Diverse Students,High School Factors,and Completion Agenda Goals: An Analysis of the Illinois Class of 2003

Abstract

Illinois education policymakers have adopted the completion agenda that emphasizes increasing postsecondary credential attainment. Meeting completion agenda goals necessitates addressing the achievement gap. To aid in developing policy to support improved completion, this study analyzes a comprehensive statewide dataset of the 2003 Illinois high school graduating class attending 4-year institutions using Cox regression survival analysis. Study findings indicate that African American (0.768 odds ratio) and Hispanic students (0.746) were significantly less likely to complete a baccalaureate degree within 7 years of graduating from high school when compared with their White peers. Furthermore, significance held regardless of income level. Several factors significantly related to improved likelihood of baccalaureate completion were identified including high school composite American College Testing (ACT) score, dual credit and advanced placement (AP) course taking, type of curriculum, ACT English and mathematics scores, and completing the ACT core curriculum. Analysis was conducted by race and income to compare the differences in significance across these groups.

Keywords

achievement gap curriculum dual credit education policy educational reform multicultural education

The completion agenda has become predominant in education policy in the United States (Ochoa, 2011; Russell, 2011; U.S. Department of Education, 2011). Embraced by the Obama administration, the National Governor’s Association, the National Conference of State Legislatures, and by foundations and policy advocacy groups such as the Bill and Melinda Gates Foundation, the Lumina Foundation, and others, the agenda’s emphasis is on increasing the number of postsecondary credential holders in the United States, both to compete internationally and to meet developing workforce demands. This focus on postsecondary degree attainment is occurring because of a dual recognition that the United States is falling behind in degree attainment, and that a growing number of jobs require a postsecondary credential. The United States has fallen to 15th in degree attainment among G-20 countries for ages 25 to 34 (Organisation for Economic Co-Operation and Development, 2011), and estimates are that more than 60% of jobs will require some postsecondary credential by 2018 (Carnevale, Smith, & Strohl, 2010).

In Illinois, the state from which this study’s dataset is drawn, the completion agenda has been adopted by the state’s executive and legislative leadership and the state’s P-20 Council (Illinois P-20 Council, 2012). Reflecting the national trend, estimates are that almost two thirds of jobs in Illinois will require postsecondary training by 2018 (Carnevale et al., 2010). At present, about 41% of working age adults in Illinois hold a postsecondary credential. Illinois has adopted a goal of 60% of working age adults holding a postsecondary credential by 2025 (Illinois P-20 Council, 2012).

Achieving completion goals will require addressing the achievement gap. The achievement gap in postsecondary education between White students, and African American and Hispanic students has long been documented. The National Center for Education Statistics study of the 2003-2004 class of first-time postsecondary students revealed that of this group, 36.4% of White students achieved a baccalaureate degree within 6 years compared with only 16.7% of Black students and 16.9% of Hispanic students (Radford, Berkner, Wheeless, & Shepherd, 2010). This achievement gap has deep roots as studies indicate it also exists for standardized testing results in grade school (National Center for Educational Statistics [NCES], 2011a, 2011b), and even as early as preschool (Burchinal et al., 2011) and kindergarten (Fryer & Levitt, 2004). Several explanations for the achievement gap are found in the literature, such as differences in school quality (Condron, 2009; Fletcher & Tienda, 2010; Oates, 2009), schools with minority concentration and inexperienced teachers (Hanushek & Rivkin, 2009), family background factors (Gutman, Sameroff, & Eccles, 2002; Yeung & Pfeiffer, 2009), self-doubt (Tyson, Darity, & Castellino, 2005), and social pressures and concerns about alienation (Ford, Grantham, & Whiting, 2008; Fordham & Ogbu, 1986).

Like many other states, the situation facing the Illinois P-20 system is highly challenging. In Illinois, for every 100 students who enter the ninth grade, only 76 graduate from high school, 42 enter college, 28 enroll the following year, and just 20 graduate within 150% of their expected degree program time (Illinois Board of Higher Education [IBHE], 2008). Exacerbating this situation are shifting demographics in Illinois, with the portion of the population that has traditionally been harder to move through the system to postsecondary degree attainment growing as a percentage of the overall population. According to the U.S. Census Bureau (2013), in 2010, African Americans made up 14.5% of the state’s population, and the Hispanic or Latino population is rapidly increasing, growing from approximately 1.5 million or 12.3% of the state’s population in 2000 to 2.0 million or 15.8% in 2010. Furthermore, the students from these groups make up a disproportionately large percentage of the high school enrollments. In the 2008-2009 academic year, 21% of Illinois high school enrollments were African American, 17% were Hispanic, and 56% were White (IBHE, 2011b). However, African Americans made up 45% of the state’s high school dropouts, Hispanics 23%, and Whites 31%. To meet the state’s lofty completion goals, minority and low-income students must move through the education pipeline to postsecondary attainment more successfully than they have in the past. Policy must be developed that better facilitates student achievement for low-income and minority students who have traditionally faced the achievement gap. This is particularly challenging given that a number of the factors identified in the literature as contributing to the gap are associated with personal and family dynamics, and thus present limited opportunities for policy leverage.

The completion agenda literature advocates several strategies designed to improve degree attainment, with many of these strategies focused on improving the P-20 education pipeline (College Board, 2011; Harnisch, 2011; U.S. Department of Education, 2011). Reflecting these recommendations, Illinois has enacted a number of P-20 education policies particularly aimed at improving the pipeline between secondary and postsecondary education (Blankenberger & Phillips, 2016; Lichtenberger, Witt, Blankenberger, & Franklin, 2014). Joining many other states in adopting elevated education standards, the State has implemented the Common Core State Standards into its P-12 Illinois Learning Standards to better connect high school student learning outcomes to postsecondary preparation expectations. In concert with the adoption of these new standards, Illinois passed legislation in 2010 to implement improved teacher and school leader standards and revise evaluation of teacher performance. In 2009, Illinois passed legislation to encourage and establish standards for dual credit courses. Similar to several other states, Illinois enacted legislation to create a P-20 longitudinal data system (Illinois General Assembly, 2009) that will make data available in an unprecedented way. In 2013, in an attempt to address concerns about institutional equality, the General Assembly enacted legislation to create the Advisory Committee on Education Funding to consider alternatives for a more equitable distribution formula for funding schools (Illinois General Assembly, 2013). Actual enactment of legislation to change the funding formula, however, has not yet occurred. Illinois has not been successful in all of its reform efforts. For example, in 2012, Senate Bill 3244 was proposed mandating that a fourth year of math be added to the required high school curriculum. Instead, the bill was modified eliminating the mandated fourth year and replacing it with guidance provided by the State Board for expanding the math curriculum in high schools (Illinois General Assembly, 2012).

Like many states, Illinois is faced with severe financial challenges that have caused the state to curtail its spending on education. As an example, state general revenue fund support for public universities as a percent of total educational and related revenues fell from 72.7% to 47.1%, a reduction of about US$450 million in constant dollars between fiscal year (FY) 1996 and FY2011 (Blankenberger & Phillips, 2016; IBHE, 2010, 2011a; Lichtenberger et al., 2014). These cuts to public university operations and grants funding has accelerated even further from FY2010 through FY2015, decreasing US$475.8 million or 19.8% after accounting for inflation (IBHE, 2014). Furthermore, state budget cuts have caused inconsistent funding for postsecondary curricular transition programs such as dual credit/dual enrollment and advanced placement (AP) courses. Dual credit/dual enrollment courses are taken by high school students for college credit that also counts for high school credit (Lichtenberger et al., 2014). Funding for dual credit programs through the Illinois Community College Board (ICCB) under the Accelerated College Enrollment Grant and P-16 Initiative Grant were discontinued in FY2007. In FY2005, the P-16 Initiative Grant received US$1.279 million, the majority of which was distributed to support 19,210 secondary students taking 8,935 dual credit college courses, making up 44.7% of the total of 43,580 dual credit participating students in that year (ICCB, 2006). Similarly, Illinois’s funding for AP programs, including program expansion grants, training grants, and grants to offset exam fees for low-income students, has been uneven. Funding for the AP program was cut in half in FY2010 to US$823,450, cut again by 36% in FY2011, eliminated entirely in FY2012, restored to US$527,000 in FY2013, and reduced again by 5.12% in FY2014 (Illinois State Board of Education, 2014).

