Understanding Postsecondary Education Enrollment of First-Generation Students From a Social Cognitive Perspective

Abstract

Data from the High School Longitudinal Study of 2009 were used to describe and compare postsecondary education enrollment patterns of first- and continuing-generation students. Social cognitive career theory was used to explain the processes of educational and career pursuit and attainment, as well as personal, behavioral, and contextual/environmental factors influencing these processes. Postsecondary educational self-efficacy (i.e., a belief or confidence in future educational success) had a significant positive influence on establishing higher postsecondary educational goals for all adolescents. Postsecondary educational self-efficacy and goals, together, also had a substantial positive influence on postsecondary enrollment patterns of both groups. Self-efficacy exerted a stronger total effect for first-generation students. Contextual supports and barriers directly influenced students’ goals but played different roles depending on generational status.

Keywords

first-generation students high school longitudinal study postsecondary education enrollment social cognitive career theory

Pursuit and attainment of postsecondary education have become increasingly important in determining one’s career development, economic well-being, and job satisfaction. From personal earnings to employment rates to job commitment, college graduates outperform peers with lesser education attainment. The value accorded a college degree has also been increasing as evidenced by rising disparities in earnings and employment rates of high school and college graduates. The benefits afforded to individuals by postsecondary education have contributed to substantial increases in U.S. college enrollment over the past several decades (Pew Research Center, 2014). In 2017, approximately 67% of high school graduates enrolled in some form of postsecondary education immediately after high school graduation, including 44% at 4-year universities and 23% in 2-year community college institutions (National Center for Education Statistics, 2018). In addition, many more individuals enter college later in life, resulting in roughly three fourths of all Americans eventually enrolling in a college program at some point in their lives (Long, 2017).

College enrollment rates are promising, but gaps in participation exist between first- and continuing-generation students. Data from the Education Longitudinal Study of 2002 (ELS:2002) showed that first-generation college students (FGCSs) accounted for only 24% of college attendees, with most of this group enrolled in 2-year community college programs. FGCSs refer to those individuals whose parents have had no postsecondary educational experience. Conversely, continuing-generation college students (CGCSs) have had at least one parent with some postsecondary educational experience (Redford & Hoyer, 2017). Students who have not yet graduated from high school and whose parents have had no formal education beyond high school are also referred to as prospective FGCSs (Gibbons & Borders, 2010b). In this study, we were interested in prospective FGCSs and refer to them as first-generation students.

It is important to study first-generation students as they are often disadvantaged when accessing postsecondary education opportunities because of demographic or educational characteristics that differ from continuing-generation students. For example, first-generation students are more likely to be of racial/ethnic minority status (i.e., Hispanic or Black), come from a low-income family, and have limited knowledge about college and college-going plans (Falcon, 2015; Redford & Hoyer, 2017). Each of these characteristics is independently associated with lower rates of college enrollment (Engle, 2007). First-generation students are also more likely to perceive limited support and receive limited guidance from their families due, in part, to parents’ lack of experience with college attendance and the college application process (Gibbons & Borders, 2010b; Moschetti & Hudley, 2015). These students often face social and academic barriers when considering college attendance such as poor academic preparation, lack of role models, and inadequate financial support (Chen, 2016; Falcon, 2015). And, once enrolled in college, they are less likely to persist to graduation (Kena et al., 2015; Lohfink & Paulsen, 2005).

Time during high school represents a vital transitional period from adolescence to adult life where future goals and plans to achieve those goals are identified and begin to coalesce. Students more involved in planning their educational and career futures are also more likely to be engaged in school, succeed academically, and pursue postsecondary education (Plasman, 2018). Providing students with resources can support the process of establishing future goals, which can inform post-school planning and also enhance their high school experience (Hooker & Brand, 2010). Most research, to date, has focused on FGCSs and their academic or career development experiences after they arrive at college, mostly 4-year university settings (e.g., Garriott et al., 2015; Ma & Shea, 2019). Only recently have studies begun to examine the period of preparation during high school and time before actually arriving at college (e.g., Gibbons & Borders, 2010b). Given noted differences between FGCSs and CGCSs, this study examined the process of first-generation students’ pursuit of postsecondary education and the role of contextual supports and barriers in their transition from high school to postsecondary education. Results might inform researchers and educators on how to better support first-generation students in early planning and preparation for postsecondary education.

Theoretical Framework

Social cognitive career theory (SCCT; Lent, 2005; Lent et al., 1994, 2000) is directly applicable to a better understanding of first-generation students by providing a framework that explains academic and career pursuits while acknowledging the influence of background and contextual factors (Garriott et al., 2015; Gibbons & Borders, 2010b). SCCT was derived from Bandura’s (1986) social cognitive theory, which emphasizes the role of self-regulation in guiding human motivation and behavior. Self-regulation refers to processes where individuals control, evaluate, and reflect on their learning, behavior, and goal achievement (Schmitz & Wiese, 2006; Zimmerman, 2002). SCCT integrates self-regulatory processes with personal, behavioral, and contextual factors to understand how interests are developed, decisions are made, and performance is attained.

SCCT explains three intricately linked tenets affecting individuals’ academic and career intentions and behaviors: self-efficacy beliefs, outcome expectations, and personal goals (Lent et al., 1994). Self-efficacy refers to individuals’ beliefs about their abilities to attain a goal and complete specific tasks. Outcome expectations refer to individuals’ beliefs about the likely outcomes (imagined consequences) of performing particular behaviors and the relative value of these outcomes. Personal goals, often expressed as plans or aspirations, are an individual’s determination to engage in a particular activity or affect a particular outcome. By setting goals, individuals organize, guide, evaluate, and sustain their behaviors toward desired outcomes.

