When Developmental Education is Optional, What Will Students Do

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DOI 10.1007/s10755-015-9343-6
When Developmental Education is Optional, What
Will Students Do? A Preliminary Analysis of Survey
Data on Student Course Enrollment Decisions
in an Environment of Increased Choice
Toby Park 1 & Chenoa S. Woods 1 & Keith Richard 1 &
David Tandberg 1 & Shouping Hu 1 &
Tamara Bertrand Jones 1
# Springer Science+Business Media New York 2015
Abstract Historically, college students needing additional academic preparation have been
assigned to developmental/remedial courses. In 2013 Florida took a drastic departure from this
model by passing Senate Bill 1720, which prohibited institutions from requiring placement
tests and made developmental education optional for many students, regardless of prior
academic preparation. For this pilot study we conducted a survey at two colleges in the
Florida College System to begin to understand the kinds of courses students will take now
that developmental education is optional and the factors that students considered when making
their course enrollment decisions.
Key words developmental education . community colleges . education policy
Toby Park is Assistant Professor of Economics of Education and Education Policy and Associate Director of the
Center for Postsecondary Success at Florida State University. He received his B.S. in mathematics and his M.Ed.
in higher education from the University of Pittsburgh and his Ph.D. in education policy from Vanderbilt
University. His research interests include student outcomes in postsecondary education and exploring potential
policy initiatives that could improve student success, with a particular focus on non-traditional students and
institutions. He can be reached via tjpark@fsu.edu.
Chenoa S. Woods is a Postdoctoral Research Fellow at the Center for Postsecondary Success at Florida State
University. She received her B.A. in psychology and M.S. in school counseling from California State University,
Long Beach, and her Ph.D. in education policy and social context from the University of California, Irvine. Her
research interests include exploring the relationships between precollege counseling, college choice, postsecondary transitions, and student success.
Keith Richard is a Ph.D. candidate in Sociology and a Research Assistant in the Center for Postsecondary
Success at Florida State University. He received his M.A. in psychology from Florida State University and B.A.
in psychology from Coastal Carolina University. His research interests include community college reform,
sociology of education, and social inequalities.
David Tandberg is Associate Professor of Higher Education and Associate Director of the Center for Postsecondary Success at Florida State University. He received his B.S. in history and education from Adams State
College and his M.A. in political science and Ph.D. in higher education from Pennsylvania State University. His
research interests include state higher education policy and politics.
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As students transition into college from high school, military service, or the world of work,
many may be underprepared for college-level work. Traditionally, these underprepared students have been placed in developmental–sometimes called remedial–courses in reading,
writing, and/or mathematics in order to improve their skills and to prepare themselves for
credit-bearing, college-level courses. However, when Senate Bill 1720 (SB 1720) passed in the
state of Florida in 2013, developmental education (DE) became optional for all students
graduating from a Florida public high school with a standard diploma since 2007, as well as
for students who are serving as active duty members of the military. Whereas DE was
previously required for all Florida College System students testing below established levels
on standardized tests, these newly defined exempt students can now make their own enrollment
decisions. Specifically, exempt students have the opportunity to bypass placement tests
altogether and to opt out of DE courses and enroll directly into college-level work, regardless
of previous academic performance. Given this environment of increased choice that is no
longer strictly dictated by test scores, we sought to understand how students make course
enrollment decisions. Succinctly stated, we wanted to explore what DE courses students will
decide to take and why when they are advised to take such courses.
Literature Review and Background
Developmental Education
The reform of DE has gained a significant place in the federal and state policy limelight
in recent years; however, research on the benefits of this approach has been mixed.
Boatman and Long (2010) for example, found that the effects of DE courses on grades,
credit accumulation, persistence, and graduation vary based on students’ academic preparedness. The authors found that it can have a positive or a small negative effect for
students needing multiple levels of remediation compared to the larger negative effects for
students who test on the margin and are placed into higher-level courses. Additionally,
researchers have found that DE increased students’ persistence when compared to
Shouping Hu is the Louis W. and Elizabeth N. Bender Endowed Professor of Higher Education and the
founding Director of the Center for Postsecondary Success at Florida State University. He received his B.S. in
geography from Peking University and M.A. in economics and Ph.D. in higher education from Indiana
University, Bloomington. His research interests include college access and success, student engagement and
learning, and higher education policy.
Tamara Bertrand Jones is Assistant Professor of Higher Education and a Senior Research Associate in the
Center for Postsecondary Success at Florida State University. She received her B.J. in journalism from the
University of Texas at Austin, and M.S. in higher education and Ph.D. in research and evaluation methods from
Florida State University. Her research interests include sociocultural influences on the educational and professional experiences of underrepresented populations in academia.
* Toby Park
tjpark@fsu.edu
1
Center for Postsecondary Success, Florida State University, Tallahassee, FL, USA
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similarly-prepared peers not placed into DE (Bettinger and Long 2009; Lesik 2007).
Alternatively, other work has found negative effects of DE, including an increased
likelihood of dropping out of college, lower self-esteem, and more frustration for those
students who enrolled in DE (Bettinger and Long 2007; Jacob and Lefgren 2004).
In addition to debates about its effectiveness, there are issues regarding appropriate DE
placement and enrollment. For example, Perin (2006) found that there were loopholes
such that students who tested into DE could (and did) enroll in higher-level courses
despite state and institutional policies against doing so. Similarly, Bailey et al. (2010)
reported that nearly one-third of students who are recommended for DE do not enroll in a
DE course within three years. Further, it remains unclear whether or not placement exams
have a discernable relationship with student success, suggesting that multiple measures
regarding placement may be more appropriate (Scott-Clayton 2012).
