College-level Learning in High School and Post-Secondary Academic Success, Presented at the National...
Transcript of College-level Learning in High School and Post-Secondary Academic Success, Presented at the National...
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College-level Learning in High School and Post-Secondary Academic Success
Presented By:
Dion Daly, Ph.D., Assistant Professor
D’Youville College
Buffalo, NY 14201
Paper presented at the annual meeting of the Association for the Study of Higher
Education in Indianapolis, Indiana November 18, 2010
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Abstract
The purpose of this study was to assess the impact of college-level learning in high
school on the post secondary academic success of first term, full time freshman (FTFT)
students. The study employed an analysis of admission and transcript data of FTFT
students who began their undergraduate studies from the fall of 1999 to the fall of 2006.
A group of 269 FTFT students who had earned at least one credit of college-level
coursework while in high school (CLLHS) were compared to a randomly selected sample
of 269 FTFT students who had no CLLHS credits. The groups were compared by
gender, race, socio-economic status (SES), high school average, SAT score, first-
semester college GPA, total number of college credits accumulated by the fourth
semester, cumulative college GPA by the fourth semester , and persistence to the fourth
semester. Descriptive statistics (measures of dispersion, indices of centrality), bivariate
strategies (crosstabulation, correlation), and multivariate procedures (ANOVA,
ANCOVA, Pearson Chi-Square) were utilized to compare these two groups. Results
indicated that, after controlling for academic achievement (high school average and SAT
score), students with CLLHS credits achieved a statistically significant higher mean first
semester GPA than those without CLLHS credits. Moreover, students with CLLHS
credits earned a statistically significant higher mean cumulative GPA by the fourth
semester, accumulated a statistically significant higher mean number of total credits by
the fourth semester, and were found to persist at a higher but not statistically significant
mean rate than students with no CLLHS credits. Consequently, the results of the data
analysis of this study suggested that the existence of CLLHS credits had an overall
positive impact on the post secondary academic success of these first term, full time
students.
Introduction
A defining characteristic of the American system of higher education is that it is heavily
controlled by local forces (Peng, 2003). There is no federal ministry of education with the
power to charter institutions, demand accountability, pool resources, certify teacher
training standards, or approve a common curriculum (Trow, 1989). Higher education in
the United States struggles to maintain its institutional integrity in an environment of
eroding public trust, ever increasing costs, uneven demographics, and diminishing
revenues (Johnstone, 1993). Martin Trow (1989) states that American colleges have
grown to resemble living organisms which are heavily influenced by market forces, and
who face “malnutrition at the margin” (p. 575) as they compete for resources, in an
environment where they must be highly sensitive to local demands or face extinction in a
ruthless game of survival. In addition to maintaining their viability, American colleges
face an ever present pressure for growth in students, courses, physical space, and esteem
(Johnstone, 1993). The rising costs and scarcity of revenues in this competitive high
stakes game has forced educators to look acutely at the educational system as a whole to
find new ways of facilitating the timely, efficient, and successful movement of students
from the high schools to the colleges (Barnes, 2001). The lack of cohesiveness between
these two main educational levels often prevents students from using their senior year to
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adequately prepare for college-level study (Boswell, 2001) and a key component to this
lack of preparation centers around the rigor of the high school curriculum (Peterson,
2003).
Rigor of the High School Curriculum and “Senioritis”
According to Adelman (1999, 2006), the strongest predictor of bachelor’s degree
completion is the intensity of a student’s high school curriculum. But, there is a large and
growing body of literature suggesting that the rigor of the high school curriculum,
especially in the senior year, is severely lacking (cf., Adelman, 1999, 2006; Barth, 2001;
Haycock, Barth, Mitchell, & Wilkins, 1999; Kirst, 2001; National Commission on the
High School Senior Year, 2001; Peterson, 2003; Wilbur & Chapman, 1978). Since the
1970s, there has been a dramatic rise in the percentage of high school seniors who
compete most of their required coursework by the end of their junior year and then who
idle by their senior year (Wilbur & Chapman, 1978). In addition, post-secondary
institutions, who find themselves in an ever increasing competition for these students,
engage in early acceptance programs after the junior year of high school and maintain
admissions calendars that provide few incentives for high school seniors (Kirst, 2001).
Thus, the “best and the brightest” college-bound students now know that the serious
preparation for college ends at the junior year of high school (National Commission on
the High School Senior Year, 2001). For these best students, schools may offer an array
of AP courses or simply seek to tread water and maintain the status quo during the senior
year (Dreis & Rehage, 2008). The National Commission on the High School Senior Year
(2001) has gone as far as to state that the senior year of high school is akin to nothing
more than a “waste of time” (p. 16) and, as a result, the senior-year grade point average
has become practically irrelevant. The result is that many capable high school seniors
lose interest in school (Kirst, 2001; National Commission on the High School Senior
Year, 2001). These students routinely ignore academic demands and they view studying
as irrelevant as they anxiously wait for graduation (National Commission on the High
School Senior Year, 2001).
In addition to students not being academically challenged during their senior year, many
of them were not adequately preparing for college in the first place (Peterson, 2003).
Almost three-quarters of graduating seniors enter some form of post-secondary education
each year yet only about 50% of these students have completed at least a mid-level
college preparatory curriculum consisting of four years of English, three years of science,
three years of math, and three years of social studies (Barth, 2001). The end result of
these pressures is a large and growing number of high school seniors who are not
adequately prepared to succeed at the post-secondary level (Conley, 2005: Kirst, 2008).
Some schools recognize the deficiencies of students and attempt to use the senior year as
a last ditch effort to address them but these efforts all result in, at best, limited success
(Dreis & Rehage, 2008).
The relationship between a rigorous high school curriculum and success in post-
secondary education applies not just to the top academic achievers; it holds true for the
middle and low academic achievers as well (Adelman, 1999). Students of all academic
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abilities view the last year of high school as a time that has been earned for nonacademic
pursuits (Kirst, 2001). For the best students, the slump begins the day after they are
accepted by an early admissions program at a prestigious college, for the average student,
the slump begins right after they have completed their college applications, and for the
low academically able student, because of open college admission policies, the slump
begins the moment they feel confident that they will graduate (Kirst, 2001). The “senior
slump” is then not just a byproduct of the most academically gifted students; it has
become a component of the entire American high school culture (Kirst, 2001). One
consequence of the “senior slump” is the growing number of students who must take
remedial courses at the post-secondary level (Peterson, 2003). Having to repeat topics in
college that were already covered in high school wastes time and money and increases
the effect of the curricular overlap between the last two years of high school and the first
two years of college (Peterson, 2003).
Duplication of the Secondary and Post-secondary Curriculum
There is a large amount of evidence of curriculum duplication between the last two years
of high school and the first two years of college (Carnegie Commission on Higher
Education, 1973; Greenberg, 1988). Since the 1950s, secondary schools have encouraged
their academically able students to take rigorous courses early as a means to stimulate
and maintain an intellectual bearing (Greenberg, 1982). The result was that the senior
year became a wasted period and students increasingly found that they were not
adequately prepared for academic work (Greenberg, 1982). In response to parental
concerns that the school provide students with a rigorous curriculum in preparation for
college-level work, the high schools began enriching the curriculum by offering more
advanced courses (Wilbur & Chapman, 1978). This had the effect of improving
educational statistics and quieting the critics (Gemma, 2004). But, because K-12 and
higher education faculty and administrators rarely meet with each other (National
Commission on the High School Senior Year, 2001), a negative outcome of this response
was an increase in the likelihood of course duplication between the secondary and post-
secondary educational levels (Gemma, 2004; Wilbur & Chapman, 1978).
There is a striking and readily apparent disconnect (Boswell, 2001) or disjuncture (Kirst,
2001) between high school graduation standards and college admission requirements. To
date, except for the Advanced Placement (AP) program, there are no major, large-scale,
coordinated attempts to provide either sequencing of courses or curricular cohesiveness
between the senior year of high school and the first two years of post-secondary
education (Kirst, 2001). Kirst (2001) has called the current scene a “Babel of standards
rather than a coherent strategy” (p. 5). The Carnegie Commission, in its report, Less
Time, More Options Education Beyond the High School (1971), suggested that the
amount of course duplication was so great that it recommended the secondary school be
accredited to provide the curriculum equivalent to the first year of college. Despite the
fact that there have been no attempts to replicate the work of this Commission since
1971, it still serves as a collection of remarkably refreshing and relevant solutions to
today’s problems (Aubrey, 2005).
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The overlapping curriculum between the last two years of high school and the first two
years of college occurs mainly in the subject area of general education (Kirst, 2001).