The SCCT choice model posits that self-efficacy, along with outcome expectations, gives rise to career-related interests, which, in turn, foster career choice goals. Goals motivate choice actions (or efforts to implement goals) that lead to performance success or failure (Lent et al., 1994). Self-efficacy and outcome expectations may also affect choice goals and actions directly via interests by helping people interpret, organize, and apply their skills. Self-efficacy exerts a direct effect on individuals’ performance attainment, as well. Genetic predispositions (e.g., age, gender) and contextual factors (e.g., supports and barriers) shape individuals’ self-efficacy and may directly or indirectly influence personal goals via self-efficacy. Because SCCT constructs are domain- or process-specific (e.g., self-efficacy of math abilities, self-efficacy of ability to conduct a career search), we focused our attention on self-efficacy, outcome expectations, and goals in terms of postsecondary education enrollment (e.g., postsecondary educational self-efficacy).

Postsecondary Educational Self-Efficacy and Outcome Expectations

Postsecondary educational self-efficacy refers to individual beliefs about the ability to enroll and be successful in college after high school. Because the goal of enrolling in college is particularly specific, few studies have examined this construct. However, extensive research has examined self-efficacy pertaining to educational-related goals that are more general. For example, academic self-efficacy (i.e., beliefs about abilities to succeed in academic tasks and pursuits) has been found to influence academic goal setting and the amount of effort spent on task performance and perseverance and, as a result, influence academic achievement and performance (Honicke & Broadbent, 2016). A similar construct is college-going self-efficacy that refers to individuals’ beliefs about their abilities to attend and persist in college. Attending college involves a number of tasks such as paying for college tuition, getting accepted to a college, college choice, and college planning. Persisting in college involves tasks such as maintaining good grades, taking care of responsibilities, making friends, and receiving a degree (Gibbons & Borders, 2010a). First-generation students usually report lower levels of college-going self-efficacy than continuing-generation peers. Regardless of domain or process, the role that self-efficacy plays in motivation is the primary focus of SCCT; individuals with high levels of self-efficacy are more likely to successfully cope with perceived barriers and persevere amidst challenges (Bandura et al., 2001).

Postsecondary Educational Goals

Goal setting is an essential feature of self-regulated learning and improves academic performance. Goals serve as the standard against which performance can be evaluated (Morisano et al., 2010). In addition, goal attainment generates a feedback loop that modifies levels of self-efficacy, which in turn enhances or prohibits the process of mobilizing cognitive and motivational resources to commit to the goal and facilitate subsequent achievement (Dent & Koenka, 2016). In fact, underrepresented students with clear and realistic goals in secondary school are more likely to have plans to meet those goals (Knaggs et al., 2015). Postsecondary educational goals (i.e., goals of college enrollment) were also associated with higher possibilities of college attendance (Wei et al., 2016). Other benefits of goals include higher levels of enthusiasm, greater energy, and lower levels of anxiety, disappointment, or frustration (Morisano et al., 2010). First-generation students are likely to (a) establish lower goals than their continuing-generation peers and (b) expect to enter a community college instead of a 4-year university (Gibbons & Borders, 2010b; Redford & Hoyer, 2017). This study sought evidence of the influence of postsecondary educational goals during high school on the college enrollment of first-generation students.

Supports and Barriers of First-Generation Students to Access College

Informational and emotional supports are critical to academic and career development and can influence decisions regarding college attendance (Bell et al., 2009; Moschetti & Hudley, 2015). Providing students with information about college and careers enhances the relevance of their high school experience, increases school engagement, and informs them of the necessary steps to prepare for postsecondary education and future careers (Gibbons et al., 2006; Hooker & Brand, 2010). Knowledge about college may include practical information about how to plan for and enroll in college, such as academic requirements, college application, college costs, and financial aid (Bell et al., 2009); it may also include applied learning opportunities and exposure to the world of postsecondary education, such as college-level coursework and college campus tours (Hooker & Brand, 2010). Information about and exposure to different careers during high school can help students decide on a career and understand educational requirements to obtain that career (Gibbons et al., 2006). Emotional support and encouragement from students’ close networks (e.g., parents and friends) influence their social behaviors as well as academic aspirations and achievement (Holland, 2011; Leonard, 2013).

Bell et al. (2009) reported that high school students mostly relied on family and friends as sources of support when obtaining college- and career-related information; ninth graders almost exclusively depended on these two sources, while 11th graders also gathered information from teachers, counselors, and career centers. Family always plays a prominent role in students’ college enrollment (King, 2012; Moschetti & Hudley, 2015). However, a lack of familiarity with college-related expectations can contribute to the inability of parents of first-generation students to help their child adequately prepare for college (Falcon, 2015). First-generation students often recognize their lack of information about college and career opportunities but have little idea of where to access such information. As a result, first-generation students tend to rely on other sources (e.g., friends, teachers, and school counselors) for guidance and information (Gibbons et al., 2006).

Socioeconomic status and financial considerations are the main barriers that prevent students from continuing their education after high school (Jerrim et al., 2015; Perna, 2010). First-generation students, especially, perceive heavier financial burdens attached to college enrollment. These perceptions are often reinforced by their family’s low-income status (Redford & Hoyer, 2017). Many FGCSs have part-time jobs and work more hours per week to support their college expenses than continuing-generation students (Gibbons & Shoffner, 2004). While taking out greater numbers and amounts of student loans in their first year of college, many first-generation students leave college without any credentials due to financial challenges (Furquim et al., 2017). First-generation students also perceive barriers related to family issues, racial/ethnic discrimination, lack of college-educated role models, lack of college-planning guidance, and lack of preparation and/or desire in terms of college-going (Gibbons & Borders, 2010a).