Recent trends in DE reform, which are supported by policy organizations as well as
empirical research, have tended to focus on placement into DE via multiple measures and
a gradual and planned implementation of policy changes. For instance, the Research for
Action report (2015) recommended providing ample professional development for faculty
and staff and piloting reforms using multiple measures in academic advising practices.
Indeed, Scott-Clayton (2012) found that using multiple measures for placement could
reduce student-course mismatch (i.e., severe misplacement) by about 15%. As such, North
Carolina, which adopted its multiple measures policy as recently as 2013, implemented an
exempt status for recent high school graduates who also met GPA, SAT/ACT, or
placement test thresholds (Research for Action 2015). Florida, however, has taken a
broader approach by no longer requiring placement tests and making developmental
education optional for many students.
Florida Legislation
In 2013 the State of Florida passed Senate Bill 1720 that changed developmental
education in major ways. The legislation defined exempt students as those who
graduated from a Florida public high school in the year 2007 or later or are active
duty members of the military; and it gives these students the option to opt out of DE
courses, regardless of academic preparation or demonstrated ability. Further, the new
legislation mandated that colleges offer advising for all incoming students. In addition,
colleges must now offer a range of course delivery methods for DE courses, including
modularized courses that focus on students’ specific strengths and weaknesses, compressed courses taught in a shorter timespan than the typical 16-week semester,
contextualized courses that relate course materials to major-course pathways and
contain real-world connections, and co-requisite courses where students take DE
courses alongside college level courses. Our study focused on the first part of the
law, which no longer requires exempt students to take placement tests and makes DE
optional. Given options, how will students make decisions when advised to take DE?
Further, what are the factors that these students consider when they make course
enrollment decisions? Answers to these questions may be useful for institutions in
developing effective advising programs. Exploring these issues is particularly important given that there is increasing evidence suggesting that structured and guided
pathways are beneficial for student completion of educational credentials in community colleges (Jenkins and Cho 2013).
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Student Decision-Making and Advising
Enrollment decisions that promote student success become more pertinent as the variety of
course offerings change. Previous research has found that most students who are given several
academic options often ignore advisors’ recommendations or enroll in courses that do not lead
towards graduation, even when enrolled in a structured degree program (Complete College
America 2012). As of fall 2014, students identified as exempt under Senate Bill 1720 have
even greater freedom in their enrollment choices and course selection options through the
optional, modified forms of DE offered by the 28 colleges in the Florida College System. DE
courses are offered in a variety of new formats in an attempt to meet the varying needs of a
diverse student population, and now exempt students may choose from DE and college-level
courses alike.
Much of the existing research on student course selection explored the process through
factors such as student self-concept and characteristics (Yeung and Marsh 1997), course
evaluations as sources of information (Wilhelm 2004; Wilhelm and Comegys 2004), and
specific advising programs tailored to assist students in the course selection process (Van Wie
2011). Throughout the literature, factors affecting course selection can be divided into two
broad categories: academic characteristics, which are related to the course or instructor, or
personal characteristics, which are related to the individual student.
The first category refers to academic information regarding the course such as course
content and description, perceived difficulty, examinations, or instructor style and reputation.
Babad’s (2001) study of students’ considerations in selecting first and last courses of their
degree programs showed that students selected first courses based on intellectual level and
expected quality of teaching and last courses based on low level of difficulty. In a later study,
Babad and Tayeb (2003) identified learning value, perception of an instructor’s style, and
course difficulty as highly important to students in the decision-making process about course
selection. Moreover, professor and course reputation have been shown to be important factors
(Leventhal 1976; Pass et al. 2012; Yeung and Marsh 1997). Students receive information
regarding courses and professors from a variety of different sources including formal course
bulletins or guides (Babad et al. 1999) or informally through peers or internet sources such as
ratemyprofessor.com (DellaGioia 2008).
The second category pertains to the individual student’s personal context and is
manifested in decision-making based on the student’s personal needs. Examples of these
needs can include the demands of a particular work schedule, the fulfillment of requirements for a program of study, career goals, social needs, or the need to fulfill an
academic deficiency. Feather (1988) found that student selections of specific mathematics
and English courses were related to their self-concept of ability in the subject area.
Moogan and Baron (2003) identified problem recognition—the degree to which a choice
fulfills a certain gap for the student—as an additional factor behind student course
selections. Furthermore, students tend to use friends, family, peers, advisors, and faculty
members as sources of information when selecting courses (Kerin et al. 1975). Peers and
friends are often ranked highest in consideration although they are somewhat unreliable
sources of information (Brooks 2002, 2003; Roberts and Allen 1997).
Prior to Florida’s SB 1720, DE was required for certain students depending on college
placement test scores. However, under SB 1720 the placement tests and DE courses are
now voluntary for a substantial number of students; and one of the issues with making
placement tests and DE enrollment optional is that students don’t do optional (Couturier
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2010; Lay 2010). When students have the option to bypass DE courses that they may
consider to be costly, time-intensive, and unnecessary, they may not see the potential
benefits (e.g., better preparation for college-level work) of enrolling in DE courses. Thus,
when important educational support systems such as DE are severely adapted and made
optional, students may be less likely to enroll in the most appropriate course for their
level of ability and future goals.
