecondary contextual variables such as number of subjects for remedial work (NumRem), external demands (Ext), receipt of financial aid (Aid), enrollment intensity (FullTime), and work hours (WorkHrs).
Data analysis was performed using Mplus 6.1, a statistical software package that models a mixture of observed continuous, ordinal, nominal scale variables, as well as latent variables, all based on generalized linear models as a unifying framework for both continuous and categorical variables, where the latter are first transformed into continuous linear functions and subsequently modeled by SEM (Kupek, 2006; Muthén & Muthén, 1998-2010). ELS:2002 is characterized by data collection through complex survey design; that is, the sample design involved stratification, disproportionate sampling of strata (e.g., over-sampling certain minority groups), and clustered probability sampling of students clustered within a school (Ingels, Pratt, Wilson, Burns, Currivan, Rogers, & Hubbard-Bednas, 2007). In regard to the clustering effects, traditionally, two approaches have been suggested: model-based approach and design-based approach (Kalton, 1983). A model-based approach involves statistical methods such as multi-level structural equation modeling and hierarchical linear modeling that directly accommodate the clustering in the analysis (Heck & Mahoe, 2004). In contrast, a design-based approach estimates the best overall model fit by focusing on one level of the analysis (Thomas & Heck, 2001). Using a design-based approach, a single level analysis can be maintained after making appropriate adjustments for sample design effects, including unequal case selection probabilities and non-independence of observations resulting from clustered designs (Muthén & Satorra, 1995). This study followed a design-based approach due to the small number of individual cases clustered within institutions, which makes a model-based approach that utilizes methods like multi-level SEM inappropriate. Mplus contains complex survey subcommands that take into account the complex sampling design for both survey weight and the clustering nature of the ELS data.
Following Byrne (1998), the overall model fit was examined and assessed by using chi-square (χ2), comparative fit index (CFI), Tucker-Lewis Fit Index (TLI), and root-mean-square error of approximation (RMSEA), where chi-square and RMSEA are indices of absolute fit and CFI and TLI are indices of incremental/relative fit via comparison to a baseline model (Hooper, Coughlan, & Mullen, 2008). A non-significant chi-square value would suggest that the null hypothesis is not to be rejected, meaning that the proposed theoretical model fits the data. However, the chi-square test is sensitive to sample size, and with a large sample size as in this study, the chi-square value is almost always statistically significant (Wheaton, Muthén, Alwin, & Summers, 1977) and may thus erroneously suggest that the model fit is a poor one (Schumacker & Lomax, 2004). Since chi-square tests often reject null hypotheses due to a large sample size, the relative chi-square (χ2/df)—the chi-square value divided by the degrees of freedom—is used as a relative model fit index (Wheaton et al., 1977). While the recommended χ2/df index ranges from below 2.0 (Ullman, 2001) to below 5.0 (Wheaton et al., 1977), Carmines and McIver (1981) suggested that a model is acceptable if its chi-square value is two or three times as large as its degrees of freedom. Steiger and Lind (1980) proposed using the RMSEA as a model fit index. A smaller RMSEA value indicates a better model-to-data fit. In general, values of 0.01, 0.05, and 0.08 indicate excellent, good, and mediocre fit, respectively (MacCallum, Browne, & Sugawara, 1996). While Heck and Thomas (2000) asserted that a CFI value above 0.90 indicates acceptable model fit, others suggested a higher cutoff standard of 0.95 (Hooper et al., 2008; Schreiber et al., 2006).
After fitting the SEM model for the entire sample and assessing its overall fit, a multiple group analysis was used to ascertain whether the structural model is invariant across gender groups. Prior research based on other student populations suggests that educational expectations and their underlying factors tend to differ based on gender (Mau & Bikos, 2000; Rigsby, Stull, & Morse-Kelley, 1997; Wells, Seifert, Padgett, Park, & Umbach, 2011). Therefore, it is important to cross validate the proposed model among males and females. First, sub-sample models were tested separately based on gender (i.e., testing the model for the female sample only and for the male sample only). This step helps provide an overview of how consistently the model fits different gender groups. To identify possible significant differences in model parameters between groups, structural weight invariance was tested by comparing the unconstrained multiple group model, where all regression paths across groups were freely estimated, with the model in which all structural path values were constrained to be equal across groups. The chi-square difference statistic was then used to assess whether significant differences exist between the unconstrained model and the constrained-equal model. If the chi-square difference statistic does not reveal a significant difference between the models, then it can be concluded that the model has structural weight invariance across gender groups.
Missing data on dependent variables were handled using Mplus programs Full Information Maximum Likelihood (FIML) method. Likelihood-based procedures such as maximum likelihood (ML) or Bayesian multiple imputation (MI) under the missing at random (MAR) assumption currently are considered state-of-the-art in handling missing data (Enders, 2010; Schafer & Graham, 2002). For missing data on observed independent variables, I included covariance of observed independent variables in the model to avoid listwise deletion (Muthén & Muthén, 1998-2010).
THE STUDYS LIMITATIONS
This study has several limitations. One of the most important is that due to ELS:2002s design, the studys data only spans two years after high school. This short time frame prohibits the study from delving deeper into the longitudinal process of the development and change in educational expectations and the long-term impact of the models focal independent variables. This limitation makes it difficult to completely capture community college students transfer behaviors and degree attainment as subsequent educational outcomes. This study will be followed by additional research on the development of baccalaureate expectations over a longer time period and how that development translates into upward transfer and baccalaureate attainment.
Another limitation of the study is that because ELS:2002 follows a particular high school cohort, it excludes non-traditional age students attending community colleges; this limits the studys generalizability to the population of all community college students.