The Current Study

Two research questions guided our analysis: (a) What are the relationships among postsecondary educational self-efficacy, contextual supports and barriers, postsecondary educational goals, and postsecondary education enrollment? and (b) How do these relationships vary between first- and continuing-generation students? Figure 1 depicts the simplified SCCT choice model that framed our analysis and also indicates the specific paths that were tested. We expected to find that postsecondary self-efficacy would exert a direct influence on postsecondary goals (1) and postsecondary enrollment (2). Postsecondary goals were hypothesized to exert a direct effect on postsecondary education enrollment (3). The role of contextual supports and barriers was also examined with expectations that both supports and barriers had direct effects on postsecondary educational goals (4,5) and indirect effects on postsecondary goals via self-efficacy (6,7). Finally, separate models were constructed for first- and continuing-generation students. We expected higher contextual barriers and lower contextual supports, as well as lower postsecondary goals and enrollment rates, for first-generation students compared to continuing-generation students.

Figure 1.

Theoretical model of the study.

Method

Data and Sample

This study used nationally representative longitudinal data from the High School Longitudinal Study of 2009 (HSLS:2009). HSLS:2009 was gathered from a cohort of ninth-grade high school students beginning in fall 2009 (base year). Data collection from the first follow-up began in spring 2012, when most students were in 11th grade. Student updates and transcript data were also collected in fall 2013 and spring 2014, when most students had graduated from high school. Second follow-up data were collected during the 2016–2017 academic year, when most students had been out of high school for approximately 3 years (Ingels et al., 2015).

Our sample included students who had attended a public high school, participated in the first three waves of data collection (i.e., base year, first follow-up, and 2013–2014 updates), and had at least one parent participate in the base-year parent survey (n = 10,121). The sample included 5,050 (49.9%) boys and 5,071 (50.1%) girls. White students (n = 5,799; 57.3%) constituted a majority of the sample. Hispanic (n = 1,539; 15.2%), Black (n = 956; 9.4%), Asian (n = 813; 8.0%), multiracial students (n = 904; 8.9%), and students in the “Other” race category (n = 110; 1.1%) constituted the remaining students. The Other race category included American Indian, Alaska Native, Native Hawaiian, and Pacific Islander.

Measures

Table 1 lists the name, description, and HSLS:2009 label of all variables used in this study. The endogenous variable, postsecondary education enrollment, was measured by the type of educational program, if any, students were enrolled in during the fall 2013 academic semester. Postsecondary educational enrollment (a nominal variable) was derived from an HSLS:2009 survey item (in 2013) that asked all students enrolled in some type of postsecondary education to indicate the type of program. The original response options were 1 = bachelor’s degree program, 2 = associate’s degree program, 3 = certificate or diploma program, 4 = no specific program, but taking courses, 5 = other, and 6 = don’t know. We combined response Options 2 and 3 (programs lasting 2 years or less) and Options 4, 5, and 6 (possible involvement but disengaged). Students who legitimately skipped this item were viewed as not being enrolled in any college programs or classes and, thus, coded as having no college.

Table 1.

List of Variables in the Study.

Variable Name	Description	HSLS:2009 Label
Endogenous variable
Postsecondary education enrollment	Program enrollment in fall 2013: 1 = bachelor’s, 2 = certificate/associate’s, 3 = taking postsecondary classes but unsure of program, 4 = no college	Recoded from: S3PROGLEVEL
Mediating variables
Postsecondary educational goals	Enrollment plans for fall 2013: 1 = no college, 2 = plans to go to college but not sure what type of program, 3 = certificate/associate’s degree, 4 = bachelor’s degree	Recoded from: S2DEGREE2013
Postsecondary educational self-efficacy	Student thinks he or she has ability to complete a Bachelor’s degree: 1 = definitely not, 2 = probably not, 3 = probably, 4 = definitely	S1ABILITYBA
Exogenous variables
Support
Parent support	Student has talked with parents about college, careers, or personal problems (continuous)	Computed from: S1MOM(DAD)TALKCLG S1MOM(DAD)TALKJOB S1MOM(DAD)TALKPRB
Friend support	Student has talked with friends about college, careers, or personal problems (continuous)	Computed from: S1FRNDTLKCLG S1FRNDTLKJOB S1FRNDTLKPRB
Teacher support	Student has talked with teachers about college, careers, or personal problems (continuous)	Computed from: S1TCHTALKCLG S1TCHTALKJOB S1TCHTALKPRB
Counselor support	Student has talked with counselors about college, careers, or personal problems (continuous)	Computed from: S1CNSTALKCLG S1CNSTALKJOB S1CNSTALKPRB
Barriers
Lack of support	Student has talked with no one about college, careers, or personal problems: 0 = false, 1 = true	Recoded from: S1NOTALKCLG S1NOTALKJOB S1NOTALKPRB
Financial concern	Student thinks family cannot afford to pay for college: 1 = strongly disagree, 2 = disagree, 3 = agree, 4 = strongly agree	Recoded from: S1AFFORD
Demographic variable
Generational status	At least one of the student’s parents had some college education: 0 = false, 1 = true	Recoded from: X1PAREDU X1PAR1EDU X1PAR2EDU P1STARTDEG1 P1STARTDEG2

Note. The percentage of missing values was 0.7% (n = 69) for postsecondary education enrollment; 0.5% (n = 48) for postsecondary educational goals; 1.9% (n = 188) for postsecondary educational self-efficacy; 3.2% (n = 325) for parent support; 3.3% (n = 329) for friend, teacher, and counselor support; 1.4% (n = 146) for lack of support; 2.1% (n = 213) for financial concern; and 0.0% for generational status.