Although there is duplication of the general education requirements between the
secondary and post-secondary educational levels, these efforts are inadequate and
inefficient because neither level specifically maintains ownership of those requirements
(Boyer & Levine, 1981). The lack of ownership of the problem and the lack of a
comprehensive strategy, results in an educational environment that resembles, not a
continuous path of cohesively integrated curriculum, but rather an “eclectic academic
muddle” (Orrill, 2001, p. 84). Parents, students, and educators are attempting to find
ways through this miasma of overlapping curriculum and lack of rigorous preparation and
one of the most promising, controversial, and popular approaches is the use of college-
level learning in high school. This study examined this growing phenomenon.
Statement of the Problem
The Literature suggests that the strongest predictor of post-secondary academic success is
the intensity of a student’s pre-collegiate history (Adelman, 1999, 2006). But, the ability
of the American school system to provide an intense pre-collegiate history is being
hampered by a lack of curricular cohesiveness between the secondary and post-secondary
levels (c.f., Carnegie Commission on Higher Education, 1973; Greenberg, 1988, Kirst,
2001, National Commission on the High School Senior Year, 2001) and a lack of a
universal systematic and coherent curricular strategy (Orrill, 2001). Increasingly, the
curricular options available to the average American high school student, especially in
the senior year, are limited (Peterson, 2003), inadequate, and inefficient (Boyer &
Levine, 1981).
The promise of college-level learning in high school programs is that they can increase
the intensity of the high school curriculum which will then lead to an enhancement of the
student's college academic success (Chapman, 2001). But, there is not a lot of evidence
that this promise is being fulfilled (Porter, 2003) and few programs can claim "solid
evidence of systematic or sustained success" of their efforts (Fleischman & Heppen,
2009, p. 105). Johnstone and Del Genio (2001) state that “college-level learning in high
school is a rapidly growing, yet remarkably little-studied phenomenon” (p. 9). A review
of the current literature shows few attempts to examine outcomes using comprehensive
data sets and rigorous statistical methods and few attempts take into account independent
variables that may affect student academic success other than the presence of college-
level learning in high school (Karp, Calcagno, Hughes, Jeong, & Bailey, 2007).
Although it is assumed that exposing high school students of all academic abilities to
college-level coursework can result in post-secondary academic success, there is little
research, from either state or regional data to support this notion (Swanson, 2010). It is
clear that outcomes research on the effects of college-level learning in high school
programs is very much lacking (Bailey & Karp, 2003). This has lead to a large amount of
criticism (Klein, 2007) with the main areas of concern being curricular rigor,
transferability of earned credits, funding issues, and assessment data (Swanson, 2010).
State and local policy makers have been increasingly implementing dual enrollment
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programs but they vary greatly on a number of key issues (Fleischman & Heppen, 2009)
and the college-level learning in high school phenomenon is growing quicker than the
development of policies to ensure curricular quality (Barnes, 2001). The lack of outcomes
research, coupled with the explosive growth of these programs, provided a number of
possible research designs on the effectiveness of college-level learning in high school
programs.
Purpose of the Study
The purpose of this study was to investigate how college-level learning in high school
may be related to post-secondary academic success. It sought to examine the relationship
between college-level learning in high school and post-secondary academic success as
measured over multiple college semesters.
Research Question
The purpose of this study yielded one research question: Are their significant differences
in post-secondary academic success of students who vary by gender, race, socio-
economic status, type of college-level learning in high school, high school average, and
SAT score? Post-secondary academic success was measured using the following
dependent variables: First-Semester College GPA; Cumulative College GPA; Total
Number of Cumulative Credit Hours Competed; Number of Semesters in Attendance. To
determine the main effects on the dependent variables, the following independent
variables were employed: Gender; Race; Socio-economic Status; Type of College-level
Learning in High School credits; High School Average; SAT Score.
Significance of the Study
This study is significant in a number of ways. First, it adds to the limited number of
studies tracking post-secondary academic success of students with dual/concurrent
enrollment learning in high school. Porter (2003) has stated that there is a need for
information about how well students with dual/concurrent enrollment credits perform in
their post-secondary endeavors. Second, this study is significant because it tracks the
academic success of students over multiple college semesters. DiPuma (2002) has stated
that there are few studies that have focused on the post-secondary academic success of
students with dual/concurrent enrollment credit over more than a few semesters. Third,
this study can provide some quantifiable evidence that dual/concurrent enrollment
programs can exist as a viable college access strategy by “leveling the playing field” for
low achieving and underrepresented groups. Rocheford, O’Neill, and Gelb (2009) state
that an underlying belief in dual enrollment programs is that all students can successfully
complete college level course work while in high school and that this belief is a
paramount ingredient in the recipe of growth for these programs.
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Definition of Key Terms and Variables
For the purpose of this study, the following definitions will be used throughout
this document:
College-Level Learning in High School: Is defined as any program that offers
students the opportunity to participate in courses that are “college-like” or “college-level”
while they are still in high school (Karp, Bailey, Hughes, & Fermin, 2004). These
courses may be actual college courses (the successful completion of which guarantees the
accumulation of college credits) or they can be courses that have an increased curricular
rigor over regular high school courses (the successful completion of which has the
potential to lead to the accumulation of college credits) (Boswell, 2001).
Dual/Concurrent Enrollment: Is defined as any college-level learning in high
school program that allows for high school students to participate in actual college
courses and, once they successfully complete the course/s, be guaranteed the
accumulation of college credits (Hébert, 2001).
"Post-secondary Academic Success" is defined as a student's academic
performance as measured by the following variables:
First-Semester College GPA: This variable indicates students' post-secondary
grade point average, counting grades from any course completed at the College by the
end of the first semester in attendance and ranging on a scale of 0 - 4.0.
Cumulative College GPA: This variable indicates students' post-secondary grade
point average, counting grades from any course completed during the first semester in
attendance and each semester thereafter up to, and including, either the fourth semester or
the last semester in attendance at the College, whatever comes first, and ranging on a
scale of 0 - 4.0.
Total Number of Cumulative Credit Hours Competed: This variable indicates the
total number of credit hours attained by a student from the student’s first semester in
attendance and each successive semester thereafter up to, and including, either the fourth
semester or the last semester in attendance at the College, whatever comes first. This
variable includes all credits accepted by the College for each student as shown on the
student's official transcript and expressed in whole numbers.
Number of Semesters in Attendance: This variable indicates the total number of
semesters in attendance starting from the student’s first semester in attendance and each
successive semester thereafter up to, and including, either the 4th
semester in attendance
or last semester in attendance, whatever came first, and expressed in whole numbers from
1 to 4.
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Context
This study utilized data collected from students who enrolled as first term, full time
students at D’Youville College, a small private urban college located in Buffalo, NY.
D’Youville College is an independent private institution of higher education with a
Catholic tradition that offers baccalaureate, graduate, first-professional, and doctoral
degree programs to students of all faiths, cultures, and backgrounds (D’Youville College
Calendar Resource Guide Planner, 2009). The College currently enrolls over 3,100 total
students (93% of which receive some form of financial aid), has a large Canadian
population (about 31% of all enrollments), and has a number of international students
from other countries. Despite this focus on international students, particularly in its
graduate, first professional, and doctoral programs, the overwhelming majority of its
undergraduate students originate from high schools located in New York state (D.
Lyman, personal communication, October, 18, 2010). Due, in part, to the College’s
history and emphasis on nursing and health related fields, it enrolls undergraduate female
students (75.4%) at a rate about three times that of undergraduate male students (24.6%)
(IPEDS, 2008). In addition, the undergraduate population is composed of more than four
times the number of White students (63%) than Black students (15%), and graduates just
over two-thirds (68%) of all undergraduate students within five years (IPEDS, 2008).
It is important to note that although D’Youville College is a small private institution, it
prides itself on admitting students who would have otherwise not been accepted to a
private college. It is a school with a selective admissions policy that also maintains a
number of admission pathways for students with less than stellar academic credentials.
The result of these pathways can be witnessed in the average SAT score of its entire
incoming freshman student body which hovers, from year-to-year, between 1010 and
1020 and an average incoming freshman high school average between 88 and 90 (D.
Lyman, personal communication, October, 18, 2010). Because the promise of CLLHS
programs is that they can increase access to those students “just below” the top students
(Hugo, 2001), the nature of the D’Youville College freshman student body made for an
ideal population for this study.
Theoretical Framework
Prior research has identified a significant positive relationship between the intensity of a
student’s pre-collegiate academic preparation and post-secondary academic success that
is stronger than for other variables such as gender, race, family composition, and
socioeconomic status (c.f., Alexander & Palis, 1984; Alexander, Riordan, Fennessey, &
Pallas, 1982; Thomas, Alexander & Eckland, 1979). In an effort to, in part, study this
phenomenon more closely, Adelman (1999, 2006) created an index he termed “Academic
Resources”. This index consisted of the three elements of curricular intensity, academic
performance (class rank/GPA), and an external measure of general learned abilities in the
form of a performance test (i.e., SAT, ACT, or other equivalents). His analysis, in part,
discovered that, of these three variables, the intensity of the high school curriculum had
the strongest association with bachelor’s degree attainment, for all students in general and
for African American and Latino students in particular. In a similar study, Pike and Saupe
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(2002) used the three variables of high school curriculum, class rank, and ACT test score
to predict students’ first-year college GPA. They found the relationship between a
student’s first-year college GPA was statistically significant and more strongly correlated
with the high school curriculum than either class rank or ACT test scores which implied
that increasing the intensity of the high school curriculum could have positive effects on
post-secondary academic performance.