In addition, while the study focused on a select set of theoretically grounded variables in order to achieve a parsimonious model that explains baccalaureate expectations among community college students, other variables relevant to educational expectations may not be represented in the study. For example, the status attainment model discusses the importance of significant others. This study modeled the role of parental expectations, but the influence of other significant people in students lives was not clearly captured, although some of it might be roughly approximated by marital and parental status measuring external demands. In addition, due to the small number of students clustered within community colleges, this study was not able to utilize multi-level analysis that models institutional level variables, such as exposure to part-time faculty that prior research indicates have an influence on community college student success (Eagan & Jaeger, 2009). Also, some studies (Adelman, 1999, 2006; Cabrera et al., 2005) suggest that community college students curricular choices will be an important factor to consider when studying the development of their educational expectations. However, this information is not included given that ELS:2002 lacks postsecondary transcript data that fully describe student course-taking behavior.
The following section first presents descriptive statistics for the demographic characteristics of the studys sample. The model fit is then assessed by examining various model fit indices and discussing results from the multiple group SEM analyses. Following that, various direct and indirect effects of the independent variables on the dependent variables are discussed.
Table 2 displays the descriptive statistics of the sample. In summary, 46.7% of the students in the analytical sample were male and 53.3% were female. Out of all respondents, 62.8% had baccalaureate expectations in their high school senior year, but only 49.9% of them retained their expectations two years later in college. About 18.2% of the respondents initially did not have baccalaureate expectations in 2004, but raised their educational aspirations to expect at least a baccalaureate in 2006. In total, 68.1% of the respondents reported having baccalaureate expectations in 2006.
Table 2. Demographic Characteristics of the Analytical Sample
Notes. Other minorities include students who reported being Native American, multi-racial, or unknown race and ethnicity.
RESULTS OF MEASUREMENT MODEL OF SEM
In this study, the measurement part of the model contained four latent variables: (1) parental expectations on students educational advancement, (2) students motivational beliefs, (3) academic integration in college, and (4) external demands. In a preliminary test of the model fit for the measurement model, the fit indices indicated that the measurement model fit the data adequately, χ2(48) = 277.664, CFI = 0.984, TLI = 0.978, RASEA = 0.039. Later in the full SEM analysis, the confirmatory factor analysis was simultaneously conducted with the path analysis. Table 3 presents the standardized and unstandardized factor loadings of those items underlying the four latent factors in the measurement model.
Table 3. Standardized and Unstandardized Factor Loadings of Measurement Model
*** p< 0.001, ** p< 0.01
MODEL FIT AND MULTIPLE GROUP ANALYSES
The applicability of the model was assessed based on gender. Fit indices for the pooled sample and for each gender subgroup are presented in Table 4. Most of the fit indices were within acceptable ranges, thus indicating that overall the structural model fit the data well for the whole sample as well as for each gender subgroup.
Table 4. Fit Indices of Structural Models
Note. Due to the use of weighted least square mean and variance adjusted (WLSMV) estimator in the study, the chi-square difference value has to be adjusted accordingly. (Mplus Users Guide 6th edition, p. 435 & p. 553).
In addition, tests for invariance were conducted for subgroup comparisons based on gender. With the configural model, all regression paths across gender groups were freely estimated. This model fit the sample data to an acceptable degree (see Table 4). This unconstrained model served as the basis for comparison with the structural weight constrained model in which all structural path values were constrained to be equal across gender groups. A χ2 difference test between the configural model and the constrained-equal model revealed no significant difference, Δχ2(20) = 28.405, p = 0.100, which suggested that there were no gender differences in model parameters. Therefore, the original structural model for the whole sample, which was also a better fitting model, was tenable, χ2(208) = 656.439, p < 0.001, χ2/df = 3.156, CFI = 0.960, TLI = 0.950, RMSEA = .026.
RESULTS OF STRUCTURAL MODEL
Table 5 displays the path coefficients of the three structural equations that measure links among the independent and dependent variables for the entire sample. The latent variables were formatted in italics for easier visual identification. The regression coefficients also represent the direct effects of independent variables on dependent variables. Standardized regression coefficients are also presented in Table 5 to help compare the strengths of the independent variables effects on dependent variables.
Table 5. Coefficient Estimates of Structural Model Based on Pooled Sample
Note. DV = Dependent variable in a given structural equation. Latent variables are italicized.
*** p< 0.001, ** p< 0.01, * p< 0.05, p< 0.10
As indicated in the first structural equation that modeled initial baccalaureate expectations of community college students, both socio-demographic background and motivational attributes were positive and statistically significant predictors. Community college students whose parents held high educational expectations for them and who were of more favorable SES were more likely to report baccalaureate expectations. In addition, being Asian, being African American, and being Hispanic (although the effect of being Hispanic is only marginally significant) all indicated a stronger likelihood of having baccalaureate expectations, compared to being White. Students motivation also emerged as a significant predictor of reporting baccalaureate expectations during the high school senior year.
The path coefficients on the second structural equation indicated that motivational beliefs regarding career success and the value of education had a positive, statistically significant effect on postsecondary academic integration, which was also positively influenced by students initial baccalaureate expectations.
Results from the third structural equation that focused on the studys key outcome, baccalaureate expectations two years after high school, suggested that initial baccalaureate expectations had a significant and strong influence on community college students subsequent baccalaureate expectations. Additionally, academic integration played a positive role on subsequent baccalaureate expectations. Remediation had a statistically significant negative effect on baccalaureate expectations and full-time enrollment showed a significant positive effect. SES continued to exert a significantly positive and direct effect on baccalaureate expectations in college.
The standardized and unstandardized direct and indirect effects of the independent variables are presented in Table 6.
Table 6. Estimates of Direct and Indirect Effects in the Model
Note. Latent variables are italicized.