Like those in other states, Illinois policymakers are seeking data to inform the difficult policy decisions they face for improving postsecondary attainment outcomes, particularly for low-income and minority students. If only one in five freshmen entering high school will complete a baccalaureate degree within 6 years of graduation from high school in Illinois (IBHE, 2008), it begs the question, what factors are associated with those who do complete a baccalaureate degree? And more specifically given the achievement gap, what factors are associated with completion for African American, Hispanic, and low-income students? How do curriculum and early enrollment program effects compare with one another? Which merit increased funding? To begin to answer some of these questions, this study analyzes a statewide dataset of the Illinois high school graduating class of 2003 using Cox regression survival analysis to provide insight into the P-20 factors related to likelihood of timely bachelor’s degree completion.

Review of the Literature

The literature provides a framework for analysis of these factors associated with completion as well as a rationale for inclusion of several of the data elements incorporated in this study. The review opens with a discussion of the conceptual framework employed in the analysis, and then a consideration of P-20 pipeline factors present in the literature which may be associated with greater likelihood of baccalaureate degree attainment.

The Conceptual Framework

Perna and Thomas (2006) offered a conceptual model designed to help policymakers identify factors associated with student success and particularly for reducing the “college success gap.” The model is based on a broad review of the literature and on a previous model developed by Perna (2006). It incorporates 10 indicators of student success across four key transitions in the education process, such as college readiness measures, college enrollment, college achievement, and measures of post-academic performance. The model stresses that student success is a longitudinal process, making it particularly appropriate for studies conducted using longitudinal data systems. The authors emphasize that analysis of student success should be conducted at multiple levels of context as are student decisions and actions. The authors identify four contextual layers: internal student context; family context; school context; and the social, economic, and policy context. The authors offer specific guidance to policymakers and practitioners regarding analysis of student success. They recommend, “For policymakers and practitioners, the three most important units of analysis are students, the K-12 and higher education institutions they attend, and the public policies and programs that help shape student and institutional behaviors” (p. 10). Our study employs the recommendation of Perna and Thomas and analyzes a large number of factors within these four contexts while focusing on bachelor’s degree completion, part of Perna and Thomas’s third transition. The factors in our study not only include student and family characteristics, but secondary and postsecondary institutional factors as well (see Figure 1).

Figure 1.

Conceptual framework.

Education Pipeline Policies: Curricula and Early Enrollment Program Policies

Although certainly not exhaustive of all possible options, for this study, we were able to make use of a dataset that included a large number of curriculum-based institutional factors that have been associated with improved completion in the literature. Studies have offered a number of recommendations for strengthening curriculum aimed at improving postsecondary credential attainment. First, the importance of appropriate high school preparation cannot be understated. With a weak college preparatory curriculum, large numbers of students require developmental course work as they enter postsecondary education. It is estimated that almost 60% of community college students are required to complete at least one developmental education course (Attewell, Lavin, Domina, & Levey, 2006). Improving high school curriculum is proposed as one means of facilitating degree completion, but this will not eliminate the need for remediation altogether. Policies advocated to address developmental and remedial needs include setting clear college readiness standards, aligning curriculum across secondary and postsecondary institutions, providing early assessments for students, and establishing common measurement comparisons across institutions (Collins, 2009).

To improve standards and better align secondary and postsecondary curricula, nearly all states have adopted the more rigorous Common Core State Standards (Common Core State Standards Initiative, 2014). The new standards are meant to more clearly identify college readiness expectations by connecting them to high school degree completion requirements, as well as emphasize career and college readiness skills. Whether through the Common Core or other curriculum reform efforts, advocates for enhanced preparation have emphasized the need to improve these readiness skills alongside improving academic rigor (Conley, 2005, 2007, 2010). Although the Common Core has become politically divisive in some states and has even been repealed by some, rigorous high school standards are nonetheless being adopted as replacements. The increased rigor in secondary curricula and a greater emphasis on career and college readiness skills are intended to improve the likelihood of postsecondary degree completion.

In addition to strengthening high school standards, the introduction of early enrollment programs has been identified by advocates and policymakers as a way to help students complete degrees in a more timely fashion. Johnstone (1993) has long advocated achieving greater learning productivity in P-16 education. He recommended focusing on reducing redundancies between the last 2 years of high school and the first 2 of college by implementing programs that recognize and credit learning that is achieved that cuts across these levels.

Early college programs or “credit-based transition programs” (Bailey, Hughes, & Karp, 2003) such as international baccalaureate programs (IB), advanced placement, early college high schools, and dual credit/dual enrollment/concurrent enrollment courses are advocated by those seeking to improve transitions from high school to college and as a means of acquiring college credit while still in high school (Hoffman, 2012). Proponents argue that dual credit/enrollment is a conduit for improving high school curriculum, raising student motivation to attend college, and helping students adjust to college (Hoffman, Vargas, & Santos, 2008; Hunt & Carroll, 2006). Studies have shown that dual credit has a positive impact on educational aspirations (Hoffman et al., 2008; Howerter, 2011), improved likelihood of enrollment and graduation particularly for low-income and male students (Karp, Calcagno, Hughes, Jeong, & Bailey, 2007; Lichtenberger et al., 2014), improved college readiness in reading, writing, and mathematics (Kim & Bragg, 2008), as well as improved degree attainment and time to degree completion (An, 2013, 2015; Geise, 2011). However, there are limitations and some conflicting findings in the literature as well (Jones, 2014; Speroni, 2011). For example, in her analysis of data from two high school cohorts in Florida districts using regression-discontinuity design, Speroni (2011) found no evidence that taking dual enrollment courses improves marginal students’ outcomes for high school graduation, college enrollment, and college degree attainment.

Differentiating impacts by race and income group is a critical part of the analysis of high school programs and strong preparation for successful postsecondary attainment. The literature emphasizes that differences in quality of high schools attended by minority and nonminority students plays a significant role in racial and ethnic college achievement gaps (Condron, 2009; Fletcher & Tienda, 2010; Massey, 2006; Niu & Tienda, 2008; Niu, Tienda, & Cortes, 2006; Oates, 2009; Schneider, Martinez, & Owens, 2006). For example, in a study of students who attend selective universities, Massey (2006) found that minority students attending such institutions were disproportionately from high schools of lower quality on a number of measures. Fletcher and Tienda (2010) argued that institutional impacts on performance gaps have been understudied, at least in part due to lack of available data. In their study of collegiate achievement gaps, they found support for their hypothesis that quality of high school attended by minority versus majority students was a factor in collegiate achievement gaps even when controlling for precollege records such as exam scores and class rank based on high school grade point average (GPA).

Research Questions

As the State of Illinois began the development of a longitudinal data system (ILDS), staff of the IBHE, in conjunction with researchers at the Illinois Education Research Council (IERC), which provides research support to the Illinois P-20 Council, launched a pilot project to develop a framework for conducting analyses of data that would become available through the ILDS. The core of the dataset housed at IERC is available through a data-sharing agreement undertaken with the IBHE and has been enhanced through additional data-sharing agreements entered into by the IERC. At the time, the dataset was the most comprehensive available at the student unit record level in Illinois and included the entire population of public Illinois High School Graduates from 2003.