Some skeptics argue that students in high school are not adequately prepared to complete
college-level work in terms of cognitive and maturation levels. Despite these few critics,
it is generally believed that students desire to practice adult behaviors and that, for proper
adolescent development, students must be provided with opportunities to assume roles
and responsibilities like an adult (Erikson, 1968). College-level learning in high school
programs provide for high school students to assume the role of the more mature
traditional college-aged student. In addition, it is believed that at risk behaviors diminish
as educators increase responsibility and expectations of students (Bernard, 1991). An
increase in responsibility and expectations is tied to an increase in curricular rigor which
is a main underlying tenant of college-level learning in high school programs.
Fleishman & Heppen (2009) articulate five desired outcomes of school reform and state
that dual enrollment programs seek to achieve student success via all five of them. These
outcomes provide clues as to the underlying theory of such efforts. First, the program
must maintain a personalized and orderly environment. Second, is for the program to
have the capability to help students who have poor academic skills. Third, is an ongoing
improvement of instructional focus and effective practice (i.e., ensuring that the teachers
in such programs are both well-prepared as well as experienced). Fourth, is the capacity
to prepare students for life after high school (whether it be to get a job or to continue into
post-secondary education). Fifth, is to create positive change in complex and overstressed
school systems. Such efforts can exist in any high school but are of paramount
importance in the schools with the poorest students.
It has traditionally been assumed that low-achieving students are, by definition, not
prepared for college level work (Jordan, Cavalluzzo, & Corallo, 2006). Sending the less
prepared students through a more academically rigorous transition program then seems
counterintuitive (Bailey & Karp, 2003). But, according to Adelman (1999, 2006), the
strongest predictor of bachelor’s degree completion, among all groups and abilities of
students, is the academic intensity of a student’s pre-collegiate history, and it is this one
variable that can most contribute to the narrowing of degree completion gaps among all
these groups. The promise of college-level learning in high school programs is that they
can smooth the transition for a broad range of students by better preparing them for
college-level work which will in turn facilitate both access to and success in post-
secondary education (Bailey & Karp, 2003).
Method of Inquiry
Data for this study consisted of first term, full time (FTFT) freshman. In order to
determine the possible effects of CLLHS, two groups were formed and then compared,
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those with CLLHS credits (n = 269) and those with no CLLHS credits (n = 269). The
existence of CLLHS credits was considered a defining variable (i.e., the student earned
an acceptable grade or score for the course to be accepted by the college for credit).
Students with CLLHS credits were assumed to have an exposure to a greater pre-
collegiate curricular intensity than students with no CLLHS credits. These two groups
where then compared with rigorous statistical procedures over multiple college
semesters. It is important to note that, although the sample was relatively low, one value
of this study is its identification of the sample. Students with CLLHS credits are typically
“invisible” in the student databases of post-secondary institutions (because the CLLHS
credits show as transfer credits not credits earned while in high school) and as such,
comparisons of this nature are difficult, if not impossible to conduct in many instances.
Data Collection Procedures
This study employed data derived from two sources. The first source was the College’s
student database and the second source was individual student files (paper copy). A query
of the student database provided all the collected data elements with the exception of
“CLLHS Credits”. This data item was not available for query in the College’s database so
it had to be extracted via transcript analysis of the official college transcript/s located in
the students’ official files. The data derived from this transcript analysis was added to the
initial query to form an ancillary dataset. The ancillary dataset was the source of all data
used for statistical manipulation and analysis for this study.
Like most institutions of higher education (Karp, Calcagno, Hughes, Jeong, & Bailey,
2007) the College does not maintain in its database data elements that can identify all
students with college-level learning in high school credits. This study identified students
with college-level learning in high school credits via transcript analysis. The initial query
of 1546 cases was divided between those cases with transfer credits and those with no
transfer credits. This action resulted in 1028 cases of students with no transfer credits
(i.e., no possible CLLHS credits) and 518 cases of students with transfer credits (i.e.,
possible CLLHS credits). Individual student paper-copy files were examined for all of
these 518 cases to determine if the students had college-level learning in high school
credits. The completion date of every transfer course was compared to the student’s high
school graduation date and any college credits earned prior to that date where considered
CLLHS credits.
The result of these procedures was to identify 269 total cases of students with some form
of college-level learning in high school credits (59 Advanced Placement only, three
International Baccalaureate only, one AP and IB, 24 AP and Dual Enrollment, and 182
Dual Enrollment Only). This group was entitled “Students with CLLHS Credits”. A
second group was then created by taking a random sample of 269 cases from the
available population of 1277 FTFT freshman students with no form of college-level
learning in high school credits. This group was entitled “Students with No CLLHS
Credits”.
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Data Analysis
This study employed an evaluation design and involved a descriptive ex post facto
analysis that attempted to derive conclusions (comparisons of groups to one or more
variables) from quantitative data. It followed a deductive research process and involved
the collection of data from mixed sources in order to identify statistical relations to
variables. All collected data was entered and coded into the Statistical Package for the
Social Sciences (SPSS, Version 16.0) software which was then utilized to run all
analysis. The data collected was secondary data and transcript data. Secondary data is
data that is already collected and maintained in a database (Rosenberg, Greenfield, &
Dimick, 2008). Desired data elements that were not in the existing data base were
collected via transcript analysis and coded into the secondary data set to form an ancillary
data set. This ancillary data set formed the basis of all statistical procedures employed in
this study.
The research question for this study was: Are their significant differences in post-
secondary academic success of students who vary by gender, race, socio-economic status,
type of college-level learning in high school, SAT score, and high school average? The
statistical methods that were employed to answer this question were descriptive statistics
(i.e., measures of dispersion, indices of centrality), bivariate strategies (i.e.,
crosstabulation, correlation), and multivariate procedures (i.e., ANOVA, ANCOVA,
Pearson Chi-Square). Post-secondary academic success was measured using the
following dependent variables: First-Semester College GPA; Cumulative College GPA;
Number of Cumulative Credit Hours Competed; Persistence. The independent variables
were: Gender; Race; Socio-economic Status; Type of College-Level Learning in High
School Credits; SAT Score; High School Average.
Descriptive statistics and measures of dispersion were used to describe and compare
groups because they are techniques that present, in an abbreviated and symbolic fashion,
characteristics of large amounts of data (Sprinthall, 1999). These techniques included
mean, median, mode, frequency, range, standard deviation and variance. The bivariate
measure of crosstabulation was used to discover possible strong relationships between the
categorical variables, with the Pearson Chi Square being utilized to demonstrate if these
relationships were statistically significant. The Pearson Correlation Coefficient was used
to determine the degree and direction of any relatedness between the continuous
variables. ANOVA (t-test equivalent) was used to describe and compare the two groups
(when there are only two means being compared, the T-test and F-test are equivalent
measures and represented by the equation F = t2). In addition, separate three-way, two-
covariate, factorial ANCOVAs of independent samples were used to test the four
dependent variables of First-Semester College GPA, Cumulative College GPA, Total
Number of Cumulative Credit Hours Completed, and Persistence. ANCOVA was used to
test these three dependent variables because it has the ability to assess the “joint
significance of predictors on a continuous dependent variable” and provide “prediction
equations for various levels of a categorical predictor” (Hartman, 2000, p. 2). An alpha
level of .05 level of significance was used for all testing were required.
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Descriptive statistics and frequencies were utilized for all data fields, as collected, to
provide as much detail as possible. Prior to running the crosstabulations, the data field
“Type of CLLHS credits” was collapsed. In specific, the categories of “AP Only”, IB
Only”, "AP and IB", "AP and Dual Credits”, and “IB and Dual Credits” were collapsed
into the category of “Enrichment”. This new data field was called
“Type_CLLHS_Combined” and included three categories: No CLLHS Credits, Dual
Enrollment Credits, and Enrichment Credits.
Because ANOVA and ANCOVA are sensitive to cell numbers under twenty as well as
large variances between cell numbers, two data fields were collapsed prior to running the
ANOVA and ANCOVA testing. First, the data field “Race” was collapsed from the seven
categories of “White”, “Black”, “Hispanic”, “Asian”, “Native American”, “Other” and
“Unknown” to the three categories of “White”, “People of Color” (Black, Hispanic,
Asian, Native American), and “Unknown/Other”. There were a total of seven cases of
“Unknown/Other" race which were filtered out. This new collapsed data field was titled
“Race_Combined”. Second, the six CLLHS categories of “No CLLHS Credits”, “AP
Only”, “Dual Enrollment Only”, “International Baccalaureate Only”, “AP and Dual
Enrollment”, and “AP and International Baccalaureate” were collapsed into the two
categories of “Students with CLLHS Credits” and “Students with No CLLHS Credits”.