Different Choices for Different Students
Existing evidence on DE indicates that there are differences in placement and success
in relation to students’ race/ethnicity and gender. That is, females, Black students, and
Latino students are recommended for more levels of developmental education regardless of the subject matter (Bailey et al. 2010). Black students are nearly twice as
likely to be enrolled in DE when compared to their White peers (Attewell et al.
2006), and nearly 60% of DE students are Black or Latino (Melguizo et al. 2008).
Females were more likely to progress from one level of developmental mathematics to
the next when compared to males (Bailey et al. 2010). Although the research indicates
that there is no significant difference related to students’ income status and developmental education enrollment (Fernandez et al. 2014), it may remain important to
disaggregate findings by income level due to the correlations between race/ethnicity
and socioeconomic status.
Additionally, the type of course recommended has effects on students’ success in completing their course sequences. For example, students are more likely to complete their developmental course sequences in reading than in mathematics (Bailey et al. 2010). This trend may
indicate a preference for continuing coursework in reading, lower rates of initial placement into
developmental reading, and/or placement into fewer levels of developmental reading before
reaching the preparation level needed for college-level coursework. Due to the evidence that
developmental enrollment and completions vary by student background and course subject, we
disaggregated our data by course subject (reading, writing, and mathematics) and
race/ethnicity, gender, and income.
The Study and Research Design
The purpose of this study was to begin to understand students’ enrollment decisions
following the passage of SB 1720 and to explore what factors may be influencing
these decisions. In addition, we also stratified our investigation by important student
characteristics (race, gender, and income). While we surveyed all incoming students,
we focused our analysis on exempt students who were advised into a developmental
education (DE) course and either (a) enrolled in the DE course, (b) bypassed DE and
took college-level coursework instead, or (c) did not take any core subject area
course. The following research questions guided the study:
&
&
&
What are the students’ enrollment choices in DE mathematics, writing, and reading
courses?
How do these enrollment patterns vary for different groups of students?
What factors do students consider as they make their enrollment choices?
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Survey Instrument and Administration
In order to understand student course pathways and the factors they considered in making their
choices we designed a student decision-making survey that was administered online. After
receiving Institutional Review Board approval, we collaborated with two institutions in the
Florida College System, which then emailed the online survey to all first time enrollees in the
fall 2014 semester. We obtained informed consent as participants advanced through the survey
and acknowledged their voluntary participation in the study. Following the informed consent
section, students were asked whether they had graduated from a Florida public high school
since 2007 and whether they were currently active duty members of the U.S. military. Based
on the response to these survey items, we hand-coded exempt students (those students who can
opt out of DE). If a student was deemed to be non-exempt, they were not used in the analysis.
For the remaining exempt students, we then asked about course enrollment decisions broken
down by subject area. More specifically, for each area of mathematics, writing, and reading, all
of the exempt students surveyed were asked to select one option from the following list:
1. I registered for a COLLEGE level [subject] course and was not advised to register for a
developmental math/writing/reading course. In this case, students were Bcollege-ready^
and were not advised to enroll in a DE course. We assume that these students would enroll
in college-level courses despite any changes in the legislation.
2. Actual DE course selection. For this option, students selected the specific DE course
number and title in which they enrolled (e.g., MAT 0022; ENC 0051; REA 0056). In this
case, students were advised into a DE course and indeed enrolled in the DE course in the
subject.
3. I was advised to register for developmental [subject], but I chose to register for a
COLLEGE level math/writing/reading course instead. These students were advised to
take a DE course in the subject, yet chose to enroll in a college-level course instead of the
DE course. This is one of the most critical changes possible because of SB 1720.
4. I was advised to register for developmental [subject], but I chose NOT to register for any
math/writing/reading courses this semester. These students were advised to take a DE
course in the subject, yet did not enroll in any course, neither college-level nor DE, in any
of the three subject areas.
From this survey question we restricted our sample by eliminating students who had not
been advised to take DE (Option 1, above) and then classified the remaining students as having
taken DE (Option 2), bypassing DE and directly enrolling in college-level coursework (Option
3), or not enrolling in any subject area course (Option 4).
Next, we asked students to respond to a list of factors or influences that students
found important in deciding whether to enroll in a DE course. We derived our list of 14
factors from the factors presented to the Florida College System institutions by the
administrative team at the Division of Florida Colleges when the institutions were
developing implementation plans for integrated advising of exempt students. We designed
our survey instrument to allow students to indicate whether they found these factors very
important, important, moderately important, somewhat important, not important or that
they did not know how to include this information in their decision-making process. The
14 factors were high school grades in specific courses, high school grade point average
(GPA), Postsecondary Education Readiness Test placement test scores, SAT scores (or
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other standardized test scores), work history, military history, meta-major,1 high school
extracurricular activities, parent/guardian recommendation, high school teacher recommendation, high school counselor recommendation, cost of developmental education, time to
complete intended degree, and personal career goals. For reporting purposes, we present
the percentage of students who responded Bimportant^ or Bvery important^ for each of
the 14 factors. Finally, at the end of the survey, we asked a series of demographic
questions including questions about gender, race, and family income.