The focal mediating variable was postsecondary educational goals. This nominal variable reflected the same four outcomes used to indicate postsecondary educational enrollment status and ranged from no college to pursuing a bachelor’s degree. Goals were derived from an HSLS:2009 first follow-up survey item (in 2012) that asked students to indicate the type of educational program, if any, they planned to pursue after high school. Original four response options were 1 = certificate or diploma program, 2 = associate’s degree program, 3 = bachelor’s degree program, and 4 = haven’t thought about this yet. We recoded responses to combine Options 1 and 2 (programs lasting 2 years or less) and recoded Option 4 as unsure. Because this item was administered to students who indicated that they planned to attend a postsecondary institution in the fall of 2013, students who legitimately skipped this item were coded as not planning to go to college. A second mediating variable, postsecondary educational self-efficacy (a nominal variable), was measured using an HSLS:2009 base-year survey item that asked students to indicate their level of confidence in completing a bachelor’s degree. This variable was also used to test the mediation effect between supports-barriers and postsecondary educational goals.

Exogenous variables included supports and barriers. Supports for pursuing postsecondary education were measured using items from the base-year survey and included four sources: parents, friends, teachers, and counselors. For each source, students indicated whether or not they had talked with the various sources of support about college, career, or personal problems since the last school year (2008–2009). Student responses indicated the presence or absence of support but did not indicate its frequency or intensity nor the students’ perception of its impact. The use of this response structure was determined by the availability of HSLS:2009 data and limited our analysis options to some degree. However, these variables were still useful to us in determining the impact of support factors on postsecondary educational self-efficacy, goals, and enrollment when they were present or absent. Latent continuous factors labeling parent, friend, teacher, and counselor support, respectively, were computed using confirmatory factor analysis (CFA) based on those survey items (see Table 1).

Barriers against the pursuit of postsecondary education were measured from two perspectives based on items found in the base-year survey: (a) lack of supporting personnel to talk about college, career, and/or personal problems (a binary variable) and (b) student has financial concerns about attending college (a nominal variable). Lack of support was coded as true when a student had talked with no one about any college, career, or personal problems. Financial concern was reverse coded from an item that asked students’ perceptions regarding their family’s financial ability to pay for their college.

Lastly, generational status (a binary variable) was determined by (1) HSLS:2009 composite variables indicating parents’ highest degree of education and (2) items from the base-year parent survey that asked parents about the highest degree they had started but did not complete. The generational status was coded as 1 (i.e., first-generation) if neither parent had any postsecondary educational experience and coded as 0 if at least one parent had some postsecondary experience (i.e., continuing generation).

Data Analysis

Missing values were examined and handled to diminish potential bias. The percentage of missingness for each variable was less than 5.0% (see Table 1 footnote). Missingness below 5% is considered negligible and can be viewed as missing at random (Jakobsen et al., 2017). Maximum likelihood estimation and multiple imputations are the best methods for handling missing data when missing are at random. However, when the sample size is large (n > 1,000) and the percentage of missingness is low (<5%), listwise deletion is recommended over maximum likelihood or multiple imputations because it is simple and computation-friendly and does not add another layer of measurement error (Cheema, 2014). As a result, a total of 646 (6.4%) cases with missing values were deleted from further analysis. Thus, our final sample size was 9,475.

Analyses were conducted using Mplus Version 7.4 with appropriate weighting variables to accommodate the complex survey design of the HSLS:2009. Descriptive statistics provided demographic characteristics and postsecondary education enrollment patterns of the sample. χ² tests of independence were conducted to examine associations between generational status and the other study variables. CFA was used to examine the proposed measurement model that specified latent factors (i.e., support from parents, friends, teachers, and counselors) and corresponding indicator items. The weighted least square with adjustment in mean and variance (WLSMV) estimator was used because all indicator items were binary. Fit statistics of the measurement model and standardized factor loadings were examined to determine validity. Fit indices with WLSMV estimator included root mean square error of approximation (RMSEA), comparative fit index (CFI), and Tucker–Lewis Index (TLI).

Structural equation modeling (SEM) with the full sample and two subgroups (first- and continuing-generation students) were conducted to answer the first research question. SEM is a statistical technique that is often used to analyze complex relationships between observed and/or latent variables (Hox & Bechger, 1998). Hypothesized Paths 1–3 were tested by examining path coefficients from postsecondary self-efficacy to goals and from goals to postsecondary enrollment as well as the indirect effect from postsecondary self-efficacy to enrollment via goals. If all were significant, a mediation effect existed for goals. Hypothesized Paths 4–7 were tested by examining the goodness of fit of three alternative models. Model 1 included no mediation (Paths 1–5), only examining the direct effects of contextual supports and barriers on postsecondary educational goals (see Figure 1). Model 2 is a full mediation model (Paths 1–3, 6, 7) that only represents the indirect effects of contextual supports and barriers to goals via self-efficacy. Model 3 (partial mediation, Paths 1–7) represents the direct effects of supports and barriers on goals, as well as indirect effects via self-efficacy. The default estimator in Mplus is the maximum likelihood (ML). Fit indices with ML estimator included χ², Akaike’s information criteria, Bayesian information criteria, and sample size adjusted BIC, which were used to determine the goodness of fit of different models.