This new data field was entitled “CLLHS or Not”.
Descriptive statistics showed a possible meaningful difference in average SAT score for
the group of students with CLLHS credits (M = 1046.62, SD = 135.76) and the group of
students with no CLLHS credits (M = 943.16, SD = 150.658). In addition, descriptive
statistics showed a possible important difference in high school average for those students
with CLLHS credits (M = 90.16, SD = 5.598) and those students with no CLLHS Credits
(M = 84.89, SD = 6.349). A one-way ANOVA (t-test equivalent) revealed that there was
a positive statistically significant difference in SAT scores between the two groups, F
(1,536) = 70.005, p < .001. In addition, a one-way ANOVA (t-test equivalent) revealed a
positive statistically significant difference in high school average between the two
groups, F (1,536) = 104.483, p < .001. This analysis signified that “High School
Average” and “SAT Score” might be possible confounding variables that needed to be
controlled for. Since these two measures were represented as continuous data, they were
controlled for as covariates in the ANCOVA testing.
In order to complete the crosstabulation procedures, the continuous data fields of “High
School Average” and “SAT Score” were transformed into two new categorical fields
each consisting of three groups (high, moderate, low). This transformation was completed
with the goal of creating three groups of relatively equal size within each variable. This
resulted in scores possibly being categorized as "high", "moderate" or "low" within each
variable that would not typically be thought of as high, moderate, or low scores. High
School Average was transformed into the three categories of “Low Academic
Achievers”, “Moderate Academic Achievers”, and “High Academic Achievers”. These
three groups were created such that there was a clear cut-off from the last score in one
group to the first score in the next with no single score residing in more than one group.
As a result of these procedures, “Low Academic Achievers” were labeled as those cases
13
with a High School Average in the range of greater than 60 to less than 85 (n = 183, M =
80.20, SD = 3.841), “Moderate Academic Achievers” were labeled as those cases with a
High School Average in the range of greater than 85 to less than 91 (n = 179, M = 88.03,
SD = 1.938), and “High Academic Achievers” were labeled as those cases with a High
School Average in the range of greater than 91 to equal to 100 (n = 176, M = 94.63, SD =
2.184). This new data field was labeled “HS_AVE_Combined”. Similar procedures were
used to transform the continuous variable of “SAT Score” to one data field with three
categories. These categories were labeled “Low SAT Score”, “Moderate SAT Score”,
and “High SAT Score”. Those cases with an SAT score in the range of 400 – 940 were
categorized “Low SAT Score” (n = 185, M = 826.59, SD = 95.740). Those cases with an
SAT Score in the range of 950 – 1070 were categorized as “Moderate SAT Score” (n =
176, M = 1011.42, SD = 38.851). Those cases with an SAT score in the range of 1080 –
1600 were categorized “High SAT Score” (n = 177, M = 1154.35, SD = 64.082). This
new data field was entitled “SAT_Combined”.
This study attempted to include the data element of socio-economic status into the
statistical analysis but was unable to do so due to incomplete, missing, and undetermined
available information. The data that was obtained for this variable will be presented in the
profile of groups but was not included in the ANCOVA testing because doing so would
have necessitated the lowering of the total number of cases available for statistical
analysis to 259 which would have also resulted in unequal comparison groups.
Due to the lack of research on the effects of college-level learning in high school on post-
secondary academic success that control for possible confounding variables, meaningful
differences between students with CLLHS credits and those without CLLHS Credits,
with regard to First Semester College GPA, Cumulative College GPA, Cumulative
Number of Credit Hours, and Number of Semesters in Attendance, could not be
anticipated by this study prior to running the statistical analysis.
Results
Profile of Groups
A crosstabulation with the variable of “Gender” was completed between the two groups.
The group of students with CLLHS credits was comprised of 79.9% (n = 215) females
and 20.1% (n = 54) males and the group of students with no CLLHS credits consisted of
74.3% (n = 200) females and 25.7% (n = 69) males. These results appeared to be similar
in nature to the overall gender mix of the entire student body and thus a representative
sample of that population with regard to this variable. The frequencies appeared to be
relatively evenly distributed across the crosstabulation matrix and a Pearson Chi-Square,
χ2(1, N = 538) = 2.371, p = .124, suggested that no statistically significant relationship
existed between gender and the existence of CLLHS credits.
Additional comparisons between the two groups were completed to determine any
meaningful variations in race. As shown in Table 1, these numbers indicated that the
groups differed in racial composure. Specifically, the group of students with CLLHS
14
credits contained 16.4% (83.3% minus 66.9%) more White students and 14.9% (21.6%
minus 6.7%) fewer Black students than the group of students with no CLLHS credits.
This indicated that there might be a relationship between race and the existence or non-
existence of college-level learning in high school credits. To examine this relationship
further, the racial categories were collapsed into the two categories of “White” and
“People of Color” (P.O.C.) and a crosstabulation between this combined race data field
and the two groups was completed.
Table 1
Comparison of Students with CLLHS Credits and Students with No CLLHS Credits by
Race
Students with CLLHS Credits Students with No CLLHS Credits
Race Number Percentage of Group Number Percentage of Group
White 224 83.3% 180 66.9%
Black 18 6.7% 58 21.6%
Hispanic 6 2.2% 13 4.8%
Asian 10 3.7% 4 1.5%
Native American 4 1.5% 1 .4%
Other 5 1.9% 8 3.0%
Unknown 2 .7% 5 1.9%
This procedure revealed that P.O.C. students represented the majority of students with no
CLLLHS credits (66.1%) as compared to White students (44.6%) and White students
represented the majority of students with CLLHS credits (55.4%) as compared to P.O.C.
students (33.9%). The frequencies appeared to be relatively unevenly distributed across
the crosstabulation matrix and a Pearson Chi-Square, χ2(1, N = 531) = 18.012, p <.001,
suggested a statistically significant relationship between race and the existence of
CLLHS credits.
To examine race and CLLHS more closely, a crosstabulation was completed between the
collapsed race categories and the group of students with CLLHS credits. White students
represented 82.4% (n = 150) of all students with Dual Enrollment Credits Only and
87.1% (n = 784) of all students with Enrichment Credits. In addition, P.O.C. students
15
accounted for 17.6% (n = 32) of the students with Dual Enrollment Credits Only and
12.9% (n = 11) of the students with Enrichment Credits. The results suggested that,
although it was much more likely for a White student to have some form of CLLHS
credits than a P.O.C. student, there existed a relatively consistent racial distribution
across the categories of types of CLLHS credits, with White students being skewed
toward Enrichment Credits and P.O.C. students being skewed toward Dual Enrollment
Only credits.
Following the same procedure of creating crosstabulations between two variables,
viewing the crostabulation table for relative even frequency distribution across the
matrix, and then utilizing a Pearson Chi-Square to determine statistical significance, a
number of additional results were obtained.
Gender and Race
White students represented 76.8% of all female students (n = 314) and 73.8% (n = 90) of
all male students. Students categorized as People of Color represented 23.3% (n = 95) of
all female students and 26.2% (n = 32) of all male students. A Pearson Chi-Square, χ2(1,
N = 531) = .465, p = .495, suggested that no statistically significant relationship existed
between gender and race.
Gender and High School Average
Female students were evenly represented with regard to high school average with 31.8%
(n = 132) categorized as low high school average, 33.7% (n = 140) categorized as
moderate high school average, and 34.5% (n = 143) categorized as high high school
average. In addition, male students were also evenly represented with a slight skew,
41.5% (n = 51) were categorized as low high school average, 31.7% (n = 39) categorized
as moderate high school average, and 26.8% (n = 33) categorized as high high school
average. A Pearson Chi-Square χ2(2, N = 538) = 4.406, p = .110, implied no significant
relationship existed between gender and high school average.
Race and High School Average
White students were relatively evenly present across the three levels of academic
achievement although skewed toward the moderate (36.1%, n = 146) and high (39.6%, n
= 160) high school average categories with only 24.3% (n = 98) being categorized as
having a low high school average. Students categorized as People of Color were heavily
skewed to the moderate (24.4%, n = 31) and low (63.8%, n = 81) high school average
categories with only 11.8% (n = 15) categorized as having a high high school average. A
Pearson Chi-Square, χ2(2, N = 531) = 71.408, p < .001, implied a possible significant
relationship might exist between the two variables of race and high school average.
16
Race and Type of CLLHS
White students represented 82.4% (n = 150) of all students with Dual Enrollment Credits
Only and 87.1% (n = 784) of all students with Enrichment Credits. In addition, P.O.C.
students accounted for 17.6% (n = 32) of the students with Dual Enrollment Credits Only
and 12.9% (n = 11) of the students with Enrichment Credits. The results may suggest
that, although it was much more likely for a White student to have some form of CLLHS
credits than a P.O.C. student, there existed a relatively consistent racial distribution
across the categories of types of CLLHS credits, with White students being skewed
toward Enrichment Credits and P.O.C. students being skewed toward Dual Enrollment
Only credits.
