The School Counselor Caseload and the
High School-to-College Pipeline
CHENOA S. WOODS
University of California, Irvine
Thurston Domina
University of California, Irvine

Background: Advising students on the transition from high school to college is a central part
of school counselors’ professional responsibility. The American School Counselor Association
recommends a school counselor caseload of 250 students; however, prior work yields inconclusive evidence on the relationship between school counseling and school-level counseling
resources and students’ college trajectories.
Focus of Study: This study evaluates the relationship between access to school counselors and
several critical indicators of student transitions between high school and college.
Research Design: The study utilizes the Education Longitudinal Study of 2002 to explore
the relationships between the school counselor caseload and students’ progress throughout the
high school-to-college pipeline. The key indicator is the counselor caseload for students at a
given high school, measured as the number of 10th graders per counselor at the high school
at which each student is enrolled. The outcome variables are students’ college expectations,
whether students spoke with a counselor about college, taking the SAT, and college enrollment.
Logistic and multinomial logistic regression analyses are applied to examine the relationships
between these variables.
Findings: Students in schools with small counselor caseloads enjoy greater success at navigating the high school-to-college pipeline. Controlling for student- and school-level characteristics, students in schools where counselors are responsible for advising a large number of
students are less likely to speak with a counselor about college, plan to attend college, take the
SAT, and enroll in a four-year college.
Conclusions: The findings support the claim that a smaller school counselor caseload may
increase students’ access to key college preparation resources and raise four-year college enrollment rates.

Teachers College Record Volume 116, 100301, October 2014, 30 pages
Copyright © by Teachers College, Columbia University
0161-4681
1

 Teachers College Record, 116, 100301 (2014)

Although college attendance rates have increased greatly in the past several decades, issues of equity in the college preparation and admissions
process persist. A large majority of high school students expect to attend
college, yet fewer students enroll, and even fewer students graduate with
a baccalaureate degree (e.g., Solorzano, Villalpando, & Oseguera, 2005).
The road from high school to college is particularly perilous for students
from families with limited college experience, because many of these students lack access to information about college entrance requirements,
selection criteria, and cost (Kirst & Venezia, 2004). Without this critical
information, it is difficult for students to realize their college expectations,
and even high-achieving students fail to make the transition from high
school to a postsecondary educational institution (Plank & Jordan, 2001).
High school counselors have many duties, including providing students
with informational and other assistance in college preparation and attendance. The American School Counselor Association (ASCA), which
recommends that high schools maintain a ratio of 250 students per counselor, suggests that the role of school counselors includes responding
to students’ academic, career, and personal/social development. High
school counselors face the task of guiding students through adolescence
into early adulthood, preparing them to be future citizens, college students, employees, and parents; they implement their counseling program
by providing classroom guidance, individual student planning, responsive
services, and by collaborating with other educators and community members (ASCA, 2012c, 2012d).
Although counselors are charged with the task of equitably serving all
students, many scholars argue that counselors in schools that serve underrepresented students are often unable to effectively advise students
because their caseloads are too large (Cabrera & La Nasa, 2000; Corwin,
Venegas, Oliverez, & Colyar, 2004; Farmer-Hinton, 2008; Farmer-Hinton
& McCullough, 2008; González, Stoner, & Jovel, 2003; Hamrick & Stage,
2004; V. E. Lee & Ekstrom, 1987; McDonough, 1997, 2005; Muhammad,
2008; Perna et al., 2008; Rosenbaum, Stephan, & Rosenbaum, 2010). The
counselor caseload, sometimes referred to as the student–school counselor ratio, is usually measured by the number of students in a school divided by the number of counselors in a school. Many counselors manage
caseloads double or triple ASCA’s recommended caseload. Nationally,
the counselor caseload at the average high school is 471 students, and in
California, the state with the largest caseload, counselors work with more
than 1,000 students (ASCA, 2012b). Reasoning that manageable school
counselor caseloads may facilitate more efficient counseling, several
states, including Indiana, Maine, and New Hampshire have passed legislation limiting the size of counselor caseloads (ASCA, 2012a). Nevertheless,
2

 TCR, 116, 100301 The School Counselor Caseload and the High School-to-College Pipeline