The study focuses exclusively on baccalaureate completion by students initially enrolling after high school graduation at baccalaureate granting institutions. We used this approach primarily for two reasons. First, more data were available on these students for inclusion in the analysis, improving the ability to control for a large number of covariates. Second, we had concerns about controlling for student motivation to pursue a baccalaureate degree and related selection bias issues. No indicator of student motivation to obtain a baccalaureate degree was available in the dataset. Delimiting the study group to students whose initial enrollment after high school was at a baccalaureate granting institution improves the likelihood that such students were of similar motivation with regard to pursuing a baccalaureate degree when compared with those students who began their postsecondary experience at a community college or delayed enrollment. The delimitation provides all study group members the same amount of time to complete a bachelor’s degree, 7 academic years following high school graduation.

Planning for this study took place in the context of challenges facing Illinois in pursuing state degree attainment goals and with an emphasis on the need to reduce the achievement gap to meet these goals. Given this focus, the broad and exploratory nature of the analysis, and the number of potentially competing factors included in the analysis, we decided that the initial study would employ Cox regression survival analysis. This technique yields odds ratios indicating comparative likelihood of completion for a factor while controlling for the effect of all covariates included in the analysis. With this approach in mind, we developed the following research questions:

Research Question 1: While controlling for a large number of covariates, how do patterns differ by race and income level for the likelihood of on-time bachelor’s degree completion?

Research Question 2: While controlling for a large number of covariates, what curricular factors are associated with increased likelihood of on-time bachelor’s degree completion for 4-year college entrants overall and from different racial and income groups?

Method

The dataset includes the total population of public Illinois High School Graduates from 2003 who enrolled at 4-year institutions the Fall semester following high school graduation and for whom complete information on the factors studied was available. This includes 21,665 students, out of the total of 115,677 in the 2003 class (see Table 1). The population does not include those who started at a community college after high school. This is a limitation of the study, and future studies capitalizing on the expanded ILDS data may be able to include those students as well, but this also strengthens the validity of the study as only students with similar intent to pursue a baccalaureate degree at a 4-year institution were included. Furthermore, as the entire population of baccalaureate institution enrollees was included, the study shows strong results for such students and offers guidance for more comprehensive and focused studies with a larger available dataset in the future. No sampling technique was necessary for the analysis of the entire population. Using the full enumeration means the dissimilarities uncovered are actual differences in result for this group of students. Nonetheless, statistical significance was provided in the analysis to indicate strength of relationship associated with the differences.

Table 1.

Descriptive Information for Categorical Variables for Total Sample and by Family Income Level.

Variable	All(N = 21,655)		High(n = 8,104)		Mid-high(n = 5,875)		Mid-low(n = 4,593)		Low(n = 3,083)
Variable	n	%	n	%	n	%	n	%	n	%
Gender
Male	9,726	44.9	3,948	48.7	2,676	45.5	1,925	41.9	1,177	38.2
Female	11,929	55.1	4,156	51.3	3,199	54.5	2,668	58.1	1,906	61.8
Race
African American	2,096	9.7	256	3.2	322	5.5	591	12.9	927	30.1
Hispanic	1,125	5.2	174	2.1	261	4.4	314	6.9	376	12.2
Asian American	1,518	7.0	429	5.3	404	6.9	361	7.9	324	10.5
White	16,916	78.1	7,245	89.4	4,888	83.2	3,327	72.4	1,456	47.2
High School GPA
3.5+	10,606	49.0	4,371	53.9	2,977	50.7	2,074	45.2	1,184	38.4
3.0-3.4	6,531	30.2	2,409	29.7	1,789	30.5	1,405	30.6	928	30.1
2.5-2.9	3,004	13.9	938	11.6	769	13.1	716	15.6	581	18.9
<2.5	1,514	7.0	386	4.8	340	5.8	398	8.7	390	12.7
High School Program Type
College Prep	15,360	70.9	6,192	76.4	4,290	73.0	3,082	67.1	1,796	58.3
CTE	1,781	8.2	447	5.5	407	6.9	449	9.8	478	15.5
General	4,514	20.8	1,465	18.1	1,178	20.1	1,062	23.1	809	26.2
Selectivity
Highly/Most Competitive	4,582	21.2	2,310	28.5	1,165	19.8	720	15.7	387	12.6
Very Competitive	4,993	23.1	2,049	25.3	1,263	21.5	978	21.3	703	22.8
Competitive	9,817	45.3	3,292	40.6	2,865	48.8	2,252	49.0	1,408	45.7
Less/Noncompetitive	2,263	10.5	453	5.6	582	9.9	642	14.0	585	19.0

Note. CTE = Career and Technical Education; GPA = grade point average.

The study period extends from Fall 2000 to Spring 2010. The data were available from American College Testing (ACT) under shared data agreements between the IBHE and ACT. At the time, every public high school junior in Illinois was required to take the ACT as part of the Prairie State Achievement Examination (PSAE). Additional college enrollment and degree completion information was acquired from the National Student Clearinghouse (NSC), a national collaborative of over 3,400 postsecondary institutions, encompassing 96% of all postsecondary enrollments (NSC, 2016). The study includes the postsecondary enrollment information from the Fall semester of 2000 through the Spring semester of 2010. The dataset included three academic years during which the students could be enrolled during their secondary experience and 7 academic years after high school graduation in the Spring of 2003. These datasets were enhanced with information from the Illinois High School Report Card, IPEDS, and Barron’s (2003) Profiles of American Colleges.

In light of the contextual layers identified by Perna and Thomas (2006), we categorized variables as internal student/family, school, and social/economic/policy factors. In focusing the analysis on the specific data elements, key parts of the conceptual framework were supplemented by the approaches used by Wang (2009) in a study to examine postsecondary outcomes of community college students, and Lichtenberger (2011) in a study to examine the postsecondary outcomes of undergraduate reverse transfer students. The student-level and family factors included variables that could potentially impact not only a students’ ability to pay for college, but also the amount of time they are able to dedicate to their studies. We used the school-level factor high school composite ACT to help control for differences across high schools that could potentially impact a student’s postsecondary completion pattern. The components are illustrated in Figure 1 with definitions of the terms provided in the appendix.

Analysis

To answer the research questions, we employed a form of survival analysis called Cox regression. A Cox regression model is a statistical technique used to explore the relationship between a set of explanatory/independent variables and a time-based event of interest, in this case, the number of semesters to bachelor’s degree completion. Time to degree completion was selected as it is of substantial interest to policymakers. A Cox regression estimates the risk of an event occurring within a specified time span (Cox, 1972). It provides an estimate of the effect of each independent variable, which allows for an estimation of the probability of an event of interest, given the characteristics of the individuals included in the study (Walters, 2001). The estimate of the treatment effect on survival is provided in odds ratios. The estimates are relative as they are comparisons between a baseline group and the group being examined. For this study, this enabled us to compare odds ratios for African American and Hispanic students against those of the group overall, and White and Asian students.

Cox regression is a method that is traditionally used in medical and epidemiological research but has been increasing in use as a technique for analysis in policy settings (Buckley & Westerland, 2004; B. S. Jones & Branton, 2005; Jun & Weare, 2010). Although multinomial regression analysis has been typically utilized for studies with nominal dependent variables, such as those related to student departure and completion (Chen, 2010; DesJardins, Ahlburg, & McCall, 1999; Han & Ganges, 1995; Huff & Fang, 1999), survival analysis has begun to be used as well (Ortiz & Dehon, 2013; Scott & Kennedy, 2005). Unlike multinomial, Cox regression is additionally able to handle cases of repeatable events such as differing semesters of degree completion, the dependent variable for this study.