High School Average and Existence of CLLHS
Students with CLLHS credits had a mean High School Average of 90.16 (SD = 5.598)
and the group of students with no CLLHS credits had a mean High School Average of
84.89 (SD = 6.349). This data indicated that there might be a significant relationship
between high school average and the existence or non-existence of CLLHS credits.
Almost half (46.8%, n = 126) of the students with CLLHS credits were categorized as
having a high high school average and over half (50.9%, n = 137) of the students with no
CLLHS credits were categorized as having a low high school average. A Pearson Chi-
Square, χ2(2, N = 538) = 79.327, p < .001, suggested that a significant relationship existed
between high school average and the existence of CLLHS credits.
SAT Score and Existence of CLLHS
Students with CLLHS credits had a mean SAT score of 1046.62 (SD = 135.76) and the
group of students with no CLLHS credits had a mean SAT score of 943.16 (SD =
150.658). This data indicated that there might be a significant relationship between SAT
score and the existence or non-existence of CLLHS credits. Almost half (46.8%) of the
students with CLLHS credits were categorized as having a high SAT score and almost
half (46.8%) of the students with no CLLHS credits were categorized as having low SAT
scores. A Pearson Chi-Square, χ2(2, N = 538) = 56.408, p < .001, suggested that a
significant relationship existed between SAT score and the existence of CLLHS credits.
High School Average and Type of CLLHS
Just over seven out of every ten (71.3%, n = 62) of the students with enrichment credits
were categorized as having a high high school average and just over five out of every ten
(50.9%, n = 137) of the students with no CLLHS credits were categorized as having a
low high school average. A Pearson Chi-Square, χ2(4, N = 538) = 1.142E2, p < .001,
suggested a significant relationship existed between high school average and type of
CLLHS credits.
17
SAT Score and Type of CLLHS
With regard to SAT score and Type of CLLHS credits, more than seven out of every ten
students (73.6%, n = 64) with enrichment credits were categorized as having a high SAT
score. Dual enrollment students were relatively evenly distributed between the three
categories of SAT score with almost seven out of every ten (65.9%, n = 130) being
categorized as Moderate and Low SAT scores. In addition, almost half (46.8%, n = 126)
of the students with no CLLHS credits were categorized as having a low SAT score. A
Pearson Chi-Square, χ2(4, N = 538) = 1.007E2, p < .001, suggested a significant
relationship existed between SAT score and type of CLLHS credits.
Socio-economic Status
The data for this variable are being presented here but this variable was not included in
further statistical procedures. The data was represented as a categorical variable. Students
were classified as either economically disadvantaged or not economically disadvantaged.
The criterion by which this determination was made was decided by the Office of
Institutional Research and was based on federal reporting guidelines. After the
investigator received the available data, it was decided to remove this variable from
further statistical testing. This decision was made because no data was available prior to
the year 2004 which significantly lowered the total possible sample size to 288 (students
with CLLHS and students without CLLHS combined). Of this number, there were 26
cases of incomplete information and 3 cases of completely missing information which
dropped the available total sample size for statistical analysis to 259 cases.
Of the 259 total cases, 33% of the students (n = 86) had CLLHS credits and were not
economically disadvantaged, 15.1% of the students (n = 39) had CLLHS credits and were
economically disadvantaged, 34.7% of the students (n = 90) had no CLLHS credits and
were not economically disadvantaged, and 17% of the students (n = 44) had not CLLHS
credits and were economically disadvantaged.
First Semester GPA
The data showed a difference in first semester GPA between the groups. Students with
CLLHS credits had a mean first semester GPA (M = 3.067, SD = .635) that was higher
than for students with no CLLHS credits (M = 2.490, SD = .934). There are a number of
things that could account for this difference such as motivation (as measured in high
school average) and ability (as measured in SAT score). The data showed differences
between these two groups on these two variables. Students with CLLHS credits had a
higher mean high school average (M = 90.16, SD = 5.59) than did students with no
CLLHS credits (M = 84.49, SD = 6.35) and a higher mean SAT score (M = 1046.61, SD
= 135.76) than students with no CLLHS credits (M = 943.16, SD = 150.66). A Pearson
Correlation Coefficient showed a strong positive correlation (r = .512, p < .001) between
first semester GPA and High School Average. In addition, a Pearson Correlation
Coefficient showed a moderate positive correlation (r = .373, p < .001) between First
Semester GPA and SAT Score. These results indicated that a higher first semester GPA
18
was related to both a higher SAT score as well as a higher high school average, but the
latter is a stronger relationship.
The difference in first semester GPA between the two groups could then be explained by
either the existence of CLLHS credits, motivation, ability, some other variable (i.e. race,
gender), or some combination of these variables. In order to measure the affect of the
existence of CLLHS credits, an ANCOVA was completed with high school GPA and
SAT score as confounding variables (i.e., covariates), first semester GPA as the
dependent variable, and sex, race, and the existence of CLLHS credits as the independent
variables.
A number of procedures were conducted prior to running the ANCOVA to ensure all
assumptions required of a valid ANCOVA test were met. First, histograms of all the
variables were viewed and they showed relatively normal distributions with slight skews.
Since ANCOVA is relatively robust to violations of normality if the variables are slightly
irregular, it was assumed that this requirement was met. Second, because ANCOVA is
sensitive to cell numbers below twenty, crosstabulations between the variables was
viewed. Based on these viewings, it was decided to use the collapsed race data field (i.e.,
White, People of Color) and the collapsed CLLHS credits data field (i.e., students with
CLLHS credits, students with no CLLHS credits). Third, ANCOVA testing is sensitive to
outlier scores. The data were sorted by each variable and viewed. Due to the bounded
nature of the variables (i.e., GPA ranges from 0 – 4.0, number of semesters in attendance
ranges from 0 to 4), no outliers were found. Fourth, ANCOVA assumes equal variances
in all the groups (Norušis, 2008). ANCOVA results can be assumed to be relatively
accurate if the variance ratio is no more than 4:1 (Moore, 1995 as cited in Norušis, 2008).
A hand calculation was completed for each of the groups and none violated this ratio.
Based on the results of these pre-testing procedures, it was concluded that the subsequent
ANCOVA test would meet all required assumptions.
The results of the ANCOVA showed that race and gender were not significantly related
to first semester GPA but the existence of CLLHS credits was found to be significantly
related to first semester GPA. These results are similar to other studies that indicate a
student’s academic background is far more important with regard to post-secondary
academic success than demographic variables such as gender and race (c.f., Adelman,
1999, 2006; Alexander & Palis, 1984; Alexander, Riordan, Fennessey, & Pallas, 1982;
Thomas, Alexander & Eckland, 1979). Students with college-level learning in high
school credits performed, on average, better than their counterparts with no college-level
learning in high school credits on the post-secondary academic success indicator of first
semester GPA.
Cumulative GPA
The data showed a difference in cumulative GPA between the two groups. Students with
CLLHS credits had a mean cumulative GPA (M = 3.056, SD = .629) that was higher than
for students with no CLLHS credits (M = 2.440, SD = .910). A Pearson Correlation
Coefficient showed a strong positive correlation (r = .551, p < .001) between high school
19
average and cumulative GPA. In addition, a Pearson Correlation Coefficient showed a
moderate positive correlation (r = .360, p < .001) between SAT score and cumulative
GPA. These results indicated that a higher cumulative GPA was related to both a higher
SAT score as well as a higher high school average, but the latter is a stronger
relationship.
In order to measure the affect of the existence of CLLHS credits, an ANCOVA was
completed with high school GPA and SAT score as confounding variables (i.e.,
covariates), cumulative GPA as the dependent variable, and sex, race and the existence of
CLLHS credits as the independent variables. The results of this procedure showed that
race and gender were not significantly related to cumulative GPA but the existence of
CLLHS credits was found to be significantly related to cumulative GPA. Although a
causal relationship could not be determined, the existence of CLLHS credits was found to
be significantly correlated with a student’s post-secondary academic success, as
measured in cumulative GPA.
Implications
The results of the data analysis showed that a students' high school average was a
statistically significant and strong predictor of both first semester GPA and cumulative
GPA but SAT score was neither a strong or statistically significant predictor for either
variable. In addition, the results indicated that the existence of CLLHS credits was
significantly related to first semester GPA as well as cumulative GPA after controlling
for high school average and SAT score. This is not to imply that these relationships are
caused from an increase in curricular intensity. Students with CLLHS credits could have
a higher first semester GPA and a higher cumulative GPA for a number of reasons. First,
the CLLHS credits could have been earned as part of an articulation program aimed at
enhancing the curricular choices available in the high school. Such a program, regardless
of the quality of its curriculum, could academically engage and better prepare the student
for college success simply because the student did not “take the senior year off”. This
could act as a barometer, and/or build confidence, and/or improve the immediacy of the
material, all of which could aid the student’s transition from the high school to the
college. Bridging the gap between these two educational levels could be shown in a
higher first-semester GPA, which would lower the chance of, what Bailey, Hughes, and
Karp (2003) term “costly false starts”. In addition, the creation of a solid first semester
GPA could be a building block toward, as well as an indication of, a higher cumulative
GPA.