*** p< 0.001, ** p< 0.01, * p< 0.05, p< 0.10
Aside from these direct influences on baccalaureate expectations of community college students, the analysis uncovered several important indirect effects of background variables. For example, parental expectations exerted a positive impact on community college students baccalaureate expectations by influencing students initial expectations in high school, which then affected the degree of academic integration students experienced in community colleges. In a similar fashion, motivational beliefs related to career success and education positively contributed to baccalaureate expectations through their effects on initial expectations and academic integration during college. Also worthy of note is that SES had a lasting influence on subsequent baccalaureate expectations, both directly and indirectly through its influence on initial expectations. Not surprisingly, initial expectations showed both direct and indirect effects (through academic integration) on subsequent expectations.
In the final structural model (Figure 3), the significant structural paths are highlighted, and the estimated standardized coefficients are denoted along with the paths.
Figure 3. Final SEM diagram
Note. The significant paths with p-values less than 0.01 are highlighted. The standardized estimates are denoted along the significant paths.
This study showed that community college students baccalaureate expectations were strongly influenced by their initial expectations upon postsecondary entry. This result resonates with prior literature on other student populations suggesting that initial educational expectations are one of the best predictors of subsequent degree expectations (e.g., Carter, 1999, 2001; Pascarella, Pierson, Wolniak, & Terenzini, 2004). Community college entrants baccalaureate expectations were also strongly correlated with their socio-demographic backgrounds, which directly affected initial expectations and, through this direct effect, indirectly influenced subsequent expectations. Of particular note are the strong effects of SES and parental expectations on baccalaureate expectations. This finding suggests that these two key elements of the status attainment modelsocial origin (represented by SES) and influence of significant others (represented by parental expectations)have powerful roles in understanding the development of educational expectations of the population of this studys particular interest, recent high school graduates accessing postsecondary education through community colleges. Parental expectations particularly influenced students initial educational expectations. Considering the fact that the studys sample consists of recent high school graduates only, it seems reasonable that parents still have a powerful influence on the expectations and aspirations of these young adults. However, it is social origin that exerted a pervasive and lasting impact, with students from less favorable socioeconomic backgrounds being less likely to report both initial and subsequent baccalaureate expectations. Despite the fact that community colleges opened the door to postsecondary education for many socioeconomically disadvantaged students, it seems that the sorting mechanism based on class continues to perpetuate social inequality (Wang, in press). Therefore, for policymakers, sustaining the educational expectations of students from more humble socioeconomic backgrounds becomes an important equity issue.
Given the limitation of the dataset, this study was not able to directly address the influence of significant people in students lives other than parents, such as spouses and peers. Although marital status was modeled in external demands, this study cannot gauge the influence in terms of emotional support or expectations of those parties such as spouses and close friends and peers. These dynamics should be further explored in future research, especially given the important role of significant others hypothesized in the status attainment model.
Also pertaining to the influence of socio-demographic backgrounds is the effect of race/ethnicity. Prior research generally indicates that certain minorities, especially African American students, tend to have higher educational expectations compared to White students of comparable SES and educational experiences (Hirschman, Lee, & Emeka, 2003; Kao & Tienda, 1995; Qian & Blair, 1999). This study showed that among community college students, race/ethnicity did play a role in explaining students expectations. Asian American, African American, and Hispanic students were more likely to report initial baccalaureate expectations than White students, although the effect of being Hispanic was only marginally significant on initial expectations. It should be pointed out that the racial-ethnic gap in educational expectations does not correspond with the gap in postsecondary access and attainment (Ryan, Seifert, Padgett, Park, & Umbach, 2011). In particular, despite the fact that African American students and Hispanic students are more likely than White students to expect a bachelors degree, their enrollment and graduation rates are much lower than White students (Kao & Thompson, 2003; Skomsvold, Radford, & Berkner, 2011).
Prior studies suggest that female students tend to have higher educational expectations than male students upon postsecondary entry (Mau & Bikos, 2000; Rigsby et al., 1997) and this gender gap in educational expectations seems to match the gender disparity in postsecondary access and success, with male students educational outcomes being lower than those of females (Buchmann & DiPrete, 2006; Skomsvold et al., 2011). As indicated previously, the multiple group analysis in this study suggested that not only did the conceptual model fit both female and male groups, but also the paths along the structural model did not vary significantly based on gender. In other words, the equivalence in model fit affirms the viability of the conceptual model across gender groups. This seems to indicate that while males and females may differ in their educational expectations that largely shape their educational outcomes, the mechanisms undergirding the development of these expectations do not vary based on gender.
One of the factors influencing educational expectations is motivational beliefs, represented by students perceived importance of career success and getting a good education, which had a positive impact on initial baccalaureate expectations. This link seems natural, given that achieving a baccalaureate degree or above is one of the surest ways to higher career attainment and financial well-being (Pascarella & Terenzini, 2005; Swail, 2000) and that the more value one attaches to education, the more likely one aspires to more education (Wang, 2009, 2012).
Another important finding regarding motivational beliefs is that perceived importance of career success and education directly influenced students academic integration at community colleges, which in turn directly and positively affected subsequent baccalaureate expectations. This association between motivation and subsequent baccalaureate expectations through academic integration has important implications. But before delving into that discussion, it is necessary to first address the finding regarding academic integration itself.
Academic integration has often been cited as a strong predictor for future student success (e.g., Pascarella & Terenzini, 2005). Indeed, this study confirmed the positive role academic integration plays in community college students baccalaureate expectations. From the perspective of social capital theory (Coleman, 1988), given that academic integration largely involves interacting with faculty and advisors, students may receive information, values, norms, standards, and expectations for education through the interpersonal relationships they establish with faculty and advisors (Wang, 2012). These interpersonal networks may contribute to community college students baccalaureate expectations. It should also be noted that the population of this study is comprised of recent high school graduates, and the relationship between academic integration and educational expectations may be different among older students attending community colleges because they are more likely to attend community colleges for job retraining and lifelong learning (Dougherty & Kienzl, 2006; Peter & Forrest Cataldi, 2005). Despite this caveat, the studys finding points to the importance of promoting positive academic integration in supporting the educational expectations of baccalaureate-aspiring community college students.