In an effort to determine if the results regarding student and environmental factors for 4-year college entrants differed across the various family income categories, several separate Cox regression models were developed and analyzed, one for the entire sample and subsequent models for each income category and racial group. The family income categories were based on an ordinal measure that included high = >US$80K, mid-high = US$50K to <US$80K, mid-low = US$30K to <US$50K, and low = <US$30K.

This study is intended to be an exploratory analysis of differences in odds of baccalaureate completion by race and income group, as well as several possible curriculum factors that may be associated with that completion. Despite being the most comprehensive such dataset available in Illinois at the time, there were limitations in the dataset that restricted our analysis. For example, the dataset does not include pre-high school data or any student motivation measures. These limitations in the data prevented us from conducting stronger causal analyses of the factors determined to be associated with higher odds ratios for baccalaureate completion. For example, student academic ability prior to high school could have influenced student entry into a curriculum track in high school (Career and Technical Education [CTE], general, or college prep), and performance in that high school curriculum. Similarly, factors such as academic motivation may mediate some of the effect of curriculum options on student academic success. For example, although An (2015) determined that at least 78% of the effect of dual credit participation on academic performance was not mediated by academic motivation and engagement, he found that some of the effect may have been mediated by these factors. As noted previously, we believe that restricting our analysis only to those students who chose to enroll in a baccalaureate granting institution in their first semester after high school increases the likelihood that they had similar motivation to obtain a baccalaureate degree. Nonetheless, there was no true measure of academic motivation in the dataset. Thus, with limitations such as these in the dataset used for this study, the findings of our analysis are not necessarily causal. Significant results in our analysis should be interpreted only as indicating that a relationship exists between the independent variables/factors in the study and the dependent variable of on-time bachelor’s degree completion for these students who entered a 4-year college the Fall semester after high school completion.

Findings and Discussion

Table 1 displays the descriptive information for the categorical variables, as well as the scaled variables, for each of the family income levels. Of the 21,655 students in the cohort representing every graduating public school high school senior in 2003 who attended a baccalaureate institution the Fall semester after graduating, just 2,096 were African American, and 1,125 were Hispanic, underscoring the challenge faced in reducing the achievement gap to meet degree attainment goals. Furthermore, 927 of those 2,096 African American students were low income, and 376 of the 1,125 Hispanic students were low income.

Table 2 displays the results of the institutional and curriculum factors for the combined model and the four separate Cox regression models designed to predict time to bachelor’s degree completion for each income group. Table 3 shows the same results for the four racial groups.

Table 2.

Student, Family, and Institutional Factors Associated With Baccalaureate Completion: Combined and by Income Group.

Variables in the equation	All students	High-income model	Mid-high-income model	Mid-low-income model	Low-income model
Variables in the equation	Exp(B)	Exp(B)	Exp(B)	Exp(B)	Exp(B)
Dual Credit Participation at a CC	1.026*	1.032	0.998	1.031	1.076**
Dual Credit Participation at a 4-year College	1.077	1.002	1.053	1.075	1.130
AP English	0.986	0.960	1.008	0.996	1.007
AP Math	1.008	1.004	1.033	1.015	0.960
AP Social Science	1.052*	1.045	1.064	1.066	1.073
AP Science	0.957*	0.985	0.930	0.964	0.925
AP Foreign Language	1.053**	1.072*	1.050	1.035	1.015
Male	0.825***	0.801***	0.841***	0.831***	0.830***
African American to White	0.768***	0.796**	0.830**	0.825**	0.750***
Hispanic to White	0.746***	0.763**	0.755***	0.797**	0.709***
Asian to White	0.930*	0.907	0.907	0.919	1.039
GPA range
2.5-2.9 to <2.5	1.322***	1.384***	1.431***	1.165	1.291**
3.0-3.4 to <2.5	1.700***	1.677***	1.934***	1.540***	1.601***
3.5+ to <2.5	2.272***	2.158***	2.635***	2.128***	2.233***
ACT English	1.007*	1.009*	1.001	1.010	1.002
ACT Math	1.013***	1.008	1.015**	1.017**	1.016
ACT Reading	0.999	1.002	0.997	0.993	1.007
ACT Science	0.992**	0.993	0.991	0.994	0.995
Completion of ACT Core Curriculum	1.066***	1.027	1.051	1.112**	1.153**
HS Curriculum: CTE to College Prep	0.940	1.012	0.906	0.908	0.974
HS Curriculum: General to College Prep	0.948*	0.972	0.896**	1.001	0.965
Income category
Mid-High to High Income	0.929***
Mid-Low to High Income	0.846***
Low to High Income	0.766***
Expected to Receive Financial Aid	0.969	0.985	0.929	0.988	0.764**
Expected to Work in College	0.954**	0.967	0.966	0.892**	0.945
Number of Siblings	0.961***	0.969**	0.971*	0.977	0.912***
HS Overall Composite ACT	1.044***	1.037***	1.049***	1.047***	1.045***
Competiveness of College Attended
Most competitive to less/non	1.720***	1.551***	1.668***	1.808***	2.343***
Very competitive to less/non	1.460***	1.400***	1.415***	1.368***	1.609***
Competitive to less/non	1.342***	1.213**	1.371***	1.341***	1.434***

Note. ACT = American College Testing; AP = advanced placement; CC = community college; CTE = Career and Technical Education; GPA = grade point average; HS = high school.

Significant at the p < .05 level. **Significant at the p < .01 level. ***Significant at the p < .001 level.

Table 3.

Student, Family, and Institutional Factors Associated With Baccalaureate Completion by Race.

Variables in the equation	African American	Hispanic	Asian	White
Variables in the equation	Exp(B)	Exp(B)	Exp(B)	Exp(B)
Dual Credit participation at a CC	0.969	1.098	1.047	1.025*
Dual Credit participation at a 4-year college	1.125	1.139	1.041	1.048
AP English	0.978	0.939	0.971	0.990
AP Math	0.906	0.911	1.076	1.018
AP Social Science	1.049	0.928	1.105	1.057*
AP Science	1.007	1.043	0.953	0.951*
AP Foreign Language	1.030	1.067	1.033	1.059**
Male	0.760***	0.737***	0.963	0.820***
GPA range
2.5-2.9 to <2.5	1.225	1.265	1.244	1.342***
3.0-3.4 to <2.5	1.623***	1.603*	1.313	1.734***
3.5+ to <2.5	2.193***	2.464***	1.932***	2.285***
ACT English	1.023**	1.010	1.003	1.005
ACT Math	1.017	1.020	1.016	1.011***
ACT Reading	0.980**	1.014	1.001	1.000
ACT Science	1.010	1.005	1.001	0.990**
Completion of ACT Core Curriculum	1.146**	0.978	1.044	1.066***
HS Curriculum: CTE to College Prep	0.928	1.221	0.932	0.937
HS Curriculum: General to College Prep	1.031	1.047	0.955	0.939**
Income Category
Mid-High to High Income	1.015	0.911	0.900	0.927***
Mid-Low to High Income	0.918	0.878	0.849	0.839***
Low to High Income	0.759**	0.735*	0.880	0.772***
Expected Aid	0.983	1.081	1.015	0.961
Expected to Work	0.770***	0.803	0.917	0.976
Number of Siblings	0.931***	0.918*	1.012	0.965***
HS Overall Composite ACT	1.050***	1.013	1.010	1.047***
Competiveness of College Attended
Most Competitive to Less/Non	1.888***	2.579***	2.149***	1.648***
Very Competitive to Less/Non	1.365**	1.891***	1.914***	1.416***
Competitive to Less/Non	1.220*	2.024***	1.749**	1.302***

Note. ACT = American College Testing; AP = advanced placement; CC = community college; CTE = Career and Technical Education; GPA = grade point average; HS = high school.