To answer the second research question, differences in paths by generational status were examined using the best fit model obtained from Research Question 1. Measurement invariance was hypothesized to be nonexisting between two subgroups, which was examined by the multiple group SEM analysis. For both research questions, direct and indirect effects were estimated and tested for statistical significance (α = .05). Because the endogenous variable was nominal, odds ratios (ORs) were calculated by an exponential function of effect estimates, explaining how much more likely it was for an outcome of the endogenous variable when a change occurred to an exogenous variable.

Results

Descriptive Statistics

Almost three fourths (72.6%) of the public school student in our sample reported enrollment in some type of postsecondary education in the fall of 2013 (following graduation), including 39% in 4-year bachelor’s degree programs, 20% in 2-year certificate/associate degree programs, and 14% enrolled in some level of postsecondary courses (weighted percentages). Postsecondary enrollment rates were 77% for women and 68% for men. Asian students had the highest postsecondary enrollment rate (92%) among all racial/ethnic minority groups, followed by White students (75%). About 70% of multiracial and Black students enrolled in some form of postsecondary education. Hispanics and students in the Other category reported the lowest postsecondary enrollment rate at 67%.

χ² tests of independence show that the generational status had significant associations with all the other study variables except gender, indicating first- and continuing-generation group differences. Table 2 presents demographic and educational characteristics and postsecondary education enrollment patterns of sample participants in fall 2013 (first academic semester after traditional spring high school graduation), disaggregated by generational status. Unweighted totals represent students included the HSLS:2009 sample, while weighted numbers indicate projected population totals. Overall, 58.1% of first-generation students enrolled in some type of postsecondary education, compared with 81.0% for continuing-generation students. Differences were detected in all areas except certificate/associate degree program enrollment. First-generation students were 2.2 times more likely to not enroll in any type of postsecondary programs, 1.6 times more likely to enroll in college classes, and 57% less likely to enroll in a 4-year college program than continuing-generation students were.

Table 2.

Characteristics of First- and Continuing-Generation Students, Unweighted and Weighted.

Variables	First-Generation		Continuing-Generation
Variables	N (%)	Weighted N (%)	N (%)	Weighted N (%)
Postsecondary education enrollment
Bachelor’s	703 (23.2)	221,867 (21.3)	3,487 (54.1)	880,740 (49.3)
Certificate/associate	576 (19.0)	201,033 (19.3)	1,171 (18.2)	366,673 (20.5)
College classes	492 (16.3)	182,563 (17.5)	661 (10.2)	199,864 (11.2)
No postsecondary	1,255 (41.5)	436,102 (41.9)	1,130 (17.5)	338,823 (19.0)
Gender
Men	1,463 (48.3)	520,117 (49.9)	3,212 (49.8)	898,156 (50.3)
Women	1,563 (51.7)	521,447 (50.1)	3,237 (50.2)	887,944 (49.7)
Race/ethnicity
Hispanic	752 (24.9)	344,228 (33.0)	670 (10.4)	263,245 (14.7)
White	1,498 (49.5)	424,265 (40.7)	3,981 (61.7)	1,091,338 (61.1)
Black	329 (10.9)	165,807 (15.9)	524 (8.1)	183,771 (10.3)
Asian	159 (5.3)	22,152 (2.1)	614 (9.5)	70,454 (3.9)
Multirace	251 (8.3)	69,052 (6.6)	595 (9.2)	159,758 (8.9)
Other	37 (1.2)	16,061 (1.5)	65 (1.0)	17,533 (1.0)
Socioeconomic status
Quintile 1 (lowest)	1,417 (46.8)	504,074 (48.4)	207 (3.2)	72,294 (4.0)
Quintile 2	971 (32.1)	340,903 (32.7)	750 (11.6)	264,204 (14.8)
Quintile 3	494 (16.3)	153,066 (14.7)	1,229 (19.1)	369,572 (20.7)
Quintile 4	137 (4.5)	40,729 (3.9)	1,704 (26.4)	486,330 (27.2)
Quintile 5 (highest)	7 (0.2)	2,792 (0.3)	2,559 (39.7)	593,699 (33.2)
Self-efficacy
Definitely not	65 (2.1)	20,138 (1.9)	45 (0.7)	15,966 (0.9)
Probably not	287 (9.5)	101,027 (9.7)	229 (3.6)	79,313 (4.4)
Probably	1,497 (49.5)	496,826 (47.7)	2,449 (38.0)	724,743 (40.6)
Definitely	1,177 (38.9)	423,572 (40.7)	3,726 (57.8)	966,077 (54.1)
Educational goals
No college	572 (18.9)	192,999 (18.5)	590 (9.1)	181,910 (10.2)
College classes	873 (28.8)	308,386 (29.6)	1,653 (25.6)	502,215 (28.1)
Certificate/associate	764 (25.2)	267,647 (25.7)	1,045 (16.2)	298,316 (16.7)
Bachelor’s	817 (27.0)	272,533 (26.2)	3,161 (49.0)	803,659 (45.0)
Totals	3,026 (31.9)	1,041,564 (36.8)	6,449 (68.1)	1,786,100 (63.2)

Note. Percentages are in parentheses and may not add up to 100 due to rounding.