Sample and Data
The sample for this study came from two institutions in the Florida College System. All
first-time college freshmen attending these institutions were given an online survey to
complete during the Fall 2014 semester of college, a total of 8,779 students across the
two colleges. The survey was distributed directly by the colleges via email and was
available for two weeks. Follow-up reminders were sent by the colleges in the form of
email and/or text message. Students were offered to be entered into a drawing to receive
a $200 Amazon gift card in order to encourage participation. Ten gift cards were awarded
at each college, provided by funding from the Bill and Melinda Gates Foundation. We
received a total of 668 student responses from both colleges that had data on all
enrollment variables for all three subject areas, a response rate of 7.6%, a limitation we
address later in this article. The sample consists of the 668 students from both colleges
and represents a diverse group of students. The majority of participants identified as
Latino (32%). The other groups and percentages were White (31%), Black (25%), Asian
(6%) and Native American, Native Hawaiian, or another race/ethnicity (6%). More
females (64%) participated in the survey than did males, and the modal (33%) household
income for students living at home or for financially independent students was between
$21,000 and $50,999. Eighteen percent reported living in households making less than
$11,000 annually, 27% in households making $11,000-20,999, and 22% in households
making $51,000 or more. Students ranged in age from 16 to 53 years of age, with 92%
of the sample aged 25 years or younger. Most respondents were of traditional age for first
time enrollees, with 71% of students 18 or 19 years old.
Analysis
We used two analytical techniques to explore the data. First, descriptive statistics were used to
present overall findings. Then, we used chi-square tests to determine whether statistically
significant differences existed between student subgroups’ enrollment patterns. We also used
chi-square tests to determine how our sample compared to the students’ overall college
population. In the instance of comparing the proportion of men and women recommended
to take developmental education courses instead of college-level courses, we used z-tests to
test equivalency of proportions.
1
Meta-majors are collections of academic programs that share common coursework designed to help students
select courses. Students in the Florida College System choose between eight meta-majors: arts, humanities,
communication and design; business; education; health sciences; industry/manufacturing and construction;
public safety; science, technology, and mathematics; and social and behavior sciences and human services
(Florida Administrative Code Rule 6A-14.065 2013)
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Findings
We present our findings in two parts. First, we present course enrollment patterns for students
recommended to take DE in each of the three subject areas, disaggregating these patterns by
gender, income, and race. Second, we examine the relationship between course enrollment
patterns and the factors cited as important in making these decisions, again disaggregating our
results by subject, gender, income, and race. Among exempt students, 79% were considered
college-ready and enrolled in college-level reading, 76% enrolled in college-level writing, and
58% enrolled in college-level mathematics. Thus, roughly 21% were recommended for DE
reading, 24% for writing, and 42% for mathematics. We focus on the students recommended
for DE and disaggregate them by subject area.
Course Enrollment Patterns
Overall Table 1 presents enrollment patterns for those students recommended to take DE,
disaggregated by subject area. In mathematics, 41.9% enrolled in a developmental course
(column 1), 22.5% enrolled in a college-level course instead (column 2), while 35.7% took no
mathematics course at all (column 3). In writing, 32.5% enrolled in a developmental course
(column 4), 27.4% enrolled in a college-level English course instead (column 5), while 41.3%
enrolled in no writing or English course (column 6). Finally, in reading, a mere 8% enrolled in
a developmental course (column 7), 36.1% enrolled in a college-level English course instead
(column 8), and 56.2% enrolled in no reading or English course (column 9). While more
students in our sample enrolled in developmental mathematics or writing courses as compared
to developmental reading, these patterns suggest that a sizeable number of students may
choose to either enroll directly in college-level courses or to not take any subject area courses
when DE is optional.
Table 1 Exempt Students' Enrollment in Developmental Math, Writing, and Reading as a Percentage of Those
Advised into Developmental Education By Gender, Income, and Race
Math
Writing
Reading
1 DE 2 College 3 None 4 DE 5 College 6 None 7 DE 8 College 9 None
All Students
41.9
22.5
35.7
31.5
27.4
41.3
8.0
36.1
56.2
Male
43.2
21.6
35.1
33.3
18.5
48.1
4.2
33.3
62.5
Female
40.7
18.6
40.7
25.5
29.8
44.7
7.0
30.2
62.8
Less than $11,000
44.1
11.8
44.1
34.8
13.0
52.2
9.1
31.8
59.1
$11,001-$20,999
$21,000-$50,999
56.3
28.2
18.8
20.5
25.0
51.3
33.3
19.4
25.0
35.5
41.7
45.2
0.0
0.0
26.7
39.1
73.3
60.9
$51,000 and above 44.4
27.8
27.8
37.5
12.5
50.0
28.6
14.3
57.1
Gender
Income
Race
White
48.7
15.4
35.9
25.0
30.0
45.0
5.9
29.4
64.7
Black
51.4
22.9
25.7
37.5
16.7
45.8
4.5
36.4
59.1
Latino
30.8
17.9
51.3
23.1
34.6
42.3
9.5
33.3
57.1
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Subgroups Females were more likely to be recommended for DE math. More specifically, a
z-test of equivalent proportions indicated that the share of females recommended for developmental mathematics courses was greater than the share of males (z=2.0, p<.05, two-tailed).
As a result, females accounted for nearly 70% of students recommended for DE mathematics;
and in the other subjects females accounted for 65% of students recommended for DE writing
and 64% of students recommended for DE reading (a full breakdown of these figures for all
subgroups is available from the authors). In terms of enrollment patterns, however, a chisquare test indicates no statistically significant differences in the enrollment patterns of males
versus females. In mathematics, for instance, 43.2% of males took DE mathematics when
advised to do so compared to 40.7% of females. In writing, though not statistically significant,
females (29.8%) enrolled in college-level composition at rates 11.3 percentage points higher
than males (18.5%).