with caseloads varying in size it is apparent that access to individualized
college counseling is not available to all.
J. M. Lee, Edwards, Menson, and Rawis (2011) provide a slightly better
picture, stating that as of 2008 the student-to-“college counselor” ratio was
320:1. “College counselors” are those who are responsible for providing
college counseling, either as their sole responsibility or in combination
with other counseling tasks. Although the size of average caseloads has
decreased by 49 students between 1998 and 2009, most caseloads remain
well above the recommended ratio of 250:1 (Clinedinst & Hawkins, 2011;
J. M. Lee et al., 2011).
The purpose of this paper is to examine the relationship between students’ access to college guidance, as measured by the size of the school
counselor caseload, and college-going behaviors. Situated in the hypothesis that a more manageable school counselor caseload leads to additional
opportunities for students to build social capital and progress through
the high school-to-college transition, this study uses the Educational
Longitudinal Study of 2002 (ELS:2002) to address how the size of the
counselor caseload affects students’ postsecondary educational expectations, preparation, and attendance patterns. The research questions are
as follows:
1.  What are the relationships between the counselor caseload and students’ college planning, information-gathering, and college-preparatory behavior in 10th and 12th grade?
2.  What are the relationships between the counselor caseload and students’ college enrollment patterns?
The Influence of School Counselors on High School-toCollege Transitions
The high-school-to-college pipeline begins as students develop their college expectations, long before students enroll in college. Perna (2006)
presents a model of college choice, which draws from both economic
and sociological approaches. This model has four layers: habitus (Layer
1); school and community context (Layer 2); higher education context
(Layer 3); and social, economic, and policy context (Layer 4). The outer layers inform the inner layers, which then influence college choice.
This study focuses primarily on the school and community context, but it
stands to reason that the higher education context and macrolevel influences have real impacts for counselors’ practices in schools. For example,
universities’ changing admissions policies (Level 3) and state funding
for school counselor positions (Level 4) can impact the extent to which

3

 Teachers College Record, 116, 100301 (2014)

school counselors can engage in precollege counseling. The school environment helps to develop one’s college-going habitus, or their beliefs and
worldview, which influence their attitudes, goals, and in this case, educational expectations (McDonough, 1997).
Counselors can potentially play an important role as students develop their educational plans and prepare for life after high school. They
can influence students’ college predispositions, either by encouraging
students to consider college and providing information or by acting as
gatekeepers and redirecting students with unrealistic educational expectations away from higher education. Counselors can choose the amount
and types of college and financial aid information to provide, effectively
“channeling” students towards or away from different types of colleges
(Freeman, 1997).
Stanton-Salazar and Dornbusch (1995) describe counselors as “institutional agents”: people who not only have the ability, but also have the
dedication to communicate “institutional resources and opportunities”
(p. 117). One way that counselors do so is by influencing students’ college-going habitus; primarily shaped by the individual’s background and
socialization, habitus defines a student’s view of his or her realistic possibilities (Massé, Perez, & Posselt, 2010). Counselors can influence students’ habitus directly, using their face-to-face interactions to encourage
students to formulate high expectations and provide relevant information. Additionally, counselors can shape the college-going culture of the
school itself, creating an institutional-level atmosphere that supports college preparation and attendance for all students (Jarsky, McDonough, &
Nunez, 2009; McDonough, 1997).
In addition, counselors may increase students’ social capital. Coleman
(1988) defines social capital as relationships that lead to action. When
a student develops a relationship with a school counselor, he or she
gains access to college knowledge, resources, and advice, which can play
an important role in shaping a students’ future. Social capital factors
such as encouragement from others or assistance on college applications are closely linked to students’ likelihood of attending a four-year
college; and for black and Latino students, these social capital factors
are as important in predicting college attendance as academic ability
(Perna, 2000). Counselors may have more influence in fostering college
expectations for first-generation college students and students from low
socioeconomic backgrounds compared to their peers with more collegerelated social and cultural capital (McDonough, 1997). However, negative interactions between students and school counselors can dissuade
students from approaching counselors for guidance, thus limiting students’ access to the potential social and cultural capital counselors hold.
4

 TCR, 116, 100301 The School Counselor Caseload and the High School-to-College Pipeline

Additionally, the degree to which school counselors are able to engage
in quality precollege counseling and act as positive institutional agents
may be mitigated by larger school-, district-, or state-level regulations or
resource limitations.
To effectively influence students’ habitus and social capital, counselors need to be involved consistently with students throughout their
educational careers. Farmer-Hinton and McCullough provide a particularly evocative description of this process, reporting that counselors
at a college-prep charter school “infuse college by engaging students
in informal, yet repetitive conversations about college” (2008, p. 85).
Accordingly, the relevant literature generally assumes that counselors
use their influence to broaden college access, and working with counselors will have positive effects at each stage of the college choice process
(Bryan, Moore-Thomas, Day-Vines, & Holcomb-McCoy, 2011). These
effects may be especially pronounced for students who have few other
sources of college knowledge (Eccles, Vida, & Barber, 2004; Freeman,
1997) because these students are more dependent on their school counselor to “help them receive insider information” and guide them through
the application process (McDonough, 1997, p. 101; Rosenbaum, Miller,
& Krei, 1996).
However, counselors may also play a gate-keeping role, providing concrete encouragement and information to students that they view as “college material” and withholding information from students that they believe are less likely to succeed in higher education. Studies of students
in college prep programs, magnet schools, and charter schools that are
organized around college preparatory missions provide some evidence to
support this claim (V. E. Lee & Eckstrom, 1987). When students enter into
these programs and complete the advanced courses that are required for
selective college admissions, they may signal their commitment to higher
education to counselors, creating a continual loop in which counselors
provide encouragement and information, which in turn helps students
in these programs advance toward higher education (Farmer-Hinton &
McCullough, 2008; Tuitt, Van Horn, & Sulik, 2011). Honors track students report that their counselors “knew all of us by name” (González et
al., 2003, p. 162). In these settings, counselors regularly provide students
detailed information about scholarships, internships, and jobs as well as
guidance on where to apply and attend college (Freeman, 1997). On the
other hand, lower-achieving students report limited access to college resources (Kimura-Walsh, Yamamura, Griffin, & Allen, 2009).