Significant at the p < .05 level. **Significant at the p < .01 level. ***Significant at the p < .001 level.

Comparisons of Baccalaureate Completion by Race and Income Group

Answering the first research question, as we expected, the results of the analysis indicated that race was a significant factor in lower odds of baccalaureate completion. Examining the data from Table 2, for all income groups combined, African American (0.768 odds ratio) and Hispanic students (0.746) were significantly less likely to complete a baccalaureate degree within 7 years of graduating from high school when compared with their White peers. These significant differences held despite the large number of covariates in the model, and the fact that all of the students included were enrolled in baccalaureate granting institutions in the Fall following high school graduation. This association held even when examined by income category. While considering only low-income students, African American students were nonetheless significantly less likely (0.0750 odds ratio) to complete than their White peers, and Hispanic students were as well (0.709). These daunting figures underscore the challenge of the achievement gap, and represent a significant hurdle for states whose education policies are focused on improving postsecondary attainment.

Another factor worth noting is the difference in odds ratios based on gender. In the overall model, males are significantly less likely to complete a baccalaureate degree (0.825 odds ratio) than women, even controlling for all other covariates in the model. Similar significant effects hold across all income levels. This significant effect persists for African American students (0.760 odds ratio), Hispanic students (0.737 odds ratio), and White students (0.820 odds ratio), although it is not significant for Asian students. Thus, for African American and Hispanic students already challenged by significantly lower completion odds, this condition is further exacerbated for males.

Overall High School Academic Context

Turning to the second research question related to factors associated with higher completion odds ratios, the results of the analysis indicate that a student’s high school academic context was significantly associated with decreased time to degree completion. While controlling for all other factors, higher secondary school composite ACT scores accounted for statistically significantly higher odds ratios for baccalaureate completion (1.044 odds ratio). This statistical significance held across all income categories. However, when broken down by race, statistical significance remained only for African Americans (1.050 odds ratio) and Whites (1.047). These results align with those of other researchers who suggest that high school context has a significant impact on success for underrepresented students (Condron, 2009; Fletcher & Tienda, 2010; Massey, 2006; Niu & Tienda, 2008; Niu et al., 2006; Oates, 2009; Schneider et al., 2006).

Early College Enrollment Factors

Examining secondary/postsecondary transition programs, analysis of the overall model provides evidence of a positive relationship between early college credit opportunities and time to bachelor’s degree completion. Controlling for all of the factors in the model, odds ratios were significantly higher for students participating in dual credit courses at community colleges (1.026 odds ratio for every semester a dual credit course was taken). Similarly, significant positive relationships existed for students participating in AP social science (1.052 odds ratio), and foreign language courses (1.053 odds ratio). The impact of taking AP science was actually found to be a negative relationship (0.957 odds ratio), although this effect may be a result of the students enrolling in more rigorous baccalaureate majors. In the analyses by income category, only the low-income model yielded similar results for dual credit participation (1.076 odds ratio), and only AP foreign language in the high-income model maintained statistical significance (1.072 odds ratio). Differentiating the factors by race, the only statistical significance related to dual credit that was maintained was for White students (1.025 odds ratio). Similarly, the same significant effect found for the three types of AP courses only held for White students.

The results are substantive when considering whether it is worthwhile to consider adopting or expanding such programs, and they support those in the literature who have found positive results for degree attainment associated with dual credit participation (An, 2013, 2015; Geise, 2011). Note that a low-income student dually enrolled through a community college had 7.6% higher odds of completing a baccalaureate degree for every such semester enrolled compared with peers without a record of dual enrollment, even after controlling for all other covariates in the model. This increases to 15.2% with a second semester of enrollment in a dual credit course at a community college. Similarly, while controlling for all other factors, overall, students taking AP social science or AP foreign language were significantly related to an increased likelihood of completing a baccalaureate degree respective to those not taking such courses. It is important to note that the AP results were somewhat limited as they only reflect course-taking patterns, not passage of the AP exam.

Academic Rigor

Improved odds ratios of baccalaureate completion were found overall for students taking the more rigorous ACT core high school curriculum (1.066 odds ratio), for performance on ACT Math (1.013 odds ratio) and English tests (1.007 odds ratio), and for higher GPA. In Illinois, 4 years of English and 3 years of mathematics are required for high school graduation, but only 2 years of social science, and 2 years of natural science are required. ACT defines its core high school curriculum as 4 years of English, and 3 years of mathematics, social science, and natural science. Only 69% of the students included in the analysis indicated completion of the ACT core. All else being even, students who completed the ACT core had 6.6% higher odds of bachelor’s degree completion within 7 years of high school graduation compared with those who did not complete the ACT core. Interestingly, performance on the ACT Science test was negatively related to bachelor’s degree completion, echoing the AP Science finding and again suggesting that students who perform better in science might be enrolling in more challenging programs, decreasing their likelihood of a timely baccalaureate completion.

Statistically significant differences were demonstrated for completing the ACT core curriculum during high school for low-income and mid-low-income students only. Across racial groups, statistical significance was only achieved for African American (1.146) and White students (1.066) for the ACT core. Not surprisingly, those students with higher GPA compared with those with lower GPA were found to be significantly more likely to complete a baccalaureate degree within 7 years. This held true across income and racial categories.

Last, the high school curriculum track taken was found to be significant for overall students when comparing those taking the general curriculum with those taking the college preparatory curriculum (0.948 odds ratio). Of the 21,655 students in this study, 70.9% took the college preparatory curriculum, just 8.9% took the CTE curriculum, and the rest the general curriculum. All else equal, students taking a college preparatory curriculum and entering baccalaureate institutions after completing high school had significantly higher odds of completing a baccalaureate degree in the time allotted than those taking the general curriculum. When analyzed by income category, the same significant effect was only found for middle to higher income students. By racial category, the effect was only significant for White students.

Institutional Selectivity

An additional factor worth noting is the significant association between attending more competitive institutions and higher completion odds ratios. Competitiveness of institution attended was measured using the Barron’s admissions selectivity rankings ranging from most competitive, very competitive, competitive, to less or noncompetitive. For all students, attending more competitive institutions compared with less or noncompetitive institutions was significant. This held across income levels, with odds ratios increasing in importance as income levels were lower. For example, all else equal, overall students attending a most competitive institution had significantly higher odds (1.720) of completing than a peer attending a less or noncompetitive institution. This number was even greater for low-income students attending most competitive institutions who had significantly higher odds (2.343) of completing in the allotted time than their peers attending less or noncompetitive institutions. For example, controlling for all other covariates and with all students in the model, Hispanic students attending most competitive institutions had significantly higher odds (2.579) of completing a baccalaureate degree than their peers attending less or noncompetitive institutions, Asian students significantly higher odds (2.149), and African American students significantly higher odds (1.888) as well. These results offer additional support to those in the academic matching literature who suggest that there is a positive relationship between academic performance and college selectivity (Alon & Tienda, 2005; Bowen, Chingos, & McPherson, 2009; Cortes, 2010; Fischer & Massey, 2007; Horn & Carroll, 2006; Light & Strayer, 2000; Melguizo, 2008; Small & Winship, 2007). More focused study on this phenomenon is warranted.