In terms of income, we find that the course enrollment patterns appear to differ by income
category; however, these variations are not statistically significant. Students in the lowestincome category show the lowest rates of enrolling in a college-level mathematics course
(12%) and the highest rates of opting not to enroll in any writing course (52%). Conversely,
students in the highest income category show the highest rates of enrolling in college-level
mathematics (28%) but the lowest rates in college-level writing (13%). Again, however, chisquare tests do not reveal any significant differences between income categories.
Similarly, we observe differences in the enrollment rates by race/ethnicity although this
variation is not statistically significant. Due to small sample sizes in the various pathways for
some student groups, we present only those results for White, Latino, and Black students. With
regard to mathematics, 49% of White students, 51.4% of Black students, and 31% of Latino
students enrolled in the DE course when advised to do so. Further, 51% of Latino students
enrolled in no mathematics course whatsoever when advised to do so. In writing, 25% of
White students, 38% of Black students, and 23% of Latino students enrolled in the DE course.
In reading, 6% of White students, 5% of Black students and 10% of Latino students enrolled in
the DE course. It should be noted, however, that chi-square tests of independence do not
indicate statistically significant differences in enrollment patterns based on race/ethnicity for
any subject area. Thus, although course enrollment patterns varied by race/ethnicity for the
students in our sample in terms of the percentage of students taking different courses, we
cannot say with certainty that these patterns are significantly different from one another—a
topic that warrants future investigation.
Decision Factors
Next, we examined the decision factors associated with particular enrollment patterns. Table 2
displays the percentage of students who identified a particular factor as important or very
important, disaggregated by their course enrollment for each subject. In other words, we
present the percent of students in each pathway (took DE, took college-level, or took no
subject course) who indicated that a given decision factor was either Bvery important^ or
Bimportant^ when they made their enrollment decision. For instance, 82.8% of students who
enrolled in DE mathematics saw high school grades in certain classes as either Bvery
important^ or B important^ (table 2, column 1, row 1).
For most students, career goals were influential in their enrollment decisions. This is
particularly true for students who either enrolled in DE or enrolled in a college-level course.
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Table 2 Developmental Education (DE) Enrollment by Subject and Enrollment Decision Factors
Math
1
DE
Writing
2
3
4
College None DE
Reading
5
6
7 DE 8
9
College None
College None
Decision Factors
High school grades in certain classes 82.8 83.3
76.8
89.3 82.6
76.9
100.0 88.9
79.2
High school GPA
Postsecondary Education Readiness
Test scores
74.1 73.3
68.4 73.3
71.4
42.9
67.9 78.3
59.3 60.9
79.5
51.3
100.0 81.5
100.0 53.9
75.0
64.6
SAT scores
63.8 72.4
58.2
60.7 77.3
64.1
66.7
77.8
72.9
Work history
53.5 53.3
53.6
57.1 47.8
57.9
50.0
66.7
53.2
Military history
17.5 20.0
8.9
22.2 17.4
10.3
16.7
26.9
16.7
Program of study
Extracurricular activities
52.6 55.2
45.6 40.0
41.1
58.9
48.2 39.1
57.1 54.6
56.4
48.7
66.7
66.7
63.0
64.0
46.8
60.4
Parent recommendation
54.4 46.7
44.6
64.3 47.8
55.3
83.3
60.0
57.5
High school teacher
recommendation
65.5 56.7
60.7
67.9 68.2
68.4
83.3
76.9
66.7
High school counselor
recommendation
63.2 58.6
58.9
60.7 78.3
66.7
83.3
76.9
58.3
Cost of developmental education
84.5 70.0
73.2
75.0 82.6
74.4
83.3
76.9
66.7
Time to degree
87.9 86.7
75.0
85.7 82.6
76.9
100.0 88.5
75.0
Career goals
93.1 93.3
87.5
89.3 95.7
92.3
100.0 96.2
89.6
For instance, in mathematics, roughly 93% of the students who either took DE or enrolled in
the college-level course saw future career goals as important in their enrollment decisions,
compared to 88% of the students who did not take any core mathematics course. Further,
future career goals and time to degree were ranked among the most important factors for
students who decided to enroll in college-level coursework, across all three subjects.
The factors related to high school academic preparation tended to be important to students
who enrolled in DE courses. For instance, 100% of students who enrolled in DE reading
considered high school grades, GPA, and test scores to be important in making this decision.
Indeed, grades were also important for students who enrolled in DE mathematics (83%) and
DE writing (89%) as well as for students who decided to enroll in any college-level courses,
although at somewhat lower levels. Stated differently, students enrolling in DE courses tended
to place a strong emphasis on their current academic preparation although students enrolling in
college-level courses also thought these factors were important in making their enrollment
decisions. The difference between these groups, however, is the importance of academic
preparation relative to the importance of career goals: students enrolling in college-level
courses placed more importance on career goals.
In general, across all enrollment choices and subject areas, students tended to place little
emphasis on work history, military history, extracurricular activities, or recommendations other
than those of their college advisor. Also showing little importance across all factors is the third
group of students: those who did not take any core subject area. For example, when examining
reading enrollment specifically, those who enrolled in no college-level English course had the
lowest rates of importance on all of the 14 factors across the board. Further, these students
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showed relatively lower levels of consideration for academic preparation and future career
goals, which were the two most important factors for students taking DE or taking-college
level coursework. This suggests that students bypassing DE and not taking any core subject
course may not fully consider all of the information available to them when making enrollment
decisions. We offer a more complete discussion of the lessons gleaned from these findings in
the next section, after addressing some limitations of this study.