At the same time, it is acknowledged that at community colleges, such integration does not occur as easily as it does at four-year institutions, given that community college students are predominantly commuters, often have competing responsibilities, and are largely exposed to part-time faculty. Therefore, understanding the context underlying academic integration is important in identifying potential ways of promoting such integration. Now, returning to the positive link between motivation and subsequent baccalaureate expectations, this study found that initial baccalaureate expectations along with students motivational beliefs seemed to prompt them to engage in academic integration. Although rarely explored in prior research on community college students educational progress and success, this relationship is consistent with expectancy-value theory, which emphasizes that motivation for persisting in an activity is fundamentally decided by the subjective value that the individual places on the attainment and the perceived likelihood of success (Bandura, 1997). Positive motivational beliefs may provide the drive and incentive for students to interact with faculty and advisors and utilize the Internet and library resources to obtain necessary academic resources to enhance their chances of success in education and future career.
Remediation is often an important part of many community college students experience and may represent important challenges for many (Bahr, 2010). This study showed that the number of subjects for remedial work was negatively associated with students subsequent baccalaureate expectations, corresponding with Wangs (2012) finding that baccalaureate-aspiring community college students who have reading remediation are less likely to persist in their baccalaureate expectations. Given that many community college students are inadequately prepared for college level work and need remedial education, it is not surprising that the need for remedial education in itself is a predictor of dropping out of college (NCES, 2004). It is likely that community college students who are underprepared for college level reading, writing, and/or math struggle with assignments in key subjects, such as math, science, and English, because they lack basic skills. As a result, they may become less confident in what they can achieve in terms of postsecondary education and may lower their educational expectations (Wang, 2012).
The studys model includes a number of other postsecondary variables, such as external demands and enrollment intensity. Results revealed a significant and positive effect of full-time enrollment. The implication of this effect, however, should not be taken at face value, since stronger enrollment intensity is often a proxy of attributes and behavior that have a more direct influence on student success (Wang, in press). The student characteristics that make full-time enrollment possible, such as less family obligations, coming from middle- or upper-class families with fewer financial constraints, or having a stronger motivation to finish college, rather than full-time enrollment in and of itself, may be the real reasons for students to sustain their baccalaureate expectations. None of the other postsecondary control variables seemed to affect community college students baccalaureate expectations, which reiterates the critical role of parental expectations, motivational beliefs (as related to value and importance attached to career success and education), and academic integration on baccalaureate expectations among community college students.
IMPLICATIONS OF THE STUDY
Several implications for educational policy and practice have emerged from this study. First, the connection between student motivation and academic integration may indicate the importance of helping cultivate positive motivational beliefs among students as a means to foster more academic integration which in turn positively influences educational expectations, an approach that this study indicates may be effective among community college students. The good news is that positive motivational attributes can be developed through training (Graham & Weiner, 1996; Loeb & Magee, 1992). Community colleges may consider developing orientation programs that not only explain various support services that help students meet their educational expectations, but also help students clarify their career and academic plans and cultivate the belief that in realizing those expectations and plans, their self-motivation and self-initiation also play a significant role. For transfer-aspiring students, it may also be beneficial to involve faculty and administrators from four-year institutions in orientation programs where they explain specific academic standards, expectations, and transfer support services at four-year colleges and universities. As Mullin (2011) pointed out, community colleges that engage students self-motivation early on are in the best position of helping students streamline their academic choices that follow pathways more directly leading to a successful outcome.
Second, in consideration of this studys finding on the negative relationship between remediation and baccalaureate expectations, community colleges should take even greater and perhaps bolder steps to improve the efficacy of remedial programs. To date, remedial practices still vary widely and there has not been conclusive evidence on the effectiveness of remediation. These unresolved problems associated with remediation indicate that developing measures aimed at effectively fulfilling the remediation function remains a pressing issue of concern. Fortunately, many community colleges are progressively searching for effective models of remedial education. For example, the Virginia Community College System has recently adopted a developmental math curriculum that replaced semester-long developmental math courses with one-credit classes or web-based lessons with variable credit hours, which has allowed students to focus on areas that they need the most help and instructors to attend to the various individual learning needs of students (Gonzalez, 2011). Although the effectiveness of the new curriculum is yet to be assessed, innovative approaches to reinventing remedial practices that are student-centered may prove beneficial to student success. It should be noted that given the large proportion of students in need of remediation at community colleges, the challenge of improving remedial practices might at the same time represent a venue into stronger academic integration for many students earlier in their community college career, especially when remediation is structured in such a way that students experience exposure to faculty and various academic resources in manners that are conducive to learning.
Finally, as community colleges continue to face the pressure to document student success, such as completion and transfer rates, it may prove valuable to consider these success indicators in light of students educational expectations. This will require an intentional effort to collect reliable data on educational expectations as well as to analyze data in identifying sound institutional practices, programs, and services that help sustain and realize students educational expectations. In view of this studys findings, survey instruments that collect and track information on educational expectations, motivational beliefs, and academic integration may aid community colleges in this endeavor.
As Carter (1999) asserted, Educational aspirations are a fundamental part of the attainment process and yet are among the least understood concepts in higher education (p. 18). Over the past decade, although more research has been conducted to address educational expectations in a postsecondary context, still little prior scholarly work has examined factors influencing baccalaureate expectations of community college students. This study set out to fill this significant gap and illuminates the importance of cultivating positive motivational beliefs, promoting academic integration, and improving remedial practices in helping those baccalaureate aspirants move further toward their educational goals. This knowledge should help community college leaders seek innovative ways to better streamline student choices in alignment with their educational expectations.