First-generation students were 2.2 times more likely to identify as Hispanic and 1.5 times more likely to report Black minority race/ethnic status. Socioeconomic status (SES) presented distinct differences for first- and continuing-generation students. Four fifths (81.1%) of first-generation students reported being in one of the two lowest SES quintiles. In contrast, three fifths (60.4%) of continuing-generation students were grouped into one of the two highest SES quintiles. First-generation students were 2.2 times more likely than continuing-generation students to hold negative self-efficacy beliefs about completing a bachelor’s degree. First-generation students were almost twice as likely as continuing-generation students to hold no postsecondary educational goals.

CFA

CFA, based on the full sample and two subgroups (first- and continuing-generation students), indicated that the measurement model fit the data well (see Figure 2 for path diagram and factor loadings of the measurement model for full sample). RMSEA values were .04/.03/.04 for the full sample, first-, and continuing-generation students, respectively, with corresponding 90% confidence intervals ([.038, .042], [.030, .037], [.042, .046]) indicating a good fit (Hu & Bentler, 1999). CFI values were .95/.95/.94, and TLI values were .93/.95/.93, for the three models also suggesting good data fit. All standardized factor loadings were above .45 and statistically significant at p < .001, indicating that the measurement model possessed good convergent validity (Kline, 2011). Therefore, we concluded that each measure of contextual supports was valid and appropriate for subsequent analysis.

Figure 2.

Confirmatory factor analysis model of contextual supports.

Analysis for Research Question 1

The first research question examined relationships among postsecondary educational self-efficacy, contextual supports and barriers, postsecondary educational goals, and postsecondary education enrollment. Path coefficients and the indirect effect from self-efficacy to enrollment via goals were significant, which supports the Hypothesized Paths 1–3. Every one-level increase in self-efficacy reported by students in the ninth grade resulted in 2.14 times greater odds of setting higher goals in 11th grade. Similarly, higher goals in 11th grade resulted in greater odds of enrolling in a bachelor’s program (OR = 2.62), a certificate/associate program (OR = 1.59), or taking postsecondary classes (OR = 1.43) after high school. A one-level increase in self-efficacy in total increased the odds of student enrollment in a bachelor’s program (OR = 2.51), a certificate/associate program (OR = 1.40), or of taking postsecondary classes (OR = 1.29).

Model 1 (no mediation) produced the best fit index values among the three models (no mediation, full mediation, and partial mediation), which was true for the full sample and each subgroup. This result supports the Hypothesized Paths 4 and 5 (not 6 or 7), meaning that contextual supports (from parents, friends, teachers, and counselors) and barriers (i.e., lack of support and financial concern) yielded only direct effects on goals. This outcome was consistent for all students regardless of generational status. Table 3 presents the fit indices of three alternative models calculated for the full sample, first-, and continuing-generation students. For all students, consulting with parents (OR = 1.17) and friends (OR = 1.23) about college, career, and personal problems were small, but significant positive sources of support that resulted in higher goals. Lack of support (OR = 0.56) and financial concerns of attending college (OR = .87) were viewed as barriers and negatively affected the extent of goals.

Table 3.

Model Fit Indices (No Mediation, Partial Mediation, Full Mediation) of Postsecondary Educational Enrollment for Full Sample and First-Generation and Continuing-Generation Student Subgroups.

Models	Log Likelihood	Parameters	AIC	BIC	ssBIC
Full sample (n = 9,475)
Model 1: No mediation	−86,180.55	55	172,471.10	172,864.71	172,689.92
Model 2: Full mediation	−94,741.37	58	189,598.75	190,013.82	189,829.50
Model 3: Partial mediation	−94,592.04	64	189,312.08	189,770.09	189,566.71
First-generation students (n = 3,026)
Model 1: No mediation	−28,221.76	55	56,553.52	56,884.35	56,709.59
Model 2: Full mediation	−31,210.78	58	62,537.55	62,886.42	62,702.13
Model 3: Partial mediation	−31,175.60	64	62,479.20	62,864.16	62,660.81
Continuing-generation students (n = 6,449)
Model 1: No mediation	−57,057.35	55	114,224.70	114,597.15	114,422.37
Model 2: Full mediation	−62,502.44	58	125,120.88	125,513.64	125,329.33
Model 3: Partial mediation	−62,405.39	64	124,938.78	125,372.17	125,168.79

Note. AIC = Akaike’s information criteria; BIC = Bayesian information criteria; ssBIC = sample size adjusted BIC.

Analysis for Research Question 2

The second research question sought to determine whether relationships identified through reported analysis varied by student’s generational status. Results from the multiple group SEM analysis reveal a worse model fit when constraining factor loadings to be equal for two subgroups. Therefore, the identified relationships were seen as noninvariant for first- and continuing-generation students. Figure 3 displays the path coefficients of Model 1 for the full sample and two subgroups (significant coefficient estimates are noted). For first-generation students, every one-level increase in self-efficacy reported in ninth grade resulted in 2.00 times greater odds of setting higher goals in 11th grade. Similar to full model results, higher goals in 11th grade resulted in greater odds of enrolling in a bachelor’s program (OR = 2.55), a certificate/associate program (OR = 1.53), or taking postsecondary classes (OR = 1.35) after high school. A one-level increase in self-efficacy in total increased the odds of student enrollment in a bachelor’s program (OR = 2.68), a certificate/associate program (OR = 1.36), or of taking postsecondary classes (OR = 1.32). For these students, consulting with parents (OR = 1.20) and friends (OR = 1.16) about college, career, and personal problems were significant, albeit modest, sources of support resulting in higher goals. The selected barrier factors were found to have negative effects on college enrollment; however, neither was statistically significant.