Limitations
Our study begins to shed important light on the enrollment decisions students are making
now that developmental education is optional – how students are making enrollment
decisions and how these decisions vary by gender, income and race. These results,
however, should be interpreted with caution given the limitations the data present. First,
as is often the case with surveys, our survey had a low response rate. In recent years,
however, a number of survey researchers have called into question the extent to which
low response rates bias results (Fosnacht et al. 2013; Groves 2006; Massey and
Tourangeau 2013; Peytchev 2013). Indeed, recent research by Fosnacht et al. (2013)
finds that response rates as low as 5% in administrations greater than 1,000 individuals
may not introduce significant bias into the interpretation of survey data. Thus, for our
response rate of 7.6%, we may not be in a situation where substantial bias has been
introduced into our findings. Still, however, we note this limitation and recognize the
need for additional research that captures a larger portion of the target population and is
expanded beyond two campuses.
In addition to sample size, chi-square goodness of fit tests indicated that the sample differs
from the colleges’ population on the basis of gender (χ2= 12.5, p < .001) and race/ethnicity
(χ2= 29.4, p < .001). Our sample consisted of 64% females while the general student
population of the two target institutions used for this study consisted of 56% females. The
disproportionate sampling of women could partially account for the larger proportion of
women recommended for DE compared to men. Also, the disproportionate sample might
explain why the results indicate that more women enrolled in a college-level writing class
despite their advisor’s recommendation to take a DE course or that more women tended to opt
out of any mathematics course.
There are also noticeable differences when comparing race/ethnicity between the study
sample and the aggregate overall population of the two colleges: Whites (31% and 41%),
Blacks (25% and 20%), Hispanics (32% and 30%), Asians (6% and 4%), and other races (6%
and 4%). White students were underrepresented in our sample, while Black students were
slightly overrepresented. This suggests that the high percentage of Black students in DE
writing and mathematics might be slightly overstated. Additionally, caution should be taken
when interpreting the enrollment patterns of White students, which has the greatest potential
for substantial variability among the population of students.
Another limitation of the study is that it was administered late in the fall semester, after
traditional course withdrawal deadlines. It is likely, therefore, that the students in the sample
represent a group of more privileged, higher ability students who may have fewer outside
demands on their time, effort, and money and therefore persisted to the near-end of the
semester. Thus, the students in our sample may represent a more academically capable group
of students.
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Despite these limitations, our study begins to uncover how students are making enrollment
decisions now that developmental education is optional for many students in the State of
Florida and identifies a number of areas for additional research. One advantage our survey has
is its ability to capture the courses students were advised to take before they made their
enrollment decisions. This data point—what a student was advised to take—is valuable and
not available from most other sources, particularly now that placement exams are not required.
Further, this study is the first to provide insight into how students are making decisions about
developmental courses and will serve as a foundation upon which research on student
decision-making in the wake of a major DE reform may be built, both in Florida as well as
in other states.
Discussion
The purposes of our study were to begin to understand student enrollment decision patterns
regarding DE in an environment of increased choice as well as to begin to unearth the rationale
behind these enrollment decisions and to provide directions for additional research. Through
the use of an online survey administered at two colleges in the Florida College System, we
identified seven general findings that appear to be in line with existing research and warrant
additional investigation.
1. Students don’t (always) do optional. Our preliminary findings suggest that many students
elect not to take DE coursework when it is optional, even when advised to enroll in DE.
As noted by Perin (2006), self-placement policies—as is the case under SB 1720—may be
inefficient if students complete a course at a mismatch to their ability or if students who
realize that they are misplaced drop out of a mismatched course or switch courses, thereby
losing instructional time in the new class. When students utilize self-placement practices,
that is, they enroll in a course above the level recommended to them, it is possible that
they find themselves in mismatched courses that may have costly consequences for them.
Additionally, Perin (2006) noted that self-placement policies may only be effective in the
context of prerequisites for courses. If prerequisite courses remain mandatory, selfplacement policies require students to begin by building a foundational understanding
of relevant material. Additional research is warranted on whether or not students who selfplace into college-level coursework endure inefficient college experiences, such as spending time and money to retake courses that they may have not be prepared to take.
Specifically, it will be important to evaluate changing enrollment patterns following the
implementation of this policy and to evaluate how these enrollment decisions are related
to students’ future academic success.
2. Some students will take DE even if it is optional. Particularly in math, some students in our
sample enrolled in DE when advised to do so even when it was optional (42%). Further,
students who enrolled in DE appear to have given serious consideration to the decision
factors related to academic preparation, i.e., high school grades, GPA, and test scores, with
an additional emphasis on career goals and time to degree. In other words, this group of
students had been given and utilized the information necessary to decide that DE is both
appropriate and necessary for their academic success, whereas others may have lacked this
information, may have ignored it, or may have seen little value in these factors. This
finding further speaks to the need to provide students with the data required to make
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3.
4.
5.
6.
informed enrollment decisions, including strongly encouraging them to take placement
tests even when optional. Again, however, additional research is warranted to investigate
how students who may have been required to take DE in the past make decisions now that
it is optional.
Opting into college-level courses may be appropriate for some students. Among the
students who enrolled in college-level courses, it is encouraging to see that most of these
students considered their current academic ability (high school grades, GPA, and test
scores). Interestingly, these students tended to place greater weight on the cost of DE,
overall time to degree, and career goals. Taken together, these students are those who had
a sharp focus on their future and believed that they would be able to be successful in
college-level work despite the deficits in their academic preparation. In many ways, this
could be seen as the purpose of community college: to provide opportunity for those who
are interested in pursuing an education and able to put forth effort to complete a course of
study. Further, a growing body of research has shown that for those students Bat the cusp^
of needing DE based on placement test scores there may be no difference in their outcome
had they taken DE or taken college-level coursework (e.g., Martorell and McFarlin 2011).