5

 Teachers College Record, 116, 100301 (2014)

The Consequences of High Counselor Caseloads
Encouraging students to develop college expectations and advising students as they progress through the high school-to-college transition process is time-consuming work, particularly for counselors working with students who have access to few other reliable sources of information about
college. Counselors faced with large student caseloads, therefore, may
find it especially difficult to effectively assist all students. In such a setting,
counselors may be more likely to serve a gate-keeping role as they make
strategic decisions about which students to devote college advising time
and energy toward (Corwin et al., 2004; González et al., 2003; KimuraWalsh et al., 2009). If this is the case, school-level counselor caseloads may
be negatively associated with student college expectations, access to information and, ultimately, students’ odds of enrolling in higher education.
One explanation for providing students with limited college counseling
is that, generally, counselors tend to wear many hats and have a diverse
range of responsibilities. Public high school counselors report relatively
equal amounts of time on counseling for preparing for postsecondary
education, high school course scheduling, and personal–social counseling, and an additional 14% of their time is allotted to testing (Clinedinst
& Hawkins, 2011). School counselors are responsible for a variety of tasks
including nonguidance activities and counselors’ role confusion may lead
to discrepancies between accepted counseling models and counselors’ actual duties (Burnham & Jackson, 2000; J. M. Lee et al., 2011).
Counselors work with a diverse group of students who may be gifted,
special needs, low income, English language learners, immigrants or children of immigrants, and/or of another population requiring individualized guidance. Counselors report that a wide range of tasks compete with
college counseling for their time, including individual counseling; group
counseling; classroom guidance; consultation with community agencies;
parent groups; support, prevention and intervention strategies; and the
administration of diagnostic and other standardized tests, thus some admit
to serving only portions of the population, often relatively at-risk students
(Burnham & Jackson, 2000; Perna et al., 2008; Sears, 1993). These findings vary with enrollment and the size of the counselor caseload and have
changed over time. Counselors in schools with caseloads of 500 students
or more spend substantially less time on college counseling than counselors in smaller schools and schools with smaller caseloads (Clinedinst
& Hawkins, 2011). Nationally, school counselors’ time spent on college
advising decreased between 2006 and 2009 (J. M. Lee et al., 2011).
Counselors in schools with unmanageably large student caseloads may
focus their energy on advising students at one point in the college choice
6

 TCR, 116, 100301 The School Counselor Caseload and the High School-to-College Pipeline

process at the expense of other points. There is some evidence to suggest
that overburdened counselors reserve counseling resources for upperclassmen, leaving fewer resources (i.e., time) for 9th and 10th grade students (Corwin et al., 2004). To the extent to which counselors respond to
large caseloads by adopting such an approach, we would expect caseloads
to be particularly negatively associated with students’ odds of meeting with
counselors in the early years of high school and their odds of forming
early college predispositions.
On the contrary, Rosenbaum et al. (1996), argue that counselors articulate a “college-for-all ethos” and encourage all students to formulate
college expectations, regardless of their assessment of students’ ability to
realize these expectations. Small counselor caseloads may be an indicator
of a college-going culture on campus, raising all students’ educational expectations. Nevertheless, high expectations alone do not communicate to
students the details of how and when to prepare for college; professionals
are needed to guide students through the relevant college information.
While this strategy results in universally high expectations, Rosenbaum et
al. argue that counselors do not provide students with adequate information and preparation for success in higher education. As a result, they
argue, many students move from high schools to nonselective community
colleges, where they lack the skills to succeed academically. Rosenbaum
et al.’s argument implies that counselor caseloads should correlate negatively with students’ odds of attending two-year colleges but not their odds
of four-year college enrollment.
Despite these conflicting hypotheses, we currently have very little information on the relationship between counselor caseload and student
transitions between high school and college. Carrell and Carrell (2006)
demonstrate that large caseloads undermine the extent to which counselors can prevent disciplinary problems in schools. However, this analysis provides no evidence about college outcomes. Engberg and Wolniak
(2010), meanwhile, examine the effects of counselor caseloads and other
indicators of school learning environments on students’ two- and four-year
college enrollment. This study finds that student–counselor ratios have no
direct effect on college outcomes. However, Engberg and Wolniak’s analyses include controls for student course taking and social capital. If these
factors are mechanisms through which caseloads influence college outcomes, this study may underestimate the relationship between counselor
caseloads and student college going.