Second, there could be an unmeasured covariate at work such as post-secondary
academic motivation. Some students may be motivated to complete college-level work
and not high school work. Also, many CLLHS opportunities exist, not as formal
programs in the high schools, but as options at the college, outside of the regular high
school curriculum, and students need to seek them out. In these instances, the earning of
CLLHS credits could be an indirect or proxy measure of a student’s desire to attend and
perform at the post-secondary level, regardless of past academic performance. This desire
could possibly be witnessed in both a higher first semester and a higher cumulative GPA.
20
Third, in the case of AP credits some questions remain. It is estimated that over one-third
of all students enrolled in AP courses do not take the standardized test at the end of the
course (Gemma, 2004). Since the data for this study included only students with scores of
“3” or above on the standardized test, the results could be measuring the first semester
GPA and cumulative GPA of students who took and were successful on the test for a
variety of reasons other than the quality of the curriculum (i.e., ability to pay for the test,
availability and location of the test site, encouragement of family members, confidence in
ability to do college-level work).
Although a causal relationship could not be determined, the existence of CLLHS credits
indicated both a higher mean first semester GPA as well as a higher mean cumulative
GPA. If it is assumed that the existence of CLLHS credits is an indirect measure of an
exposure to an increased curricular rigor, then the results of this study, with regard to
first-semester GPA and cumulative GPA, support prior findings that a student’s pre-
collegiate academic history is significantly related to post-secondary academic success
which would call for an expansion of these programs.
Access, Success, and Expansion
Entrance to college-level learning in high school programs has historically been limited
to the top academically able students (DiPuma, 2002; Greenberg, 1988). Although the
popularity of the AP program has recently increased, and the pool of test takers has
expanded to include students of lower ability (Lichten, 2000), this program continues to
be most attractive to the best academically able students (Dougherty, Mellor, & Jian,
2006). Dual enrollment programs have also historically been limited to the top
academically able students but have, increasingly, been viewed as appropriate for all
students, including the low academic performers (Karp & Hughes, 2008). Dual
enrollment programs have witnessed a dramatic increase in participation numbers in
recent years (Bailey, Hughes, & Karp, 2003; Lords, 2000) and much of this increase has
come from the moderate and sometimes low academic achievers (Andrews, 2000, 2001;
DiPuma, 2002).
The data from this study reflect this landscape. High school average was significantly
related to the type of CLLHS credits attained with 71.3% of students with AP and/or IB
credits being categorized as High Academic Achievers and 64.9% of the students with
dual enrollment credits only categorized as Moderate or Low Academic Achievers. In
addition, SAT Score was significantly related to the type of CLLHS credits attained with
73.6% of students with AP and/or IB credits being categorized as High SAT Score and
65.9% of the students with dual enrollment credits only categorized as Moderate or Low
SAT Score. Students with AP and/or IB credits had a higher mean high school average
(M = 92.9) compared to students with dual enrollment only credits (M = 88.85) as well as
a higher mean SAT score (M = 1133.22) than students with dual enrollment only credits
(M = 1005.22). These results are consistent with prior suggestions that AP/IB programs
are the “best family china, brought out only for special guests” (Newsweek, as cited in
U.S. Department of Education, 2000, p. 6) and that dual enrollment programs appeal to
those “just below” the top academically able students (Hugo, 2001). In addition to
21
differences between and within the groups with regard to high school average and SAT
score, the data also identified differences by race. Race was significantly related to the
existence or non-existence of CLLHS credits. White students were more likely to have
CLLHS credits (55.4%) and P.O.C. students were more likely to not have CLLHS credits
(66.1%). In addition, P.O.C. students, if they had CLLHS credits, were more likely to
have dual enrollment credits only (74%) than White students (67%) and less likely to
have AP/IB credits (26%) than White students (33%). Almost one in every five (18.3%)
White students in the sample population had AP and/or IB credits, compared to roughly
one in every eleven students categorized as a Person of Color (8.7%). These results
appear to support the suggestion by the Thomás Rivera Policy Institute that there is an
unequal access to AP courses by race (Zarate, 2006).
Implications
The Western Interstate Commission for Higher Education (2008) points out that gaps in
educational attainment based on race and ethnicity have long existed. As shown in table
2, the gap between the first semester GPA for White students compared to P.O.C.
students narrowed from .348 for all the students to just .187 for students with CLLHS
credits. Also shown in table 2, prior to accounting for the existence of CLLHS credits, the
gap in cumulative GPA between White students and P.O.C. students was .384. After
accounting for the existence of CLLHS credits, this gap narrowed to .263.
Although a cause and effect relationship cannot be determined based on this level of
analysis of the data, it appears that the disparity in post-secondary academic success
between White students and P.O.C. students, as measured in first semester GPA and
cumulative GPA, is narrower for the group of students with CLLHS credits than for the
population as a whole. The Western Interstate Commission for Higher Education (2008)
suggests that a crucial element to narrowing the gaps in educational attainment is the
creation of an equal playing field. Considered in this context, CLLHS programs can be
viewed as a symbol for “society’s commitment to equality of opportunity and access” (p.
72) in addition to an opportunity to earn college credit (Greenberg, 1998). Because race
and income are intertwined in American society (Frey & Fielding, 1995), it can be
inferred that the existence of CLLHS credits could also have the same affect on
economically disadvantaged students although this study was unable to measure this
possible effect.
22
Table 2
Comparison of First Semester GPA and Cumulative GPA for Students with CLLHS
Credits and Students with No CLLHS Credits by Race
First Semester First Semester GPA Cumulative Cumulative GPA
GPA Sample Students With GPA Sample Students With
Race Population CLLHS Credits Population CLLHS Credits
μ SD μ SD μ SD μ SD
White 2.872 .809 3.099 .632 2.853 .815 3.101 .621
P.O.C. 2.524 .889 2.912 .634 2.469 .825 2.838 .641
Difference .348a .187
b .384
c .263
d
aThis number notes the difference in First Semester GPA between the two racial groups in the sample
population (2.872 minus 2.524). bThis number notes the difference in First Semester GPA between the two
racial groups within the group of students with CLLHS credits (3.099 minus 2.912). cThis number notes the
difference in Cumulative GPA between the two racial groups in the sample population (2.853 minus
2.469). dThis number notes the difference in First Semester GPA between the two racial groups within the
group of students with CLLHS credits (3.101 minus 2.838).
Time-to-Degree
It is an assumed benefit of CLLHS programs that they lead to the early accumulation of
college credits which can reduce costs to the student (Clark, 2001), and presumably lead
to a decrease in the time it takes to earn a degree, but there is little evidence that this is
happening. This study attempted to asses an indirect or proxy measure of a possible
shortening of time-to-degree by measuring the total number of credits earned by the end
of the student’s fourth semester or last semester in attendance, whatever came first.
The data show that students with CLLHS credits (M = 62.610) earned 21.54 more credits
(62.610 minus 41.070) by the end of the fourth semester than students with no CLLHS
credits (M = 41.070). In order to measure the affect of the existence of CLLHS credits, an
ANCOVA was completed with high school GPA and SAT score as confounding
variables (i.e., covariates), cumulative number of credits earned as the dependent
variable, and sex, race, and the existence of CLLHS credits as the independent variables.
The results of the data analysis showed that a students' High School average was a
23
statistically significant and strong predictor of cumulative number of credits earned but
SAT score was not a statistically significant or strong predictor of this indictor of post-
secondary academic success. In addition, race and gender were not significantly related to
cumulative number of credits earned. After controlling for high school average and SAT
score, the existence of CLLHS credits was found to be significantly related to cumulative
number of credits earned. Although a causal relationship could not be determined, the
existence of CLLHS credits was found to be significantly correlated with a student’s
post-secondary academic success, as measured in cumulative number of credits earned.
Implications
College-level learning in high school programs originated with the intent to allow a small
number of top students the opportunity to accelerate their academic progress (Bailey &
Karp, 2003), to possibly skip a few introductory college courses, and to signal their
academic achievement and ambition to the elite colleges (Johnstone & Del Genio, 2001).