At the same time, however, these studies measured the impact solely for those students on
the cusp—not for all students and definitely not for students far from the cut score.
Further, what is not yet known is whether a recent high school graduate at any ability level
is capable of making the best possible enrollment decision. Only through future research
on the outcomes of these students who bypassed DE and took college level courses will
we be able to offer a more definite conclusion.
Some students put off taking any core subject courses whatsoever. A sizeable proportion
of students, particularly in reading, opted not to take any core courses in mathematics,
reading, or writing. In addition, low-income students have the highest rates of opting not
to enroll in any DE reading, writing, or mathematics courses when so advised. As Bailey
et al. (2010) have found, many students who do not complete their DE sequence do so
not because they drop their courses or fail them but because they do not enroll in the
courses in the first place. Thus, it is troubling to consider the academic future of these
students who bypass taking a subject course altogether—a topic that warrants additional
research.
Enrollment patterns by student characteristics warrant further investigation. Although
not statistically significant, we did observe that Black students in our sample enrolled at
higher rates in DE mathematics and writing courses than other racial/ethnic groups. Also,
Latino students and low-income students showed the highest rates of not enrolling any
core mathematics course. Not enrolling in any core subject area coursework could have
lasting implications, including lengthening time to degree. Whereas research has found
that Black and Hispanic students are among those most often recommended for DE
(Bailey et al. 2010), our findings warrant future investigation as to whether vulnerable
students follow their advisors’ recommendations, while others do not and avoid such
coursework altogether.
Students’ use of available information may be questionable. Not all of the students used
all of the information available to them when making their enrollment decisions; as noted,
students not taking any core subject course, in particular, do not appear to consider all of
the information available to them when making enrollment decisions. For example, in
some cases up to a quarter of the students did not report using time to degree as part of
their decision-making process; and some students, particularly those not enrolling in any
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subject area courses, tended not to consider prior academic preparation. These findings
bring into question whether recent high school graduates will use all of the relevant
information available when making enrollment decisions or if they, as suggested by
Chambliss and Takacs (2014), only rely on factors such as instructor, convenience, and/
or ease when making enrollment decisions.
7. Career goals and time to degree are closely related to DE enrollment. For the students
who do enroll in DE courses, career goals and time to degree are important decision factors.
In practice, advisors could use these findings to serve students better by mapping out career
goals with meta-majors and required courses, which could encourage DE enrollment for
those students whom it might benefit. This finding gives further credence to the notion that
guided pathways can improve academic success, particularly for vulnerable students, as
suggested by Jenkins and Cho (2013). Advisors could also display a variety of educational
pathways clarifying how bypassing, delaying, or enrolling in DE courses may affect
students’ educational plans in the short- and long-terms in differential ways.
Conclusion and Continued Research Agenda
Through the passage of SB 1720, the institutions of the Florida College System are now
providing more choices to their students when it comes to developmental education and course
selection. While our current research does not allow us to offer an overall critique of this policy,
this study has demonstrated how a sample of students makes decisions now that DE is optional.
The next phase of our work will involve analyses of data from all students enrolled in the
Florida College System, site visits to select campuses, and additional surveys of students and
other campus personnel as we continue to investigate the impact of the developmental
education reform efforts in Florida. This study has identified seven broad themes that will
help guide our future research. We will seek to test whether or not these same themes arise in
the data from a larger population of students in order to provide a more complete picture of the
impact of reform. We will also seek to understand how the decisions made by exempt students
relate to both proximal (completion of DE and gateway courses, persistence into the spring
semester) and distal (degree/credential attainment, transfer) outcomes. We believe that the data
from our pilot study and that planned for future research will be of interest to other institutions
and other states.
Acknowledgement This paper is based on a research project funded in part by the Bill & Melinda Gates
Foundation. The findings and conclusions within are those of the authors and do not necessarily reflect positions
or policies of the Bill & Melinda Gates Foundation.
References
Attewell, P., Lavin, D., Domina, T., & Levey, T. (2006). New evidence on college remediation. Journal of Higher
Education, 77, 886–924.
Babad, E. (2001). Students' course selection: Differential considerations for first and last course. Research in
Higher Education, 42, 469–492.
Babad, E., Darley, J. M., & Kaplowitz, H. (1999). Developmental aspects in students' course selection. Journal of
Educational Psychology, 91, 157–168.
Innov High Educ
Babad, E., & Tayeb, A. (2003). Experimental analysis of students' course selection. British Journal of
Educational Psychology, 73, 373–393.
Bailey, T., Jeong, D. W., & Cho, S. W. (2010). Referral, enrollment, and completion in developmental education
sequences in community colleges. Economics of Education Review, 29, 255–270.
Bettinger, E., & Long, B. T. (2007). Institutional responses to reduce inequalities in college outcomes: Remedial
and developmental courses in higher education. In S. Dickert Conlin & R. Rubenstein (Eds.), Economic
inequality and higher education: Access, persistence, and success (pp. 69–100). New York, NY: Russell
Sage Foundation.
Bettinger, E., & Long, B. T. (2009). Addressing the needs of underprepared students in higher education: Does
college remediation work? Journal of Human Resources, 44, 736–771.