Students beginning at community colleges are central to the missions and functions of the institutions they attend, two- or four-year. For many of these students, attaining a bachelors degree via upward transfer is a most prominent part of their educational expectations (Wang, in press). Much future research is needed to examine how these students educational expectations change over time, what factors influence these changes, and what educational practices could help these students achieve their long-term educational goals. Given the diversity of these students, it will be a challenging task to examine the myriad factors at different levels that affect student educational outcomes. It is pivotal for higher education researchers to take gradual and solid steps to fully understand the constellation of factors that define community college students educational expectations, trajectories, and outcomes. Accordingly, effective policies and practices can be developed to promote the educational success among these students who were traditionally underrepresented in both research and policy discussions of higher education.
Adelman, C. (1999). Women and men of the engineering path: A model for analysis of undergraduate careers. Washington, DC: US Department of Education.
Adelman, C. (2006). The toolbox revisited: Paths to degree completion from high school through college. Washington, DC: US Department of Education.
Ainsworth, J. W. (2002). Why does it take a village? The mediation of neighborhood effects on educational achievement. Social Forces, 81(1), 117-152.
Alexander, K., Bozick, R., & Entwisle, D. (2008). Warming up, cooling out, or holding steady? Persistence and change in educational expectations after high school. Sociology of Education, 81(4), 371-396.
Alexander, K., & Cook, M. A. (1979). The motivational relevance of educational plans: Questioning the conventional wisdom. Washington, DC: National Institute of Education.
Alfonso, M. (2006). The impact of community college attendance on baccalaureate attainment. Research in Higher Education, 47(8), 873-903.
Astin, A. W. (1977). What matters most in college: Four critical years. San Francisco: Jossey-Bass.
Astin, A. W. (1993). What matters in college? Four critical years revisited. San Francisco: Jossey-Bass.
Bahr, P.R. (2010). Preparing the underprepared: An analysis of racial disparities in postsecondary mathematics remediation. The Journal of Higher Education, 81(2), 209-237.
Bailey, T. R., & Morest, V. S. (2006). Introduction. In T. R. Bailey & V. S. Morest (Eds.), Defending the community college equity agenda (pp.1-27). Baltimore, MD: The Johns Hopkins University Press.
Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.
Barr, R., & Dreeben, R. (1983). How schools work. Chicago: University of Chicago Press.
Bean, J. P. (1980). Dropouts and turnover: The synthesis and test of a causal model of student attrition. Research in Higher Education,12(2), 155-187.
Bean, J. P., & Eaton, S. B. (2000). A psychological model of college student retention. In J. M. Braxton (Ed.), Reworking the student departure puzzle (pp.73-89). Nashville, TN: Vanderbilt University Press.
Bean, J. P., & Metzner, B. S. (1985). A conceptual model of nontraditional undergraduate student attrition. Review of Educational Research, 55(4), 485540.
Behnke, A. O., Piercy, K. W., & Diversi, M. (2004). Educational and occupational aspirations of Latino youth and their parents. Hispanic Journal of Behavioral Sciences, 26(1), 16-35.
Braxton, J. M., & Hirschy, A. (2005). Theoretical developments in the study of college student departure. In A. Seidman (Ed.), College student retention: Formula for student success (pp. 61-87). Westport, CT: Praeger Publishers.
Braxton, J. M., Hirschy, A. S., & McClendon, S. A. (2004). Toward understanding and reducing college student departure. ASHE-ERIC Higher Education Report, Vol. 30, No. 3. San Francisco: Jossey-Bass.
Braxton, J. M., Sullivan, A. S., & Johnson, R. M., Jr. (1997). Appraising Tintos theory of college student departure. In J. Smart (Ed.), Higher education: Handbook of theory and research (Vol. 12, pp. 107-164). New York, NY: Agathon.
Brint, S., & Karabel, J. (1989). The diverted dream: Community colleges and the promise of educational opportunity in America, 1900-1985. New York: Oxford University Press.
Buchmann, C., & DiPrete, T. A. (2006). The growing female advantage in college completion: The role of family background and academic achievement. American Sociological Review, 71(4), 515-541.
Byrne, B. M. (1998). Structural equation modeling with LISREL, PRELIS, and SIMPLIS: Basic concepts, applications, and programming. Mahwah, NJ: Lawrence Erlbaum.
Cabrera, A. F., Burkum, K. R., & La Nasa, S. M. (2005). Pathways to a four-year degree: Determinants of transfer and degree completion. In A. Seidman (Ed.), College student retention: A formula for success (pp. 155-214). ACE/Prager Series on Higher Education. Lanham, MD: Rowman and Littlefield Publishers.
Calcagno, J. C., & Long, B. T. (2008). The impact of postsecondary remediation using a regression discontinuity approach: Addressing endogenous sorting and noncompliance (NCPR Working Paper). New York: National Center for Postsecondary Research.
Carmines, G. C., & McIver, J. P. (1981). Analyzing models with unobserved variables. In G. W. Bohrnstedt & E. F. Borgatta (Eds.), Social measurement: Current issues (pp. 65-110). Beverly Hills, CA: Sage.
Carter, D. F. (1999). The impact of institutional choice and environments on African American and White students degree expectations. Research in Higher Education, 40(1), 1741.
Carter, D. F. (2001). A dream deferred? Examining the degree aspirations of African American and White college students. New York: Routledge Falmer.
Clark, B. R. (1960). The cooling-out function in higher education. American Journal of Sociology, 65(6), 569-576.
Cohen, A. M., & Brawer, F. B. (2008). The American community college (5th ed.). San Francisco: Jossey-Bass.