But, these programs have grown to include the moderate and low academic achievers
who now expect to apply any earned credits toward the early completion of their degree
(Johnstone & Del Genio, 2001). Some states such as Utah (Boswell, 2000) and Florida
(Catron, 2001) have made it a point to encourage the early accumulation of college
credits in an effort to save money and the Indiana Department of Education has
mandated, under state law, that every high school in the state must offer a minimum of 2
dual enrollment courses (Indiana Department of Education, 2010). Presumably, the
thinking is that the less time a student spends in a state-funded school, the less cost to the
state. A small number of states such as Washington and Minnesota have studied their
CLLHS programs and they have determined that, due to the potential of these programs
to lead a student to a shortened time-to-degree, the potential savings to the taxpayers is
significant (Blair, 1999). But, there is little research tracking the post-secondary academic
success of students with CLLHS credits (Greenberg, 1998); especially students with dual
enrollment credits (Porter, 2003).
It is unknown if the early accumulation of credits will actually lead to a decrease in the
time-to-degree for students with CLLHS credits. It is possible that these credits are extra
free electives, are remedial courses that were added on to the regular degree requirements
after the student arrived and took the college placement tests, or they could be intended
for completion of a minor or second major. Although it is unclear if any early
accumulated credits will lead to an early awarding of a degree, it is clear that students
with CLLHS credits accumulated a statistically significant more number of mean credits
by the end of the fourth semester in attendance than the group of students with no
CLLHS credits. In addition to the accumulation of credits while in high school, another
factor that could influence the total number of college credits earned could be the total
number of semesters in attendance at the institution.
Persistence
Klopfenstein (2002) states that students who take AP coursework while in high school
show greater retention rates in college. In addition, dual enrollment programs can have a
24
positive impact on college attendance rates (Chapman, 2001). Adelman (2006) states that
the majority of studies on postsecondary persistence measure up to the end of the first
year (two semesters) in attendance but he suggests that a more constructive approach
would be to measure up the second full calendar year (four semesters). This study tracked
persistence rates up to, and including, a student’s fourth year in attendance or last year in
attendance, whatever occurred first and it did not count summer terms as semesters. The
data revealed a difference in total number of semesters in attendance (persistence)
between the two groups. Students with CLLHS credits persisted at a rate of 3.65 mean
number of semesters and students with no CLLHS credits persisted at a rate of 3.2 mean
number of semesters. In order to measure the affect of the existence of CLLHS credits, an
ANCOVA was completed with high school GPA and SAT score as confounding
variables (i.e., covariates), cumulative number of semesters in attendance as the
dependent variable, and sex, race and the existence of CLLHS credits as the independent
variables. The results of the data analysis showed that a students' high school average was
a statistically significant and strong predictor of cumulative number of semesters in
attendance and SAT score was not a statistically significant or strong predictor of this
dependent variable. In addition, race and gender were not significantly related to
cumulative number of semesters in attendance. After controlling for high school average
and SAT score, the existence of CLLHS credits was not significantly related to
cumulative number of semesters in attendance. Students with college-level learning in
high school credits persisted at a higher but not statistically significant mean number of
total semesters than their counterparts with no college-level learning in high school
credits.
Discussion
Proponents of college-level learning in high school programs suggest that they lead to
many possible benefits. A short and non-exhaustive list of these benefits includes:
students who are challenged to complete more rigorous courses develop a barometer that
helps them gauge their academic achievements with peers (Texas Education Agency,
2002); students exposed to college-level coursework while in high school are better
prepared for college (Klein, 2007), show greater retention rates in college (Chapman,
2001; Klopfenstein, 2004), and are more likely to graduate from college (Burdman,
2000); the program offerings can enhance the curricular choices available at the high
schools and can increase the curricular rigor the students are exposed to (Chapman,
2001), which can be of particular importance in poor public high schools (Hugo, 2001);
students who take these courses are less likely to feel the onset of “senioritis” (American
Association of State College and Universities, 2002); these programs can reduce the costs
of educating the student (Clark, 2001).
Inherent in all of these possible benefits are three important themes. First, there is a lack
of curricular continuity between the high schools and the colleges (Boswell, 2001;
Carnegie Commission on Higher Education, 1973; Greenberg, 1988; Orrill, 2001; Kirst,
2001; National Commission on the High School Senior Year, 2001; Wilbur & Chapman,
1978). Second, the curricular options available to the average American high student,
especially in the senior year, are limited (Peterson, 2003), inadequate, and inefficient
25
(Boyer & Levine, 1981) and the rigor of the high school curriculum, especially in the
senior year, is lacking (cf., Adelman, 1999, 2006; Barth, 2001; Haycock, Barth, Mitchell,
& Wilkins, 1999; Kirst, 2001; National Commission on the High School Senior Year,
2001; Peterson, 2003; Wilbur & Chapman, 1978). Third, there is an overlap of
curriculum between the last two years of high school and the first two years of college
(Carnegie Commission on Higher Education, 1973; Gemma, 2004; Greenberg, 1998;
Peterson, 2003; Wilbur & Chapman, 1978) at the same time that the demand for
remediation at the post-secondary levels is ever increasing (Greenberg, 1982). This study
has a number of possible implications with regard to these themes.
If there is evidence that students with CLLHS credits perform better than their peers with
no such pre-collegiate academic experience, then we can consider CLLHS programs a
means to bridge the gap and ease the transition between the secondary and post-
secondary educational levels. The Carnegie Commission (1971) called for drastic
structural changes to the secondary and post-secondary educational systems to include,
among other things, the deletion of either the high school senior year or the first year of
college. Adelman (2006) has echoed this call by stating that the first year of post-
secondary education has to begin in the high school by way of either AP, dual
enrollment, or some other form of college-level learning in high school. But, to make
such drastic changes, and to utilize college-level learning in high school programs as a
paramount component in those changes, the legitimacy and effectiveness of such
programs must be articulated and ensured. This study can aid in that process. The results
of this study showed a statistically significant relationship between the existence of
CLLHS credits and the post-secondary academic success indicators of first semester
GPA, cumulative GPA, and total number of credits earned by the fourth semester, after
controlling for high school average and SAT score. Much more research is needed with
regard to students with college-level learning in high school credits in general and post-
secondary academic success into multiple college semesters in specific, before a
complete picture will form.
Although the results of this study showed a clear correlation between the existence of
CLLHS credits and post-secondary academic success, a causal relationship has yet to be
shown. Regardless, these results indicate two important things. First, it appears that high
school students, to include the high, moderate, and low academic achievers, have the
capacity to perform at the college level while in high school. Second, success in college-
level learning in high school programs is significantly related to post-secondary academic
success. This has potential policy implications for higher education professionals in
general and admissions officers in particular. It is well accepted that high school average
is a good predictor of post-secondary academic success and the results of this study
appear to support this. But, regardless of the high school average, students who had
accumulated college-level credits (i.e., who had proven to be successful in such
programs), also performed well in their post-secondary academic endeavors. This would
suggest that the existence of college-level credits for an incoming first term, full time
freshman might be a good predictor of future academic success. This could allow
admissions officers to better find the “diamonds in the ruff” for discretionary or
probationary admissions to their institution.
26
College-level learning in high school programs exist in all fifty-two states (Frazier, 2000)
and they are growing faster than policies to ensure curricular quality can be put into place
(Barnes, 2001). The growth of these programs has exploded across the country (Andrews,
2000) and many of these programs involve taxpayer dollars (American Association of
State Colleges and Universities, 2002; Andrews, 2000; Greenberg, 1988; Johnstone,
1993). Higher education is a competitive high stakes game of increasing costs and
diminishing resources (Barnes, 2001). In order to compete for these scarce resources, it
must be shown, not only that they are effective, but also how they are effective. In other
words, where can we get the most “bang for the buck”? The results of this study can aid
in the answer to this question. The Western Interstate Commission for Higher Education
(2008) points out that gaps in educational attainment based on race and ethnicity have
long existed. The results of this study indicated that White students were more likely than
students categorized as People of Color to have dual enrollment credits and they were far
more likely to have AP and/or IB credits. If the attainment of CLLHS credits is
significantly related to post-secondary academic success, then these programs can be an
important symbol in our society’s commitment to equality of opportunity and access
(Greenberg, 1988). Colleges and Universities with missions to expand the access of
historically underrepresented groups may view the establishment of college-level
learning in high school programs with local high schools, particularly those with large
percentages of at-risk or minority students, as a strategy to help meet this mission.
Adelman (2006) suggests there are specific areas were resources can be spent to help
narrow the gaps between degree completion rates by race. He found that the impact of an
increased high school curriculum is important for all groups of students but its effects are
far more pronounced for African American and Latino students than any other pre-
college indicator of academic success. He suggested that increasing the high school
academic curriculum and having students enter college directly from high school could
close the degree completion gap between Latino students and White students from 22.2%
to 16.4%. His recommendation is to pour our efforts into high school preparation above
anything else for this fastest growing population in the U.S. The results of this study
support this recommendation. The gap in mean first semester GPA and mean cumulative
GPA for White students and P.O.C. students was greater in the population as a whole
than between White students and P.O.C. students in the group of students with CLLHS
credits. Although a causal relationship could not be determined, and although the analysis
did not account for possible confounding variables, it appears that, the gap in post-
secondary academic performance between these two main race groups diminished when
the variable of CLLHS credits was introduced. If follow-up analysis and other future
research can confirm and better articulate this interaction, this could lend support to the
argument that resources should be directed to CLLHS programs in an effort to improve
the academic preparation of all high school students in general, and historically
underrepresented race and ethnic groups in specific.