Boatman, A., & Long, B. T. (2010). Does remediation work for all students? How the effects of postsecondary
remedial and developmental courses vary by level of academic preparation. An NCPR Working Paper. New
York, NY: National Center for Postsecondary Research.
Brooks, R. (2002). Transitional friends? Young people's strategies to manage and maintain their friendships
during a period of repositioning. Journal of Youth Studies, 5, 449–467.
Brooks, R. (2003). Young people's higher education choices: The role of family and friends. British Journal of
Sociology of Education, 24, 283–297.
Chambliss, D. F., & Takacs, C. G. (2014). How college works. Cambridge, MA: Harvard University Press.
Complete College America (2012). Guided pathways to success: Boosting college completion. Washington, DC:
Author. Retrieved from http://completecollege.org/docs/GPS_Summary_FINAL.pdf
Couturier, L. K. (2010). The rallying call: Bringing game-changing results to developmental education: The
Colloquium on State Policy Support for Developmental Education Innovation. Boston, MA: Jobs for the
Future.
DellaGioia, M. (2008). Student opinion and student course selection. Journal of Undergraduate Psychological
Research, 3, 20–25.
Feather, N. T. (1988). Values, valences, and course enrollment: Testing the role of personal values within an
expectancy-valence framework. Journal of Educational Psychology, 80, 381–391.
Fernandez, C., Barone, S., & Klepfer, K. (2014). Developmental education and student debt. Round Rock, TX:
TG Research & Analytical Services.
Florida Administrative Code Rule 6A-14.065 (2013).
Fosnacht, K., Sarraf, S., Howe, E., & Peck, L. (2013, May). How important are high response rates for college
surveys? Presented at the annual forum of the Association for Institutional Research, Long Beach, CA.
Groves, R. M. (2006). Nonresponse rates and nonresponse bias in household surveys. Public Opinion Quarterly,
70, 646–675.
Jacob, B. A., & Lefgren, L. (2004). Remedial education and student achievement: A regression-discontinuity
analysis. Review of Economics and Statistics, 86, 226–244.
Jenkins, D., & Cho, S. W. (2013). Get with the program… and finish it: Building guided pathways to accelerate
student completion. New Directions for Community Colleges, 2013(164), 27–35.
Kerin, R., Harvey, M., & Crandall, N. F. (1975). Student course selection in a non-requirement program: An
exploratory study. Journal of Educational Research, 68, 175–177.
Lay, S. M. (2010). A report of the Commission on the Future of the Community College League of California:
2020 Vision: Student Success. Sacramento, CA: Community College League of California.
Lesik, S. (2007). Do developmental mathematics programs have a causal impact on student retention? An application
of discrete-time survival and regression-discontinuity analysis. Research in Higher Education, 48, 583–608.
Leventhal, L. (1976). Do teacher rating forms reveal as much about students as about teachers? Journal of
Educational Psychology, 68, 441–445.
Martorell, P., & McFarlin, I. (2011). Help or hindrance? The effect of college remediation on academic and labor
market outcomes. The Review of Economics and Statistics, 93, 436–454.
Massey, D. S., & Tourangeau, R. (2013). Where do we go from here? Nonresponse and social measurement. The
ANNALS of the American Academy of Political and Social Science, 645, 222–236.
Melguizo, T., Hagedorn, L. S., & Cypers, S. (2008). Remedial/developmental education and the cost of
community college transfer: A Los Angeles County sample. The Review of Higher Education, 31, 401–431.
Moogan, Y. J., & Baron, S. (2003). An analysis of student characteristics within the student decision making
process. Journal of Further and Higher Education, 27, 271–287.
Pass, M. W., Mehta, S. S., & Mehta, G. B. (2012). Course selection: student preferences for instructor practices.
Academy of Educational Leadership, 16, 31–38.
Perin, D. (2006). Can community colleges protect both access and standards? The problem of remediation.
Teachers College Record, 108, 339–373.
Peytchev, A. (2013). Consequences of survey nonresponse. The ANNALS of the American Academy of Political
and Social Science, 645, 88–111.
Innov High Educ
Research for Action (2015, February). Development and implementation of multiple measures for college
placement across states and systems: Phase 1 and 2 Summary Report. Retrieved from http://www.
researchforaction.org/wp-content/uploads/2015/02/RFA-Gates-Multiple-Measures-Phase-1-and-2-ReportSummary-February-2015.pdf
Roberts, D., & Allen, A. (1997). Young applicants’ perceptions of higher education. Leeds: HEIST Research
Publications.
Scott-Clayton, J. (2012). Do high-stakes placement exams predict college success? Working Paper. No. 41. New
York, NY: Community College Research Center.
Van Wie, K. O. (2011). Academic advising and career development for undecided transfer students. In M. Poisel
& S. Joseph (Eds.), Transfer students in higher education: Building foundations for policies, programs, and
services that foster student success (pp. 89–100). Columbia, SC: National Resource Center for the First Year
Experience & Students in Transition.
Wilhelm, W. B. (2004). The relative influence of published teaching evaluations and other instructor attributes on
course choice. Journal of Marketing Education, 26, 17–30.
Wilhelm, W B., & Comegys, C. (2004). Course selection decisions by students on campuses with and without
published teaching evaluations. Practical Assessment, Research & Evaluation, 9(16). Retrieved from http://
www.pareonline.net/getvn.asp?v=9&n=16
Yeung, A., & Marsh, H. (1997). Coursework selection: Relations to academic self-concept and achievement.
American Educational Research Journal, 34, 691–720.
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