Implications for Institutional and State Policy

The strength of this study is intended to be its analysis of the differences in likelihood of on-time bachelor’s degree completion for 4-year college entrants by different racial and income groups, as well as its exploratory analysis of curricular factors that are associated with these differential rates. The findings regarding differences in odds ratios across multiple factors are meant to offer suggestions for future research and potential directions for educational policies to improve completion rates for students of different racial and income backgrounds in the context of the completion agenda and the achievement gap. The results of this analysis as well as the supporting literature offer guidance to policymakers related to several factors associated with baccalaureate degree attainment. Factors related to early college enrollment, academic rigor and preparation, impact of socioeconomic status (SES) and family characteristics, and school characteristics suggest a number of policy opportunities that could have a positive impact on achieving timely baccalaureate completion for a greater number and diversity of students. These implications are important not just for state-level policy, but for institutional policy as well. In many states such as Illinois, the adoption of policies that originate at the state level have limitations. Decisions about implementation of curriculum changes and programs such as early college enrollment take place at the district and even individual school level. Finding opportunities for policy leverage is critical for improving postsecondary completion and reducing the achievement gap particularly because a number of the factors identified in the literature as contributing to the gap are associated with personal and family dynamics, and thus offer limited opportunities for policy leverage. For districts and schools seeking to increase the likelihood of their students completing baccalaureate degrees, the results of this study offer support for consideration of the adoption of such approaches.

A significant finding of the study is that comparative success rates of African American, Hispanic, and White students underscore the challenge of the achievement gap. As noted, this analysis was limited to those students with similar intentions of completing a baccalaureate degree as it only included those who entered baccalaureate institutions immediately after high school graduation. For those students attending 4-year institutions in the Fall semester after high school, and while controlling for a large number of covariates, African American students had significantly lower odds (0.768) of completing a baccalaureate degree within 7 years of high school graduation than their White peers, and Hispanic students had significantly lower odds (0.746) as well. This challenge is even further exacerbated for males, with African American males at 0.760 lower odds, and Hispanic males at 0.737 lower odds of completing than their female peers. These findings highlight the need to develop improved P-20 pathways and reduce the achievement gap, or lofty state and federal completion goals will not be met.

To that end, the findings support the efficacy of more academically challenging high school education. Results support the value of more rigorous academic standards, and the addition of more academically rigorous courses as in the ACT core curriculum to improve baccalaureate degree attainment rates. The connection of higher scores on the high school ACT and GPA to improved odds of baccalaureate completion provides further support for the adoption of higher standards. Even if more rigorous standards are not adopted in state policy, institutions and school districts can foster environments that encourage the completion of more demanding course work. Just 69% of the students included in the analysis indicated completing the ACT core, which includes 4 years of English, and 3 years of mathematics, social science, and natural science. For high school graduation in Illinois, students must take 4 years of English and 3 years of mathematics, but are not required to take a third year of social science and a third year of natural science as in the ACT core. All else being equal, the odds of timely bachelor’s degree completion for students overall who completed the ACT core were significantly higher (1.066) when compared with those who did not complete the ACT core, and African American students had significantly higher odds (1.146) than their peers as well.

The significant relationship between academic quality of high school attended and likelihood of baccalaureate completion suggests the need to consider changes to the state’s funding formula, which will improve equity of funding across institutions. Moreover, the role of attendance at more selective postsecondary institutions needs to be further explored. Increasingly, low-income students are disproportionately attending less or noncompetitive postsecondary institutions (Bastedo & Jaquette, 2011; National Center for Education Statistics, 2012). Results of the study indicate that low-income and minority students could significantly benefit from attendance at more competitive institutions.

Last, the study findings offer additional support to those advocating expanding opportunities for early college enrollment programs, particularly dual credit. Beyond just the potential for cost savings by eliminating redundancy in the P-20 system, the results of this study indicate such participation is also associated with greater likelihood of baccalaureate degree attainment. State policies such as those in Illinois can encourage the adoption of early enrollment programs such as dual credit and AP course taking. Furthermore, stable state funding of dual credit and AP programs appears warranted. Nonetheless, even without additional state funding, local policymakers should consider adding such programs. The decision to add dual credit and AP programs is ultimately made at the district and institutional level whether state or federal funding is available or not. The value of taking on the tasks necessary to work with local postsecondary institutions to create dual credit pathways with high school partners is supported by the results of this study, particularly for low-income students. This is especially important to note as researchers have found uneven access to dual credit courses, with more dual credit course offerings available in schools that have a higher proportion of White students and a lower proportion of low-income students (Taylor & Lichtenberger, 2013). If state and local policymakers and administrative leaders are to take seriously completion agenda goals and the reduction of the achievement gap, such approaches should be considered as possible measures for increasing the odds of postsecondary degree completion for a larger number and greater diversity of students.

Footnotes

Appendix

Description of the Variables.

Variable type	Description
Outcome
Time to Bachelor’s Degree Completion	The number of semesters until bachelor’s degree completion.
Covariates
Gender	Categorical measure of whether a student is male or female; reference male.
Race/Ethnicity	Categorical measure that includes the following: (a) African American, (b) Latino, (c) Asian American, or (d) White; reference White.
High School Program Type	Categorical measure of whether a student described their high school program type as being: (a) college prep, (b) career and technical, or (c) general; reference college prep.
Dual Credit at Community College	Number of semesters a student participated in dual credit via community colleges from the Fall semester of 2000 through the end of the Spring semester of 2003.
Dual Credit at Community College	Number of semesters a student participated in dual credit via 4-year colleges from the Fall semester of 2000 through the end of the Spring semester of 2003.
ACT Subtest Scores	Continuous indicators of performance in ACT English, Mathematics, Reading, and Science.
High School Grade Point Average (GPA)	Ordinal measure of high school GPA that includes: (a) ≤2.4, (b) 2.5-2.9, (c) 3.0-3.4, and (d) ≥3.5; reference ≤2.4.
Core Curriculum	Dichotomous measure of whether a student completed a core high school curriculum as defined by ACT.
AP Participation	A series of dichotomous indicators of whether a student participated in a given AP during high school. The following subjects were included: English, Math, Science, Social Studies, and Foreign Language.
Financial Aid	Dichotomous indicator of whether a student expected to receive financial aid.
Expected to Work	Dichotomous indicator of whether a student expected to work during college.
Number of Siblings	Continuous measure of each student’s number of siblings under the age of 21.
High School Composite ACT	Continuous measure of the mean high school composite ACT score for each high school’s graduating class in 2003.
Selectivity	Dichotomous measure of whether the student’s college was highly selective or less than highly selective; reference highly selective (based on Barron’s, 2003).

Note. ACT = American College Testing; AP = advanced placement.

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.

Author Biographies

Bob Blankenberger is an assistant professor in Public Administration at the University of Illinois at Springfield and a former Deputy Director for Academic Affairs and Student Success at the Illinois Board of Higher Education. His publications focus on education policy, evaluation, and assessment.

Eric Lichtenberger is Deputy Director for Information Management and Research with the Illinois Board of Higher Education and was formerly an Associate Director for Research with the Illinois Education Research Council. He is the author of several publications related primarily to education policy, and postsecondary degree completion.

M. Allison Witt is a teaching assistant professor at the University of Illinois at Urbana-Champaign and Interim Director of the Office of International Programs for the College of Education. Her research is focused on globalizing teacher education, and education policy. She is the author of Shifting Tides in Global Higher Education.

Doug Franklin is an Accreditation Coordinator for the College of Business at the University of Illinois at Springfield. His research is focused on higher education and assessment and includes articles in Community College Review and Journal of Community College Research and Practice.

References

Alon

Tienda

(2005). Assessing the “mismatch” hypothesis: Differences in college graduation rates by institutional selectivity. Sociology of Education, 78, 294-315.

B. P.

(2013). The impact of dual enrollment on college degree attainment: Do low-SES students benefit? Educational Evaluation and Policy Analysis, 35, 57-75.