7

 Teachers College Record, 116, 100301 (2014)

Method
Data Source and Measures
We use the ELS:2002 to explore the impact of the school counselor caseload on students’ educational expectations and their progress throughout
the high school-to-college pipeline. The ELS:2002 is based on a stratified
sampling design. In the first stage, a sample of 750 schools was drawn from
1,220 eligible schools. Sampled schools provided a roster of their 10th
grade students from which the study sampled approximately 30 students
from each school. In spring of 2002, when students were sophomores in
high school, all sampled students completed paper and pencil questionnaires and standardized mathematics and reading tests. In addition, the
study collected transcripts, course catalogues, and information about educational resources and school security from administrators at all sampled
high schools. In 2004, when most students were high school seniors, all
participants were resurveyed and retested. In 2006, two years after most
students have graduated from high school, students were again resurveyed
to provide information about their postsecondary experiences (Ingels et
al., 2007).
Our analyses use these data to investigate the relationship between
counseling resources in students’ high schools and their progress on the
high school-to-college pipeline. Each of these analyses takes the following
p. 12/280:
general
form:
In this equation, by indicates that the variable was taken from the
base year; f1 indicates that the variable was taken from the first followup, and f2 indicates that the variable was taken from the second followup. The CASELOAD variable is the standardized counselor caseload and
CASELOAD2 is the squared version of this variable. The STUCNTRL term
includes the student and family background variables, and the SCHCTRL
term captures schools’ urbanicity.
School Counselor Caseload
The key indicator in this study is the counselor caseload. This figure,
p. 12/280:
which represents the number of 10th graders per counselor in surveyed
students’ schools, was created by taking the 10th grade enrollment variable (BYG10ER) and dividing it by the number of school counselors employed by a school (BYA23K):

8

 TCR, 116, 100301 The School Counselor Caseload and the High School-to-College Pipeline

For example, if there are 300 10th grade students in the school and
5 counselors, the student–counselor ratio is 60:1 or 60 students per
counselor. The 10th grade enrollment and school counselor count variables are both reported in the school administrator’s questionnaire in
the base year and the caseload variable is standardized in the regression
equations. Note that this variable only accounts for 10th grade students,
resulting in smaller ratios than what may be expected if calculated using a school-wide enrollment variable. We maintain that this is the best
way to calculate the counselor caseload, given that other measures of
school enrollment in ELS: 2002 are not continuous. A squared version
of the counselor caseload variable is included to account for nonlinear
relationships.
College Expectations
College expectations and plans are measured in 10th and 12th grade, respectively. Two outcome variables, having expectations to attend a postsecondary educational institution (PEI; 10th grade; BYSTEXP) and having plans to attend college directly after high school (12th grade; F1S45)
are examined. These dummy variables are coded as one if the student
has expectations/plans for college attendance or zero if the student
does not have expectations or does not know if he or she plans to attend
college; a code of one includes any amount of college attendance, ranging from some college through advanced degree attainment.
College Information and Readiness
Speaking with a school counselor about college admissions information
is one way students gain college knowledge. Logistic regression (Cabrera,
1994) explores the impact of the counselor caseload for whether students discuss college admissions information with counselors in the
base year and in the first follow-up (BYS59B and F1S48A, respectively).
Dummy variables for 10th and 12th grade are coded as one if the student
has spoken with a school counselor about college at least once. The next
step along the education pipeline is information gathering and college
preparation. Plank and Jordan (2001) determined that preparing for,
receiving guidance about, and taking the SAT/ACT increases students’
chances of enrolling in a PEI. This dummy variable is set equal to one if
the student has taken the SAT/ACT by 12th grade (F1S21C).

9

 Teachers College Record, 116, 100301 (2014)