Coleman, J. C. (1988). Social capital in the creation of human capital. American Journal of Sociology, 94, 95-120.
Coleman, J. S., & Hoffer, T. (1987). Public and private high schools: The impact of communities. New York: Basic Books.
Corton, R., & Dronkers, J. (2006). School achievement of pupils from the low strata in public, private government-dependent and private government-independent schools: A cross-national test of Coleman-Hoffer thesis. Education Research and Evaluation, 12(2), 179-208.
Domina, T., Conley, A., & Farkas, G. (2011). The link between educational expectations and effort in the college-for-all era. Sociology of Education, 84(2), 93-112.
Dougherty, K. J., & Kienzl, G. S. (2006). Its not enough to get through the open door: Inequalities by social background in transfer from community colleges to four-year colleges. Teachers College Record, 108(3), 452487.
Duncan, O., Featherman, D., & Duncan, B. (1972). Socioeconomic background and achievement. New York: Seminar Press.
Dweck, C. S., & Elliott, E. (1983). Achievement motivation. In P. H. Mussen & E. M. Hetherington (Eds.), The handbook of child psychology (pp. 643-691). New York: Wiley.
Eagan, M. K., Jr., & Jaeger, A. J. (2009). Effects of exposure to part-time faculty on community college transfer. Research in Higher Education, 50(6), 168-188.
Eccles, J. S. (1983). Expectations, values and academic behaviors. In J. T. Spence (Ed.), Achievement and achievement motivations (pp. 75-146). San Francisco: Freeman.
Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53, 109130.
Enders, C. K. (2010). Applied missing data analysis. New York: Guilford Press.
Epps, E. G. (1995). Race, class, and educational opportunity: Trends in the sociology of education. Sociological Forum, 10(4), 593608.
Gonzalez, J. (2011, July 31). Va. community colleges dive headfirst into remedial-math redesign. The Chronicle of Higher Education. Retrieved from http://chronicle.com/article/Va-Community-Colleges-Dive/128430/
Graham, S., & Weiner, B. (1996). Theories and principles of motivation. In D. Berliner & R. Calfee (Eds.), Handbook of educational psychology (pp. 63-84). New York: Macmillan.
Hanson, S. L. (1994). Lost talent: Unrealized educational aspirations and expectations among U.S. youths. Sociology of Education, 67(3), 159-183.
Hauser, R. M., & Anderson, D. K. (1991). Post high-school plans and aspirations of Black and White high school seniors: 1976-86. Sociology of Education, 64(4), 263-277.
Heck, R. H., & Mahoe, R. (2004). An example of the impact of sample weights and centering on multilevel SEM models. Paper presented at the annual meeting of the American Educational Research Association, San Diego, CA.
Heck, R. H., & Thomas, S. L. (2000). An introduction to multilevel modeling techniques. Mahwah, NJ: Lawrence Erlbaum Associates.
Heller, D. E. (1997). Student price response in higher education: An update to Leslie and Brinkman. Journal of Higher Education, 68(6), 624-659.
Herzog, M. J. R., & Pittman, R. B. (1995). Home, family, and community: Ingredients in the rural education equation. Phi Delta Kappan, 77(2), 113-119.
Hirschman, C., Lee, J. C., & Emeka, A. S. (2003). Examining race and ethnic disparities in educational ambitions. The UW Beyond High School in Washington State Project. Seattle, Washington.
Hirschy, A. S., Bremer, C. D., & Castellano, M. (2011). Career and technical education student success in community colleges: A conceptual model. Community College Review, 39(3), 296-318.
Hoachlander, G., Sikora, A. C., Horn, L., & Carroll, C. D. (2003). Community college students: Goals, academic preparation, and outcomes (NCES 2003-164). Washington, DC: National Center for Education Statistics, U.S. Department of Education.
Hooper, D., Coughlan, J., & Mullen, M. R. (2008). Structural equation modelling: Guidelines for determining model fit. Electronic Journal of Business Research Methods, 6(1), 53-60.
Hossler, D., Schmit, J., & Vesper, N. (1999). Going to college. How social, economic, and educational factors influence the decisions students make. Baltimore: Johns Hopkins University Press.
Hossler, D., & Stage, F. K. (1992). Family and high school experience influences on the postsecondary educational plans of ninth-grade students. American Educational Research Journal, 29(2), 425-451.
Ingels, S. J., Pratt, D. J., Wilson, D., Burns, L. J., Currivan, D., Rogers, J. E., & Hubbard-Bednasz, S. (2007). Education Longitudinal Study of 2002: Base-year to second follow-up data file documentation (NCES 2008-347). U.S. Department of Education. Washington, DC: National Center for Education Statistics.
Jencks, C., Crouse, J., & Mueser, P. (1983). The Wisconsin model of status attainment: A national replication with improved measures of ability and aspiration. Sociology of Education, 56(1), 3-19.
Kalton, G. (1983). Introduction to survey sampling. Sage university paper series on quantitative applications in the social sciences, series no. 07-035. Beverly Hills, CA: Sage.
Kane, T. J., & Rouse, C. (1995). Labor market returns to two- and four-year college. American Economic Review, 85(3), 600-614.
Kanouse, D. E., Haggstrom, G. W., Blaschke, T. J., Kahan, J. P., Lisowski, W., & Morrison, P. A. (1980). Effects of postsecondary experiences on aspirations, attitudes, and self-conceptions. Santa Monica, CA: Rand Corporation.
Kao, G., & Thompson, J. S. (2003). Racial and ethnic stratification in educational achievement and attainment. Annual Review of Sociology, 29, 417-442.
Kao, G., & Tienda, M. (1995). Optimism and achievement: The educational performance of immigrant youth. Social Science Quarterly, 76(2), 1-19.