Figure 3.

Parameter estimates of the best fit model, Model 1: No mediation. Note. Path coefficients are presented in the order of full sample, first-generation students, and continuing-generation students. Estimates are in gray if path was not significant at the .05 level. [#1] = enrolled in a bachelor’s degree program compared to no college; [#2] = enrolled in a certificate or associate’s degree program compared to no college; [#3] = taking postsecondary classes but unsure of program compared to no college.

For continuing-generation students, every one-level increase in self-efficacy reported in ninth grade resulted in 2.17 times greater odds of setting higher goals in 11th grade. Setting higher goals in 11th grade resulted in greater odds of enrolling in a bachelor’s program (OR = 2.62), a certificate/associate program (OR = 1.62), or taking postsecondary classes (OR = 1.52) after high school. A one-level increase in self-efficacy in total increased the odds of student enrollment in a bachelor’s program (OR = 2.19), a certificate/associate program (OR = 1.30), or of taking postsecondary classes (OR = 1.21). The only significant, albeit modest, source of support resulting in higher goals for continuing-generation students was consulting with parents about college, career, and personal problems (OR = 1.22). Financial concern was the only significant, albeit modest, barrier to college enrollment, that is, the greater the belief that college was not affordable, the less likely students were to set higher goals (OR = .81).

Summary

First- and continuing-generation students were different in terms of race/ethnicity, SES, and levels of educational self-efficacy and goals. Regardless of status, postsecondary educational self-efficacy reported in ninth grade yielded significant and substantial positive influence on setting higher levels of postsecondary educational goals in 11th grade, and self-efficacy and goals together resulted in greater odds of postsecondary education enrollment after high school. Selected contextual supports and barriers yielded only direct effects on goals. Different sets of support and barrier factors were significant for first- and continuing-generation students yet the influence of those factors was modest.

Discussion

We examined public high school students’ pursuit of and navigation through postsecondary education options using a nationally representative data set in the United States. Results support and extend the explanations of postsecondary educational enrollment posited by SCCT (Lent et al., 2000) to better understand selected influences on the enrollment of first- and continuing-generation students before arriving at college. First-generation students enrolled in postsecondary education at substantially lower rates than continuing-generation students, particularly those pursuing a bachelor’s degree. This finding reinforces extant literature that has demonstrated generational status as a strong influential factor in determining postsecondary educational outcomes (Gibbons & Borders, 2010b; Moschetti & Hudley, 2015). Among those who were enrolled in college, about one third of first-generation students started their postsecondary education experience in 2-year community college settings, which was slightly higher than for continuing-generation students. Although the overall rate of entry to community college was lower than previous rates reported from the ELS:2002 (Redford & Hoyer, 2017), it is clear that community college still serves as a point of access to higher education, especially for first-generation students (Moschetti & Hudley, 2015).

Our results reaffirm that first-generation students are still disadvantaged when considering enrollment in postsecondary education. Hispanic and Black students, as well as those from low-income families, were overrepresented among first-generation students. This outcome is consistent with past demographic profiles of first-generation students (Falcon, 2015; Redford & Hoyer, 2017). In our sample, first-generation students scored lower than their continuing-generation peers on selected SCCT core constructs (viz., postsecondary educational self-efficacy and goals). In the ninth grade, future first-generation students were already less confident they could attain a bachelor’s degree and also reported lower postsecondary educational goals when in the 11th grade. This finding is consistent with past literature (Falcon, 2015; Gibbons & Borders, 2010b; Pascarella et al., 2004) and indicates that the lower educational aspirations of first-generation students are often established well before the need to express and pursue postsecondary educational goals and enrollment decisions.

Consistent with SCCT (Lent et al., 2000), postsecondary educational self-efficacy expressed in early high school exerted a substantial positive influence on higher postsecondary educational goals reported later in high school. Together, postsecondary educational self-efficacy and goals were important in determining immediate postsecondary education enrollment for both first- and continuing-generation students. Self-efficacy acts as a motivation factor that drives goal establishment, planning, and perseverance to achieve goals when faced with difficulties. Thus, self-efficacy has a direct influence on individual performance and attainment (Bandura et al., 2001; Gibbons & Borders, 2010a). We found that the total (both direct and indirect via goals) effects of postsecondary educational self-efficacy on postsecondary enrollment (i.e., bachelor’s, certificate/associate, and postsecondary classes) were greater for first-generation students than for continuing-generation students. This might be because first-generation students usually have lower levels of self-efficacy (Gibbons & Borders, 2010a); increasing their self-efficacy tends to create a larger impact. It appears that early (well before the ninth grade) and consistent efforts to improve the postsecondary educational self-efficacy of first-generation students would be beneficial in raising their postsecondary educational enrollment.

The support of friends and parents with college, career, and personal problems directly influenced postsecondary educational goals but did so differently for first- and continuing-generation students. Parental support exerted a positive influence on educational goal setting for both first- and continuing-generation students. Despite parents of first-generation students lack of personal experience with college life and knowledge regarding useful resources (or ways) to plan, prepare, and apply for college (Falcon, 2015; Moschetti & Hudley, 2015), support from parents still played a significant role in adolescents’ educational outcomes. The support provided by friends also played a significant role in the educational decision-making of first-generation students who may have relied on their friends to compensate for the lack of informational support from parents (Gibbons et al., 2006). Interestingly, the support offered by teachers and counselors was not significant in determining higher postsecondary educational goals for either first- or continuing-generation students. This finding is consistent with previous research (Bell et al., 2009; Gibbons et al., 2006; Gibbons & Shoffner, 2004; Gottfried et al., 2017; King, 2012).