College Attendance
Finally, we examine the relationship between the counselor caseload and
students’ college attendance. Specifically, multinomial logistic regression
assesses the relationship between the caseload and the type of PEI attended (a two-year college or a four-year college as compared to not attending
a degree-granting institution; F2PS1LVL). This outcome is measured in
the third wave, or two years after high school.
Demographic and Control Variables
All multivariate models include controls for students’ gender and race,
their family’s socioeconomic background, their prior academic achievement, and school’s urbanicity. We operationalize gender as a dummy
variable, based on the categorical ELS: 2002 BYSEX variable. Similarly,
we operationalize race as a series of dummy variables. Using data reported in BYRACE, we categorize students as African American, white,
Hispanic, Asian, or other race. For ease of interpretation we use the
modal category—white—as the omitted category in all analyses (Hardy,
1993). We measure students’ family background using maternal educational attainment (BYMOTHED) and family income (BYINCOME).
Maternal education is a series of dummy variables with “some college” as
the reference; income is a standardized continuous variable. Students’
standardized math (BYTXMSTD) and reading (BYTXRSTD) scores are
included as standardized continuous variables in the model to account
for past academic performance. School urbanicity (BYURBAN) is included as a dummy variable (with suburban schools as the reference
category) to account for schools’ local context.
Analyses
For the purposes of this study, the sample is restricted to public school
students who did not transfer schools between the base year and the first
follow-up and who have nonmissing counselor caseload data (N = 7,800).
Due to transferring schools, attending private schools, and/or missing
data for the counselor caseload variable, 8,397 students were dropped
from the original sample. Despite small differences in the current sample
and the full sample, there were no significant differences between the two
groups on any of the dependent variables. Including students who had
transferred schools may result in including students who were enrolled in
schools with different counselor caseloads between the first and second
wave of data collection, and restricting the sample in this way holds the
counselor caseload constant over the first two waves.
10

 TCR, 116, 100301 The School Counselor Caseload and the High School-to-College Pipeline

We impute data for cases missing data on one or more control variables
using Markov chain Monte Carlo multiple imputation. All analyses were
conducted using logistic regression and multinomial logistic regression
techniques and were run only for students who have data on the counselor caseload variable and the dependent variable of interest, resulting in
different sample sizes depending on the equation. Data are weighted for
representativeness to allow for generalizing to the national population.
For analyses using only base-year variables, the base-year student probability weight (BYSTUWT) is used, for analyses using variables from the
first and second wave the first-year/follow-up panel weight (F1PNLWT)
is used, and for analyses using variables from the first and third wave,
second follow-up/base-year probability weight is used (F2BYWT).
Results
School Populations
Our preliminary analyses describe student populations at schools with
counselor caseloads of varying sizes. Table 1 separates the counselor
caseload into quartiles. The mean counselor caseload for schools with
the smallest ratios (the schools at the 25th percentile and below) is 50
students per counselor; the mean for the second quartile is 74 students
per counselor; the third quartile’s mean is 95 students per counselor;
and the mean in the top quartile is 136 students per counselor. White
students tend to be concentrated in schools with the smallest caseloads,
whereas black and Latino students are concentrated in schools with
larger caseloads. Students whose mothers have less than a high school
education are more concentrated in the quartile with the largest caseloads, but students whose mothers have an advanced degree represent
the smallest proportion of students in the highest quartile. Similarly, students with the lowest family income are much more concentrated in
the schools with the largest caseloads. Not surprisingly, schools with the
largest enrollment also have the largest counselor caseloads, but the sizeable standard deviations across all four quartiles indicate that schools of
various sizes can be found in any of the caseload quartiles.
Table 1 also demonstrates differences on student outcomes for students
in the various quartiles. The rate of speaking with a counselor about college in the 10th grade is approximately seven percentage points higher for
students in schools with the smallest counselor ratios compared to their
peers in schools with the largest caseloads. By 12th grade, that gap expands to 10 percentage points. Similarly, only 59% of students in schools
with the largest caseloads take the SAT/ACT, compared to nearly 70%

11

 12

8.6

9.0

5.8

65.0

Black

Other

White

34.8

18.1

9.0

High school diploma

Some college

College graduate

Advanced degree

0.1

0.2

Standardized math
score

62108.7

49.5

Mean

Standardized reading
score

Family income in
dollars

9.0

29.1

Less than high school

Mother’s education

11.6

Latino

48.5

%

1.0

1.0

42438.6

11.8

Std. Dev.

Smallest Caseload

Asian

Race

Male

Ratio

 

 

8.7

17.6

33.5

29.3

11.0

64.1

4.2

11.7

11.2

8.7

48.7

%

0.1

0.1

62594.6

74.2

Mean

1.0

1.0

46170.0

6.3

Std.
Dev.

Lower Midsized Caseload

7.5

15.4

33.6

28.7

15.2

57.5

5.2

13.0

15.8

8.4

50.6

%

0.0

−0.1

56980.6

94.5

Mean

1.0

1.0

42572.7

6.2

Std. Dev.

Upper Midsized Caseload

Table 1. Descriptive Statistics of Student Populations of the Counselor Caseload Quartiles

6.2

16.4

33.6

27.7

16.1

47.0

5.4

14.4

17.4

15.9

50.3

%

-0.1

−0.1

55457.0

135.5

Mean

1.0

1.0

42348.0

29.4

Std.
Dev.

Largest Caseload

Teachers College Record, 116, 100301 (2014)

 14.4

49.8

Urban

Suburban

13

94.5

Expects to attend
college

80.4

69.6

Plans to attend college

Took SAT/ACT

26.9

49.2

Attended 2-year
college

Attended 4-year
college

Second follow-up dependent variables

83.3

Spoke with counselor

First follow-up dependent variables

47.9

Spoke with counselor

Base year dependent
variables

School enrollment

35.8

%

889.2

Mean

778.3

Std. Dev.