Kaplan, D. (2000). Structural equation modeling: Foundations and extensions. Thousand Oaks, CA: Sage
Karen, D. (2002). Changes in access to higher education in the United States: 1980-1992. Sociology of Education, 75(3), 191-210.
Kuh, G. D. (1999). A framework for understanding student affairs work. Journal of College Student Development, 40(5), 530-537.
Kupek, E. (2006). Beyond logistic regression: Structural equations modeling for binary variables and its application to investigating unobserved confounders. BMC Medical Research Methodology, 6(1), 13-23.
Laanan, F. S. (2003). Degree aspirations of two-year college students. Community College Journal of Research and Practice, 27(6), 495-518.
Leigh, D. E., & Gill, A. M. (2004). The effect of community colleges on changing students educational aspirations. Economics of Education Review, 23(1), 95-102.
Lipscomb, S. (2007). Secondary school extracurricular involvement and academic achievement: A fixed effects approach. Economics of Education Review, 26(4), 463-472.
Loeb, R. C., & Magee, P. M. (1992). Changes in attitudes and self-perceptions during the first two years of college. Journal of College Student Development, 33(4), 348-355.
Long, B. T., & Kurlaender, M. (2009). Do community colleges provide a viable pathway to a baccalaureate degree? Educational Evaluation and Policy Analysis, 31(1), 30-53.
Lowman, J. L., & Elliott, M. (2010). A multilevel model of educational expectations of secondary school students in the United States. Social Psychology of Education, 13(1), 77-110.
MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130-149.
Manski, C. F., & Wise, D. A. (1983). College choice in America. Cambridge, MA: Harvard University Press.
Marsh, H. W. (1991). Failure of high-ability high schools to deliver academic benefits commensurate with their students ability levels. American Educational Research Journal, 28(2), 445-480.
Mau, W. C. (1995). Educational planning and academic achievement of middle school students: A racial and cultural comparison. Journal of counseling and development, 73(5), 518-526.
Mau, W. C., & Bikos, L. H. (2000). Educational and vocational aspirations of minority and female students: A longitudinal study. Journal of Counseling and Development, 78(2), 186194.
McCormick, A. C. (1997). Changes in educational aspirations after high school: The role of postsecondary attendance and context. Paper presented at the Annual Meeting of the Association for the study of higher education. Albuquerque, New Mexico.
Melguizo, T., & Dowd, A.C. (2009). Baccalaureate success of transfers and rising four-year college juniors. Teachers College Record, 111(1), 55-89.
Melguizo, T., Kienzl, G. S., & Alfonso, M. (2011). Comparing the educational attainment of community college transfer students and four-year college rising juniors using propensity score matching methods. Journal of Higher Education, 82(3), 265-291.
Mello, Z. R. (2008). Gender variation in developmental trajectories of educational and occupational expectations and attainment from adolescence to adulthood. Developmental Psychology, 44(4), 1069-1080.
Morgan, S. L. (1998). Adolescent educational expectations: Rationalized, fantasized, or both? Rationality and Society, 10(2), 131-162.
Morgan, S. L. (2004). Methodologist as arbitrator: Five models for Black-White differences in the causal effect of expectations on attainment. Sociological Methods & Research 33(3), 3-53.
Mullin, C. M. (2011, October). The road ahead: A look at trends in the educational attainment of community college students (Policy Brief 2011-04PBL). Washington, DC: American Association of Community Colleges.
Museus, S. D., Harper, S. R., & Nichols, A. D. (2010). Racial differences in the formation of postsecondary educational expectations: A structural model. Teachers College Record, 112(3), 811-842.
Museus, S., & Hendel, D. D. (2005). Test scores, self-efficacy, and the educational plans of first-year college students. Higher Education in Review, 2, 63-88.
Muthén, L.K., & Muthén, B.O. (1998-2010). Mplus users guide. Sixth Edition. Los Angeles, CA: Muthén & Muthén.
Muthén, B. O., & Satorra, A. (1995). Complex sample data in structural equation modeling. In P. Marsden (Ed.), Sociological methodology (pp. 267316). Washington, DC: American Sociological Association.
National Center for Education Statistics [NCES] (2004). The condition of education 2004, indicator 18: Remediation and degree completion. Washington, DC: U.S. Department of Education.
Nora, A., Barlow, E., & Crisp, G. (2005). Student persistence and degree attainment beyond the first year of college: The need for research. In A. Seidman (Ed.), College student retention: Formula for student success (pp. 129-153). Westport, CT: Praeger Publishers.
Olsen, D., Kuh, G. D., Schilling, K. M., Schilling, K., Connolly, M., Simmons, A., & Vesper, N. (1998). Great expectations: What first-year students say they will do and what they actually do. Paper presented at the annual meeting of the Association for the Study of Higher Education, Miami, FL.
Pascarella, E. T., & Chapman, D. W. (1983). A multiinstitutional, path analytic validation of Tintos model of college withdrawal. American Educational Research Journal, 20(1), 60-75.
Pascarella, E. T., Pierson, C. T., Wolniak, G. C., & Terenzini, P. T. (2004). First generation college students: Additional evidence on college experiences and outcomes. Journal of Higher Education, 75(3), 249-284.
Pascarella, E. T., & Terenzini, P. T. (1991). How college affects students. San Francisco, CA: Jossey-Bass.
Pascarella, E. T., & Terenzini, P. T. (2005). How college affects students: Vol. 2. A third decade of research. San Francisco, CA: Jossey-Bass.
Peter, K., & Forrest Cataldi, E. (2005). The road less traveled? Students who enroll in multiple institutions (NCES 2005157). U.S. Department of Education, National Center for Education Statistics, Washington DC: U.S. Government Printing Office.