We found the lack of available personnel to provide consultation on college, career, and personal problems (lack of support) negatively affected higher educational goal setting but was not statistically significant for all students (full model) or for first- or continuing-generation student groups. The negative influence is consistent with the literature, given college- and career-related information, as well as emotional support, could inform students about the necessary steps to prepare for postsecondary education and future careers, and thus, influence students’ decisions of going to college (e.g., Bell et al., 2009; Gibbons et al., 2006; Hooker & Brand, 2010). Sharing problems with important personnel and looking for solutions is important for adolescents to navigate through high school studies, college and career options, and transition to postsecondary learning and careers. However, due to nonsignificance, this finding is inconclusive. Future studies need to continue investigating this topic with more empirical data and robust measures.

The financial concern of attending college was the only significant barrier for continuing-generation students and preventing students from setting higher goals but was not significant for first-generation students. Literature suggests that financial considerations, regardless of generational status, can discourage students from continuing education beyond high school (Jerrim et al., 2015; Perna, 2010). Our finding is interesting, given that most first-generation students come from low-income families and perceive heavier financial burdens toward attending college (Redford & Hoyer, 2017). Commonly, FGCSs work multiple jobs and longer hours to support their college expenses (Falcon, 2015; Furquim et al., 2017; Gibbons & Shoffner, 2004). Perhaps a lack of knowledge of college tuition costs and existing expectations of the need to work for college relieve first-generation students’ financial concerns, which, in turn, does not prevent them from continuing their education. In contrast, continuing-generation students may feel discouraged when their parents express financial difficulties in supporting them in college.

Implications

Our results suggest that postsecondary educational self-efficacy in early adolescence (ninth grade) exerted a strong, positive influence on postsecondary educational goals established later in high school. Together, self-efficacy and goals affected students’ immediate postsecondary education enrollment. The influence of self-efficacy was stronger for first-generation students. Therefore, college planning and preparation must be viewed as an important and recognized curriculum component rather than an assumption that will naturally occur as students approach graduation. A longitudinal perspective is indicated that might begin as early as in elementary school, but well before high school, where students are challenged to think about the connections between schoolwork, postsecondary educational options, and work/career. The goals of interventions would likely include opportunities to acquire information about self, the world of work, and the importance of education in achieving future goals for work and adult life. These types of activities throughout childhood and adolescence might serve to motivate the establishment of postsecondary educational goals and to take action to achieve these goals.

Interventions might also provide awareness and engagement opportunities in college and career preparation programs/activities through school coursework and in community-based settings (e.g., career and technical education courses/pathways, internships or work-based learning, college tours, dual enrollment, and sustained counseling opportunities; e.g., Xing et al., 2019). College awareness, preparation, and support are particularly critical for first-generation students who are likely to possess limited knowledge about postsecondary education options, college, and the college admission process. By engaging in informational and preparatory activities or programs, students can develop knowledge about college and careers, as well as establish self-efficacy in pursuing postsecondary education.

Establishing formal and informal networks of social support that includes family members, mentors, friends, counselors, and teachers is critical for students to navigate the process of planning and preparing for college during high school and helps them cope with barriers (Moschetti & Hudley, 2015). Such a support group should be able to provide its members with information regarding academic preparation, college application, financial aid application, and so on, and resources that increase students’ exposure to postsecondary education and careers. To accommodate the lack of social network resources of first-generation students, counselors could prepare an information brochure that contains the process of the college application, the introduction of financial aid, successful stories, campus resources, and external links to websites. Teachers could inform parents of resources on campus for students to explore college and work options and recommend opportunities to expand students’ support networks.

Limitations and Conclusions

The findings of this study should be interpreted with several limitations in mind. First, the use of existing survey data poses analytical constraints that are determined by the availability and construction of variables in the data set. For example, postsecondary educational self-efficacy was measured by an item asking for students’ perceived ability to complete a bachelor’s degree. This query was more restrictive in scope than what we would have hoped, but the HSLS:2009 database did not include a more robust measure of this construct. In addition, because measures of the variables are predetermined, using single-item measures results in unknown psychometrics of these measures compared to existing SCCT-related scales. Lastly, demographic and educational outcome data are self-reported so the validity of findings can only be inferred as accurate based on participants’ responses.

Despite limitations, this study employed the most recent nationally representative longitudinal data set sponsored by the U.S. Department of Education, which allowed for a robust sample with generalizable results. The large data set also provided an opportunity to examine the process of college planning and academic pursuits by assessing core SCCT constructs (Lent et al., 1994, 2000) at different time points in time both during and after high school. The longitudinal nature of the data allowed us to demonstrate early influences on later educational-related goals and actions. Results suggest that educators should consider introducing interventions designed to support educational self-efficacy (and its relationship to postsecondary educational attainment) much earlier in students’ school experience. The limited impact of support from school counselors and teachers also requires attention to determine ways to increase positive influence from these professionals.

We found that first- and continuing-generation students shared some demographic and educational characteristics but that contextual factors exerted different influences on the two groups. Future studies should continue to investigate contextual factors that may enhance first-generation students’ educational and career development. Studies should also explore the intersectionality of generational status and key demographic characteristics (e.g., race, social class) and their collective influence on student transition to postsecondary education.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Xue Xing

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