Smallest Caseload

Rural

School urbanicity

 

 

50.3

25.6

71.4

80.9

81.8

94.4

46.9

56.9

20.2

22.8

%

1222.4

Mean

608.5

Std.
Dev.

Lower Midsized Caseload

41.3

29.2

61.8

76.5

78.1

93.6

42.4

52.2

30.4

17.3

%

1277.3

Mean

700.6

Std. Dev.

Upper Midsized Caseload

39.3

33

59.2

78.1

73.1

91.4

40.7

49.6

29.9

20.5

%

1396.9

Mean

670.1

Std.
Dev.

Largest Caseload

TCR, 116, 100301 The School Counselor Caseload and the High School-to-College Pipeline

 Teachers College Record, 116, 100301 (2014)

of students in schools with the smallest caseloads. Again, students in
schools with the largest caseloads attend 4-year colleges at the lowest
rates (39%) compared to students in schools with the smallest caseloads
(49%). These findings provide initial descriptive evidence to suggest
that students in schools with small counselor caseloads are advantaged
in the high school-to-college transition relative to their peers in schools
with higher counselor caseloads.
Tenth-Grade Outcomes
Table 2 focuses on the relationship between counselor caseloads and
10th graders’ odds of speaking with a counselor about college and articulating college expectations. This table suggests that there is a significant negative relationship between counselor caseload and students’
odds of meeting with their counselor prior to 10th grade. This relationship persists even after controlling for student and school background
characteristics, suggesting that the relationship is robust. Furthermore,
the squared term in both of these models is not significantly different
from one, suggesting that the odds of speaking with a counselor decrease incrementally as caseloads increase.
However, the next two models suggest that the associations between
counselor caseloads and 10th graders’ college expectations are much
weaker. We recognize that expectations develop through relationships
with multiple people and influences that may begin well before high
school, yet the number of students school counselors work with does not
appear to impact 10th grade students’ educational expectations. Neither
the reduced-form model nor the model with controls for student and
school characteristics return a significant relationship between caseload
and expectations.
Figure 1 helps to illustrate these findings. The figure represents the
predicted probability that students at schools with varying counselor caseloads will speak with a counselor and articulate college expectations in
10th grade, with all controls held constant at the sample mean. Students’
probability of speaking with counselors declines dramatically as school
counselor caseloads increase, pointing to a negative and significant effect of the caseload on students’ access to conversations with counselors
about college. The probability of speaking with counselors for students
in schools with the smallest caseloads is nearly 60%, but less than 40%
for students in schools with the largest caseloads. By contrast, there is
virtually no relationship between counselor caseloads and students’ college expectations, illustrating the insignificant effect of the counselor
caseload on this outcome. In sum, these findings suggest that counselor
caseloads influence students’ odds of speaking with their counselors, but
14

 TCR, 116, 100301 The School Counselor Caseload and the High School-to-College Pipeline

nearly all students expect to attend college, regardless of their access to
counselors. This finding is surprising, given scholars’ attention to the
role that counselors can play in forming students’ college expectations
(Krei & Rosenbaum, 2001; McDonough, 1997; Rosenbaum et al., 1996).
In light of limited time and resources, school counselors should focus
their efforts not solely on encouraging students to attend college but on
providing useful assistance about the specific steps students need to take
to be adequately prepared.
Figure 1. Predicted probabilities of the effect of the counselor caseload
on students’ 10th grade outcomes: whether students expect to attend
college and whether a student spoke with a school counselor about
college. Predicted probabilities from the full models in Table 2, with
control variables held at the mean.

15

 Teachers College Record, 116, 100301 (2014)

Table 2. The Counselor Caseload and the Likelihood of Speaking With a
Counselor About College and Expecting to Attend College
 
 
Counselor caseload
Counselor caseload squared

10th Grade Outcomes
Spoke With Counselor
0.814***
(0.045)
1.043
(0.032)

0.816***
(0.046)
1.045
(0.032)
0.788***
(0.046)

Male

Expects to Attend College
0.843
(0.085)
1.019
(0.058)

0.867
(0.081)
1.045
(0.070)
0.403***
(0.053)

Racea
Asian
Latino
Black
Other

1.454**
(0.179)
0.872
(0.103)
1.068
(0.124)
1.093
(0.156)

1.678
(0.468)
1.784**
(0.379)
2.182***
(0.430)
1.184
(0.327)

0.822
(0.087)
0.850*
(0.061)
0.888
(0.079)
0.975
(0.115)
1
(0.044)
1.064
(0.048)
1.052
(0.051)

0.675*
(0.133)
0.807
(0.120)
1.215
(0.285)
1.546
(0.689)
1.509***
(0.171)
1.913***
(0.203)
1.913***
(0.199)