Qian, Z., & Blair, S. L. (1999). Racial/ethnic differences in educational aspirations of high school seniors. Sociological Perspectives, 42(4), 605-625.
Reason, R. D. (2009). An examintion of persistence research through the lens of a comphensive framework. Journal of College Student Development, 50(6), 659-682.
Remarks of President Barack Obama as Prepared for Delivery Address to Joint Sessions of Congress. (2009, February 24). Retrieved from http://www.whitehouse.gov/the_press_office/Remarks-of-President-Barack-Obama-Address-to-Joint-Session-of-Congress/
Reynolds, J., Stewart, M., MacDonald, R., & Sischo, L. (2006). Have adolescents become too ambitious? High school seniors educational and occupational plans, 1976 to 2000. Social Problems, 53(2), 186-206.
Rigsby, L. C., Stull, J. C., & Morse-Kelley, J. (1997). Determinants of student educational expectations and achievement: Race and gender differences. In R. D. Taylor & M. C. Wang (Eds.), Social and emotional adjustment and family relations in ethnic minority families (pp. 201224). Mahwah, NJ: Erlbaum.
Roksa, J. (2006). Does vocational focus of community colleges hinder students educational attainment? The Review of Higher Education, 29(4), 499526.
Rosenbaum, J. E. (2001). Beyond college for all: Career paths for the fogotten half. New York: Russell Sage Foundation.
Ryan, S. W., Seifert, T. A., Padgett, R. D., Park, S., & Umbach, P. D. (2011). Why do more women than men want to earn a four-year degree? Exploring the effects of gender, social origin, and social capital on educational expecations. Journal of Higher Education, 82(1), 1-32.
Schafer, J. L., & Graham, J. W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7(2), 147-177.
Schreiber, J. B., Stage, F. K., King, J., Nora, A., & Barlow, E. A. (2006). Reporting structural equation modeling and confirmatory factor analysis results: A review. Journal of Educational Research, 99(6), 323-337.
Schumacker, R. E. & Lomax, R.G. (2004). A beginners guide to structural equation modeling (2nd ed.). Mahwah, NJ: Lawrence Erlbaum Associates, Inc.
Sewell, W. H., Haller, A. O., & Ohlendorf, G. W. (1970). The educational and early occupational status attainment process: Replication and revision. American Sociological Review, 35(6), 1014-1027.
Sewell, W. H., Haller, A. O., & Portes, A. (1969). The educational and early occupational attainment process. American Sociological Review, 34(1), 82-92.
Sewell, W. H., Hauser, R. M., & Wolf, W. (1980). Sex, schooling and occupational status. American Journal of Sociology, 86(3), 551-583.
Skomsvold, P., Radford, A. W., & Berkner, L. (2011). Web tablesSix-year attainment, persistence, transfer, retention, and withdrawal rates of students who began postsecondary education in 2003-04 (NCES 2011152). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.
Steiger, J. H., & Lind, J. C. (1980). Statistically based tests for the number of factors. Paper presented at the meeting of the Psychometric Society, Iowa City, IA.
Swail, S. S., Redd, K. E., & Perna, L. W. (2003). Retianing minority students in higher education: A framework for success (ASHE-ERIC Higher Education Research Report Series, Vol. 30, No. 2). San Francisco, CA: Jossey-Bass.
Swail, W. S. (2000). Preparing Americas disadvantaged for college: Programs that increase college opportunity. In A. F. Cabrera & S. M. La Nasa (Eds.), Understanding the college choice of disadvantaged students (pp. 85-101). San Francisco: Jossey-Bass.
Teachman, J. D. (1987). Family background, educational resources and educational attainment. American Sociological Review, 52(4), 548-557.
Thomas, S. L., & Heck, R. H. (2001). Analysis of large-scale secondary data in higher education research: Potential perils associated with complex sampling designs. Research in Higher Education, 42(5), 517-540.
Tierney, W. G., & Venegas, K. M. (2006). Fictive kin and social capital: The role of peer groups in applying and paying for college. American Behavioral Scientist, 49(12), 16871702.
Tinto, V. (1975). Dropout from higher education: A theoretical synthesis of recent research. Review of Educational Research, 45(1), 89-125.
Tinto, V. (1993). Leaving college: Rethinking the causes and cures of student attrition (2nd ed.). Chicago, IL: University of Chicago Press.
Turley, R. N. L., Santos, M., & Ceja, C. (2007). Social origin and college opportunity expectations across cohorts. Social Science Research, 36(3), 1200-1218.
Ullman, J. B. (2001). Structural equation modeling. In B. G. Tabachnick & L. S. Fidell (Eds.), Using multivariate statistics (4th ed., pp. 653-771). Needham Heights, MA: Allyn & Bacon.
Vaughan, G. B. (2000). The community college story (2nd ed.). Washington, DC: Community College Press.
Wang , X. (2009). Baccalaureate attainment and college persistence of community college transfer students at four-year institutions. Research in Higher Education, 50(6), 570-588.
Wang, X. (2012). Stability of educational expecations among baccalaurate aspirants beginning at commmunity colleges. Community Colllege Review, 40(4), 1-20.
Wang, X. (In press). Factors contributing to the upward transfer of baccalaureate aspirants beginning at community colleges. Journal of Higher Education.
Wells, R. S., Seifert, T. A., Padgett, R. D., Park, S., & Umbach, P. D. (2011). Why do more women than men want to earn a four-year degree? Exploring the effects of gender, social origin, and social capital on educational expectations. Journal of Higher Education, 82(1), 1-32.
Wheaton, B., Muthén, B., Alwin, D., & Summers, G. (1977). Assessing reliability and stability in panel models. In D. R. Heise (Ed.), Sociological Methodology 1977 (pp. 84-136). San Francisco: Jossey-Bass.