Adelman (2006) found an “overwhelming phenomenon” (p. 55) with regard to
cumulative number of credits earned. Those students who never earned their bachelor’s
degree were already 25 credits (57.4 minus 31.6) behind those that did by the end of their
second year (fourth semester) in attendance. He recommends spending resources to
27
ensure students get to this critical level of college credits by the end of their second year
in attendance. What this may mean for higher education professionals is the
implementation of policies that encourage the early accumulation of credits. This could
involve getting the student to start at the college in the summer after the senior year of
high school, getting the student to take more credits per semester, and/or encouraging the
student to engage in summer study for the first two summers after the freshman year.
The results of this study are particularly insightful with regard to this point. Students with
CLLHS credits earned a mean number of credit hours by the end of their fourth semester
of 62.61 credits, which is above the 57.4 credit threshold, and students with no CLLHS
credits earned a mean number of credits hours by their fourth semester of 41.07 credits,
which is well below the threshold of 57.4 credits. In addition, the gap between these two
groups in total credit hours by the end of the second year was 21.54 credits. Although this
study did not directly measure degree completion rates, if it is true that students who fall
behind by 25 credit hours by the end of their second year of attendance fail to graduate,
these results indicate that students with CLLHS credits are more likely to finish their
degree and students with no CLLHS credits are less likely to finish their degree. Follow-
up studies would need to be conducted to validate this assertion, but if it is true, then this
would signify a positive statistically significant relationship between total number of
credits earned and degree completion rates. This relationship, if it exists, may differ by
race, sex, or some other variable/s. Adelman (2006) discovered for instance, that, for
African American students in particular, earning more than four credits in summer terms
created a “stunning boost” (p. 93) to their degree completion rates and narrowed the gap
between them and White students from 15.5% to 6%. This assertion, coupled with the
results of this study, would then suggest that colleges make attempts to encourage
students to accumulate credits in their first two years and to possibly tailor those efforts
to specific groups.
The results of this study provide educational stakeholders such as high school
administrators, policy makers, teachers, parents, and students, valuable information about
the possible effectiveness and associated benefits of college-level learning in high school
programs. After controlling for academic ability (i.e., high school GPA, and SAT score),
this study found evidence that students who were successful in college-level learning in
high school programs had significantly higher mean first semester GPAs, significantly
higher mean cumulative GPAs, and accumulated a significantly mean higher number of
credits hours, as compared to students with no recognized college-level learning in high
school credits. In addition, this study found evidence that students who were successful in
college-level learning in high school programs persisted at a higher but not statistically
significant mean rate than those students with no college-level learning in high school
credits (as measured in mean total number of semesters in attendance). These results
indicate that college-level learning in high school programs can be a positive force in the
post-secondary academic success for students of all academic abilities. The results of this
study support efforts to expand CLLHS programs.
There have been many varied approaches aimed at achieving these goals and college-
level learning in high school is one of those approaches. High schools have been
28
expanding their college-level learning in high school options in recent years and that
trend will continue (Gemma, 2004). The importance of finding a means to bridge the gap
between the last two years of high school and the first two years of college, of finding a
way to engage and challenge the high school juniors and senior, of finding a way to
increase the curricular offerings to all high school students, to lower the need for
remediation, and to engineer a mechanism that will increase the chances of post-
secondary academic success of the moderate and low academically able students, cannot
be overstated. This study has focused on a small group of first term, full time freshman
who entered a small private urban college over a seven-year span and it found that
successful completion of college-level learning in high school courses, for these students,
was significantly and positively related to three of the four measured post-secondary
academic success indicators. There are numerous causes for the poor performance of
American high school students and these causes are so complex that no one approach will
solve the conundrum (Fleischman & Heppen, 2009).
Limitations
This study attempted to measure the effects of college-level learning in high school on
students’ post-secondary academic success. Although it represents a good effort to
examine this complex issue, it had a number of limitations. First, this study made a
distinction between being exposed to college-level learning in high school and being
successful in it. The literature suggests that the exposure to CLLHS programs can have
positive benefits for students of all academic abilities (Adelman, 1999, Bailey, Hughes, &
Karp, 2003, Johnstone, 1993). The results of this study are limited with regard to
measuring this interaction because it was unable to compare students who had some
exposure to CLLHS to those who had no such exposure. Students were considered as
having CLLHS experience if they were successful in that endeavor (i.e., had a score of
"3" or above on an AP exam, had a grade of “C” or above on a dual enrollment course).
The participants were not categorized as those with CLLHS experience and those with no
CLLLHS experience, but rather, as those with CLLHS credits and those with no CLLHS
credits. So, this study, at best, compared students with successful completion of CLLHS
courses to those with no CLLHS credits (either because they had no exposure, or because
they had exposure but were not successful).
Second, this study was unable to control for all variables that might be related to and/or
influence the dependent variables. One example is a student’s average course-load per
semester. A possible explanation of why students with CLLHS credits showed, on
average, higher mean first semester GPAs and higher mean cumulative GPAs compared
to students with no CLLHS credits could be that these students, because they came to
college with credits in hand, were able to take a lower number of credits per semester.
Having to take even one less course in a semester could allow the students with CLLHS
credits to focus more time on the courses they were taking, with the thought being that
they could then perform at a higher level in those courses. In addition, all students in this
study were first time, full time students during their first semester at the college but this
study did not measure or take in to account whether or not any of these students
29
maintained full time status in each successive semester. One possible reason that students
with CLLHS credits accumulated a higher number of mean total credits by the end of the
fourth semester in attendance could be that they, on average, took more credits per
semester than did the students with no CLLHS credits. This was not measured or
accounted for in this study. Also, the study did not take into account or measure the
possible effects of summer study. Summer was not considered a semester and not
accounted for. So, it could be possible that one reason students with CLLHS credits
accumulated a higher mean number of credit hours by the end of the fourth semester, is
because they had a greater rate of summer course taking than students with no CLLHS
credits.
Third, this study did not address the issue of remediation. The literature suggests that
increasing the rigor of the secondary curriculum by way of CLLHS programs can result
in a lowered likelihood that the student will require remediation in the CLLHS course
subject area at the post-secondary level (American Association of State Colleges and
Universities, 2002). It is unknown if the students with CLLHS credits in the sample
population for this study attempted more or fewer remedial courses at the college and
whether they were, on average, more or less successful in them compared to students
with no CLLHS credits. Any possible effects of remediation courses was not measured,
considered, or controlled for in this study. One possible effect of the unsuccessful
completion of remedial courses could be lowered levels of persistence (i.e., total number
of semesters in attendance) which could then be an uncontrolled covariate with regard to
the dependent variable of persistence in this study.
Fourth, this study was unable to distinguish between the various types of college-level
learning in high school programs other than the broad categories of AP, IB, and Dual
Enrollment. Students were considered as having AP credits if they scored a "3" or above
on the standardized test. It is possible to take the standardized AP exam and not have
taken the corresponding course. This study was unable to identify this possible difference
among students with AP credits. In addition, dual enrollment courses exist in many forms
and vary based on who teaches the course, where a course is taught, how one pays for the
course, and if the student is in competition with other college students or not. This study
was unable to identify these distinctions. All students who had accumulated non AP
and/or IB college credit prior to the date of their graduation from high school and that
was accepted by D’Youville College as transfer credit, were considered students with
dual enrollment credits. This then could have included all possible forms of dual
enrollment programs. Due to this limitation, this study was unable to examine, in a
precise manner, any possible effects of the varied forms of dual enrollment programs on
post-secondary academic success.
Fifth, due to the limited number of cases in this study, a number of variables had to be
collapsed which could have limited the effectiveness of the analysis. In order to ensure
valid results of the ANCOVA testing, the variable of type of CLLHS credits was
collapsed into the somewhat broad two categories of students with CLLHS credits and
those with no CLLHS credits. Because of this, the study was unable to measure any
30
possible effects of the different types of CLLHS credits on the dependent variables in the
analyses.
Sixth, this study attempted to include the variable of socio-economic status but, do to
limitations in the available data, this variable had to be removed from consideration for
many of the statistical procedures. It is unknown what possible effect this variable might
have with regard to the results of this study and it is unknown if this variable is
significantly correlated with the other variables such as race and gender. Future studies
may need to incorporate a proxy measure of socio-economic status such as zip code
analysis from U.S. Census data in order to obtain a clearer picture. Until this variable is
measured and accounted for, it is unknown whether the results of this study (with regard
to the variable of race in particular) are spurious.
31
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