0.882
(0.085)
0.941
(0.096)
6300

0.811
(0.122)
1.09
(0.191)
6780

Mother’s educationb
Less than high school
High school diploma
College graduate
Advanced degree
Standardized family income
Standardized reading score
Standardized math score
School urbanicityc
Rural
Urban
N

6300

6780

Note. Odds-ratios presented. Standard error located directly under coefficients. *p < .05; **p
< .01; ***p < .001. aReference category for race is white. bReference category for mother’s
education is some college. cReference category for school urbanicity is suburban school.
Analysis is for public students who have remained in the same school between 10th and 12th
grade, weighted using BYSTUWT, and clustered by school.
16

 TCR, 116, 100301 The School Counselor Caseload and the High School-to-College Pipeline

12th-Grade Outcomes
In Table 3, we examine the relationship between counselor caseloads and
12th grade students’ odds of speaking with counselors about college, odds
of articulating college plans, and odds of taking the SAT or the ACT, a major hurdle to four-year college enrollment. The first set of analyses suggests
that there is a robust negative association between counselor caseload and
12th graders’ odds of speaking with their counselor. Furthermore, this
association is much stronger than the association between caseloads and
10th graders’ odds of talking with their counselors. This finding runs contrary to the idea that overburdened counselors focus their attention on
students at the end of their high school careers.
As the counselor caseload increases, students’ likelihood of planning
to continue their education directly following high school decreases after
accounting for personal and school demographic controls. In stark contrast to the lack of significant effects of the school counselor caseload on
10th grade students’ college expectations, 12th grade students’ plans are
significantly negatively associated with an increasing counselor caseload.
Additionally, there is a significant negative association between counselor caseloads and 12th graders’ odds of completing the SAT or ACT. Each
of these relationships remains significant after controlling for student and
school background characteristics. Interestingly, the caseload squared
term is significant and positive in each of the full models in this table,
suggesting that for schools with particularly high counselor caseloads, the
negative relationship between caseload and 12th graders’ college plans
and behaviors is somewhat truncated.
Table 3. The Counselor Caseload and the Likelihood of Speaking With
a Counselor About College, Planning to Attend College, and Taking the
SAT/ACT
 

12th-Grade Outcomes
Spoke With a Counselor
About College

Counselor caseload
Counselor caseload
squared
Male

Plans to Attend
College

Took the SAT/ACT

0.695***

0.710***

0.855**

0.868**

0.758***

0.776***

(0.052)

(0.053)

(0.050)

(0.047)

(0.049)

(0.050)

1.073*

1.070*

1.083**

1.096***

1.05

1.063*

(0.030)

(0.029)

(0.032)

(0.030)

(0.030)

(0.032)

0.696***

0.484***

0.497***

(0.053)

(0.035)

(0.033)

17

 Teachers College Record, 116, 100301 (2014)

 

12th-Grade Outcomes
Spoke With a Counselor
About College

Plans to Attend
College

Took the SAT/ACT

Racea
Asian
Latino
Black
Other

1.238

3.083***

1.813**

(0.193)

(0.667)

(0.358)

0.891

1.428**

0.847

(0.125)

(0.185)

(0.106)

1.363*

2.358***

1.580***

(0.176)

(0.266)

(0.185)

0.889

0.735

0.717*

(0.161)

(0.119)

(0.114)

0.909

0.688**

0.669***

(0.117)

(0.084)

(0.080)

1.039

0.786**

0.851*

(0.101)

(0.065)

(0.066)

0.975

1.363*

1.531***

(0.111)

(0.165)

(0.173)

Mother’s educationb
Less than high
school
High school
diploma
College graduate
Advanced degree

0.815

1.508*

1.957***

(0.122)

(0.282)

(0.319)

Standardized family income

1.017

1.428***

1.564***

(0.059)

(0.076)

(0.097)

Standardized reading score

1.041

1.232***

1.540***

(0.061)

(0.068)

(0.081)

Standardized math
score

1.137*

1.447***

2.006***

(0.068)

(0.087)

(0.111)

School urbanicityc
Rural
Urban
N

6060

0.976

1.024

1.141

(0.110)

(0.096)

(0.140)

0.99

0.934

0.851

(0.121)

(0.083)

(0.099)

6060

7720

7720

7620

7620

Note. Odds-ratios presented. Standard error located directly under coefficients. *p < 0.05; **p
< .01; ***p < .001. aReference category for race is white. bReference category for mother’s
education is some college. cReference category for school urbanicity is suburban school.
Analysis is for public students who have remained in the same school between 10th and 12th
grade, weighted using F1PNLWT, and clustered by school.
18

 TCR, 116, 100301 The School Counselor Caseload and the High School-to-College Pipeline

Figure 2. Predicted probabilities of the effect of the counselor caseload
on students’ 12th grade outcomes: whether students plan to attend
college and whether a student spoke with a school counselor about
college. Predicted probabilities from the full models in Table 3, with
control variables held at the mean.