B. P.

(2015). The role of academic motivation and engagement on the relationship between dual enrollment and academic performance. The Journal of Higher Education, 86, 98-126.

Attewell

Lavin

Domina

Levey

(2006). New evidence on college remediation. Journal of Higher Education, 77, 886-924.

Bailey

T. R.

Hughes

K. L.

Karp

M. M.

(2003). Dual enrollment program: Easing transitions from high school to college (Community College Research Center Brief, No. 17). New York, NY: Teachers College, Columbia University. Retrieved from http://ccrc.tc.columbia.edu/Publication.asp?UID=86

Barron’s. (2003). Profiles of American colleges. Woodbury, NY: Barron’s Education Series, Inc.

Bastedo

M. N.

Jaquette

(2011). Running in place: Low-income students and the dynamics of higher education stratification. Educational Evaluation and Policy Analysis, 33, 318-339.

Blankenberger

Phillips

(2016). Performance funding in Illinois higher education: The roles of the completion agenda, budget environment, and interest group dynamics in the process. Educational Policy, 30, 884–915. doi:10.1177/0895904814556748

Bowen

W. G.

Chingos

M. M.

McPherson

M. S.

(2009). Crossing the finish line. Princeton, NJ: Princeton University Press.

10.

Buckley

Westerland

(2004). Duration dependence, functional form, and corrected standard errors: Improving EHA models of state policy diffusion. State Politics & Policy Quarterly, 4, 94-113.

11.

Burchinal

McCartney

Steinberg

Crosnoe

Friedman

S. L.

McLoyd

Pianta

(2011). Examining the Black-White achievement gap among low-income children using the NICHD study of early child care and youth development. Child Development, 82, 1404-1420.

12.

Carnevale

Smith

Strohl

(2010). Help wanted: Projections of jobs and education requirements through 2018. Washington, DC: Georgetown University Center on Education and the Workforce.

13.

Chen

C. K.

(2010). Analyzing student learning outcome: Stratified Cox proportional hazards model. International Journal of Technology, Knowledge & Society, 6, 167-178.

14.

College Board. (2011). About the agenda: Continuing the conversation. Retrieved from http://completionagenda.collegeboard.org/conversation

15.

Collins

M. L.

(2009). Setting up success in developmental education: How state policy can help community colleges improve student outcomes. Boston, MA: Jobs for the Future.

16.

Common Core State Standards Initiative. (2014). Standards in your state. Retrieved from http://www.corestandards.org/standards-in-your-state/

17.

Condron

D. J.

(2009). Social class, school and non-school environments, and Black/White inequalities in children’s learning. American Sociological Review, 74, 683-708.

18.

Conley

D. T.

(2005). College knowledge: What it really takes for students to succeed and what we can do to get them ready. San Francisco, CA: Jossey-Bass.

19.

Conley

D. T.

(2007). Redefining college readiness (Prepared for the Bill and Melinda Gates Foundation). Eugene, OR: Educational Policy Improvement Center.

20.

Conley

D. T.

(2010). College and career ready: Helping all students succeed beyond high school. San Francisco, CA: Jossey-Bass.

21.

Cortes

K. E.

(2010). Do bans on affirmative action hurt minority students? Evidence from the Texas top 10% plan. Economics of Education Review, 29, 1110-1124.

22.

Cox

D. R.

(1972). Regression models in life tables. Journal of the Royal Statistical Society, 34, 187-220.

23.

DesJardins

S. L.

Ahlburg

D. A.

McCall

B. P.

(1999). An event history model of student departure. Economics of Education Review, 18, 375-390.

24.

Fischer

M. J.

Massey

D. S.

(2007). The effects of affirmative action in higher education. Social Science Research, 36, 531-549.

25.

Fletcher

Tienda

(2010). Race and ethnic differences in college achievement: Does high school attended matter? The ANNALS of the American Academy of Political and Social Science, 627, 144-166.

26.

Ford

D. Y.

Grantham

T. C.

Whiting

G. W.

(2008). Another look at the achievement gap: Learning from the experiences of gifted Black students. Urban Education, 43, 216-239.

27.

Fordham

Ogbu

(1986). Black students’ school success: Coping with the “burden of ‘acting White.’” The Urban Review, 18, 176-203.

28.

Fryer

R. G.

Levitt

S. D.

(2004). Understanding the Black-White test score gap in the first two years of school. The Review of Economics and Statistics, 86, 447-464.

29.

Geise

M. J.

(2011). A longitudinal analysis of outcomes associated with Ohio’s postsecondary enrollment options program. Retrieved from http://etd.ohiolink.edu/view.cgi/Geisepercent20Marypercent20Jo.pdf?bgsu1300423012

30.

Gutman

L. M.

Sameroff

A. J.

Eccles

J. S.

(2002). The academic achievement of African American students during early adolescence: An examination of multiple risk, promotive, and protective factors. American Journal of Community Psychology, 30, 367-399.

31.

Han

Ganges

T. W.

(1995, April). A discrete-time survival analysis of the educational path of specially admitted students. Paper presented at the annual meeting of the American Educational Research Association, San Francisco, CA. (ERIC Document Reproduction Service No. ED387033)

32.

Hanushek

E. A.

Rivkin

S. G.

(2009). Harming the best: How schools affect the Black-White achievement gap. Journal of Policy Analysis and Management, 28, 366-393.

33.

Harnisch

(2011). Performance-based funding: A re-emerging strategy in public higher education financing. Washington, DC: American Association of State Colleges and Universities.

34.

Hoffman

(2012). Why dual enrollment? New Directions for Higher Education, 2012(158), 1-8.

35.

Hoffman

Vargas

Santos

(2008). Blending high school and college: Rethinking the transition. New Directions for Higher Education, 2008(144), 15-25. doi:10.1002/he.322

36.

Horn

Carroll

C. D.

(2006). Placing college graduation rates in context: How 4-year college graduation rates vary with selectivity and the size of low-income enrollment (Postsecondary Education Descriptive Analysis Report NCES 2007-161). Washington, DC: National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education.

37.

Howerter

W. L.

(2011, May). The impact of credit-based transition programs on changing the educational aspirations of high school seniors. Retrieved from http://hdl.handle.net/2142/24096

38.

Huff

K. L.

Fang

(1999). When are students most at risk of encountering academic difficulty? A study of the 1992 matriculants to US medical schools. Academic Medicine, 74, 454-460.

39.

Hunt

Carroll

C. E.

(2006). Florida’s dual enrollment initiative: How state policy influences community colleges’ service to underrepresented youth. New Directions for Community Colleges, 2006(135), 39-47.

40.

Illinois Board of Higher Education. (2008). Illinois public agenda for college and career success. Retrieved from http://www.ibhe.state.il.us/masterPlanning/

41.

Illinois Board of Higher Education. (2010). Finance study commission report. Retrieved from http://www.ibhe.org/SJR88/default.htm

42.

Illinois Board of Higher Education. (2011a). Setting a context for fiscal year 2013 budget development. Retrieved from http://www.ibhe.state.il.us/Fiscal%20Affairs/archives.htm

43.

Illinois Board of Higher Education. (2011b). Underrepresented groups report. Retrieved from http://www.ibhe.state.il.us/URG/default.htm

44.

Illinois Board of Higher Education. (2014). Setting a context for fiscal year 2016 budget development. Retrieved from http://www.ibhe.org/Fiscal%20Affairs/budget.htm

45.

Illinois Community College Board. (2006). P-16 initiative grant funding final report summary. Retrieved from http://www.iccb.org/iccb/wp-content/pdfs/reports/P-16_Grant_Report_FY2006.pdf

46.

Illinois General Assembly. (2009). Illinois Dual Credit Quality Act. Retrieved from http://www.ibhe.org/Academic%20Affairs/p20.htm

47.

Illinois General Assembly. (2013). Senate Resolution 431. Retrieved from http://www.ilga.gov/legislation/98/SR/PDF/09800SR0431lv.pdf

48.

Illinois General Assembly. (2012). The status of SB 3244. Retrieved from http://www.ilga.gov/legislation/billstatus.asp?DocNum=3244&;GAID=11&GA=97&DocTypeID=SB&LegID=64294&SessionID=84

49.

Illinois P-20 Council. (2012). About us. Retrieved from http://www2.illinois.gov/gov/P20/Pages/About.aspx#goal

50.

Illinois State Board of Education. (2014). Agency budget information. Retrieved from http://www.isbe.net/budget/

51.

Johnstone

D. B.

(1993). Learning productivity: A new imperative for American higher education: Studies in public higher education #3. Albany: State University of New York.

52.

Jones

B. S.

Branton

R. P.

(2005). Beyond logit and probit: Cox duration models of single, repeating, and competing events for state policy adoption. State Politics & Policy Quarterly, 5, 420-443.

53.

Jones

S. J.

(2014). Student participation in dual enrollment and college success. Community College Journal of Research and Practice, 38, 24-37.

54.

Jun

Weare

(2010). Institutional motivations and the adoption of innovations: The case of the government. Journal of Public Administration Research and Theory, 21, 495-519.

55.

Karp

Calcagno

Hughes

Jeong

D. W.

Bailey

(2007). The postsecondary achievement of participants in dual enrollment: An analysis of student outcomes in two states. St. Paul: University of Minnesota, National Research Center for Career and Technical Education. Retrieved from http://ccrc.tc.columbia.edu/Publication.asp?uid=547

56.

Kim

Bragg

(2008). The impact of dual and articulated credit on college readiness and retention in four community colleges. Career and Technical Education Research, 33, 133-158. doi:10.5328/CTER33.2.133

57.

Lichtenberger

E. J.

(2011). Reverse transfer students and postsecondary outcomes: A potential opportunity (IERC 2011-5). Edwardsville, IL: Illinois Education Research Council.

58.

Lichtenberger

Witt

M. A.

Blankenberger

Franklin

(2014). Dual credit/dual enrollment and data driven policy implementation. Journal of Community College Research and Practice, 38(11), 959-979.

59.

Light

Strayer

(2000). Determinants of college completion: School quality or student ability? The Journal of Human Resources, 35, 299-332.

60.

Massey

D. S.

(2006). Social background and academic performance differentials: White and minority students at selective colleges. American Law and Economics Review, 8, 390-409.

61.

Melguizo

(2008). Quality matters: Assessing the impact of attending more selective institutions on college completion rates of minorities. Research in Higher Education, 49, 214-236.

62.

National Center for Education Statistics. (2011a). The nation’s report card: Civics 2010 (NCES 2011–466). Washington, DC: Institute of Education Sciences, U.S. Department of Education.

63.

National Center for Education Statistics. (2011b). The nation’s report card: U.S. history 2010 (NCES 2011–468). Washington, DC: Institute of Education Sciences, U.S. Department of Education.

64.

National Center for Education Statistics. (2012). National postsecondary student aid study 2011-12. Retrieved from http://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2013165

65.

National Student Clearinghouse. (2016). Frequently asked questions. Retrieved from http://www.studentclearinghouse.org/about/clearinghouse_facts.php

66.

Niu

S. X.

Tienda

(2008). Choosing colleges: Identifying and modeling choice sets. Social Science Research, 37, 416-433.

67.

Niu

S. X.

Tienda

Cortes

(2006). College selectivity and the Texas top 10% law. Economics of Education Review, 25, 259-272.

68.

Oates

G. L.

(2009). An empirical test of five prominent explanations for the Black–White academic performance gap. Social Psychology of Education, 12, 415-441.

69.

Ochoa

(2011). Renewing the American dream: The college completion agenda. Retrieved from http://www.whitehouse.gov/blog/2011/10/05/renewing-american-dream-college-completion-agenda

70.

Organisation for Economic Co-Operation and Development. (2011). Education at a Glance 2011: OECD Indicators. Author. Retrieved from http://www.oecd.org/unitedstates/48678896.pdf

71.

Ortiz

E. A.

Dehon

(2013). Roads to success in the Belgian French community’s higher education system: Predictors of dropout and degree completion at the Université Libre de Bruxelles. Research in Higher Education, 54, 693-723.

72.

Perna

L. W.

(2006). Studying college choice: A proposed conceptual model. In Smart

J. C.

(Ed.), Higher education: Handbook of theory and research (Vol. XXI, pp. 91-157). New York, NY: Springer.

73.

Perna

L. W.

Thomas

S. L.

(2006, July). A framework for reducing the college success gap and promoting success for all. Washington, DC: National Postsecondary Education Cooperative.

74.

Radford

A. W.

Berkner

Wheeless

S. C.

Shepherd

(2010). Persistence and attainment of 2003–04 beginning postsecondary students: After 6 years (NCES 2011-151). Washington, DC: National Center for Education Statistics, U.S. Department of Education. Retrieved from http://nces.ed.gov/pubs2011/2011151.pdf

75.

Russell

(2011). A guide to major U.S. college completion initiatives (A Higher Education Policy Brief). Washington, DC: AASC&U. Retrieved from http://www.aascu.org/uploadedFiles/AASCU/Content/Root/PolicyAndAdvocacy/PolicyPublications/Policy_Matters/College%20Completion%20October%202011.pdf

76.

Schneider

Martinez

Owens

(2006). Barriers to educational opportunities for Hispanics in the United States. In Mitchell

Tienda

(Eds.), Hispanics and the future of America (pp. 179-227). Washington, DC: National Academies Press.

77.

Scott

Kennedy

(2005). Pitfalls in pathways: Some perspectives on competing risks event history analysis in education research. Journal of Educational and Behavioral Statistics, 30, 413-442.

78.

Small

M. L.

Winship

(2007). Black students’ graduation from elite colleges: Institutional characteristics and between-institution differences. Social Science Research, 36, 1257-1275.

79.

Speroni

(2011). High School Dual Enrollment Programs: Are we fast-tracking students too fast? Retrieved from http://files.eric.ed.gov/fulltext/ED527527.pdf

80.

Taylor

J. L.

Lichtenberger

E. J.

(2013). Who has access to dual credit in Illinois? Examining high school characteristics and dual credit participation rates (IERC 2013-4). Edwardsville, IL: Illinois Education Research Council at Southern Illinois University Edwardsville.

81.

Tyson

Darity

Jr. Castellino

D. R.

(2005). It’s not “a Black thing”: Understanding the burden of acting White and other dilemmas of high achievement. American Sociological Review, 70, 582-605.

82.

U.S. Census Bureau. (2013). State & county quickfacts. Retrieved from http://quickfacts.census.gov/qfd/states/17000lk.html

83.

U.S. Department of Education. (2011). College completion toolkit. Washington, DC. Retrieved from http://www.ed.gov/sites/default/files/cc-toolkit.pdf

84.

Walters

S. J.

(2001). What is a Cox model? Hayward Medical Communications. Retrieved from http://www.medicine.ox.ac.uk/bandolier/painres/download/whatis/COX_MODEL.pdf

85.

Wang

(2009). Baccalaureate attainment and college persistence of community college transfer students at four-year institutions. Research in Higher Education, 50, 570-588.

86.

Yeung

J. W.

Pfeiffer

K. M.

(2009). The Black-White test score gap and early home environment. Social Science Research, 38, 412-437.