Figure 2 represents these relationships graphically, by plotting predicted probabilities that students at schools with various caseload sizes speak
with counselors about college and articulate college plans with control
variables held at the sample mean. As this figure makes clear, 12th graders in schools with large counselor caseloads are less likely to speak with
their counselors than similar students in schools with smaller caseloads,
although this relationship flattens somewhat at the top of the caseload distribution. Similarly, the figure indicates that students’ probabilities of articulating college plans decline as counselor caseloads increase, although
this relationship reverses among students in schools with the very highest
counselor caseloads.
Two points are particularly worth noting here. First, the relationship
between caseloads and students’ odds of speaking with counselors and
their odds of articulating college expectations are both much more pronounced in the 12th grade than in the 10th grade. Although there was
no relationship between caseload and expectations in the 10th grade,
the counselor caseload is significantly negatively related to 12th graders’
odds of college plans. This finding suggests that even the most overburdened counselors attempt to discuss higher education with a broad array

19

 Teachers College Record, 116, 100301 (2014)

of students at the beginning of their educational careers. In the last year of
high school, however, many students in schools with large counselor caseloads do not discuss college with a counselor. One possible explanation
for this finding is that overburdened counselors may invest their counselor resources more selectively among high school seniors. Second, the
predicted probabilities graphed in Figure 2 suggest that in schools with
an average counselor caseload or smaller, students have nearly the same
probability of speaking with counselors about college as planning to attend college. However, in schools with larger than average caseloads, these
probabilities are divergent, with more students articulating plans to attend
college than speaking with a counselor.
College Attendance
Finally, Table 4 considers the relationship between school counselor caseloads and students’ odds of enrolling in two-year and four-year colleges.
These multinomial logistic models indicate that there is no significant association between counselor caseload and students’ odds of attending a
two-year college. However, there is a negative association between counselor caseload and students’ odds of attending a baccalaureate degreegranting institution, even after controlling for student and school characteristics. This relationship is nonlinear, such that the negative association
between counselor caseload and odds of attending a four-year college is
less pronounced among schools with particularly high counselor caseloads. This suggests that negative effects of large counselor caseloads on
four-year college attendance begin to flatten in the schools with the largest caseloads.
Table 4. Multinomial Logistic Regression of Students’ Attendance at a
Postsecondary Educational Institution
 

College Outcomes
Model 1

Counselor caseload
Counselor caseload squared

Model 2

Two-Year
College

Four-Year
College

Two-Year
College

Four-Year
College

0.983

0.789***

0.997

0.798***

(0.061)

(0.053)

(0.062)

(0.050)

1.064

1.056

1.069*

1.084*

(0.037)

(0.043)

Male
Racea
20

(0.031)

(0.041)

0.630***

0.443***

(0.050)

(0.042)

 TCR, 116, 100301 The School Counselor Caseload and the High School-to-College Pipeline

 

College Outcomes
Model 1
Two-Year
College

Model 2

Four-Year
College

Asian
Latino
Black
Other

Two-Year
College

Four-Year
College

1.937**

2.802***

(0.453)

(0.622)

1.196

0.902

(0.155)

(0.133)

1.297

2.144***

(0.179)

(0.316)

0.588**

0.736

(0.120)

(0.162)

0.513***

0.471***

Mother’s educationb
Less than high school
High school diploma
College graduate
Advanced degree
Standardized family income
Standardized reading score
Standardized math score

(0.071)

(0.074)

0.690***

0.673***

(0.067)

(0.071)

1.294

1.857***

(0.207)

(0.291)

0.874

1.717*

(0.216)

(0.396)

1.401***

1.846***

(0.094)

(0.127)

1.176**

1.792***

(0.073)

(0.115)

1.389***

2.626***

(0.092)

(0.187)

0.996

1.525***

(0.119)

(0.177)

Urbanicity
Rural
Urban
N

6970

6970

0.955

0.805

(0.099)

(0.097)

6970

6970

Note. Odds-ratios presented. Standard error located directly under coefficients. *p < .05; **p
< .01; ***p < .001. Models are in comparison to no college attendance. aReference category for race
is white. bReference category for mother’s education is some college. cReference category for
school urbanicity is suburban school. Analysis is for public students who have remained in the
same school between 10th and 12th grade, weighted using F2BYWT and clustered by school.
21

 Teachers College Record, 116, 100301 (2014)

Figure 3 illustrates these findings by graphing students’ predicted probabilities of enrolling in two-year and four-year colleges, with control variables held at the sample means. This figure indicates that in schools with
the largest counselor caseloads, students’ four-year college attendance
rates are lowest and two-year college attendance rates are highest. Students
in schools with the smallest caseloads are more than twice as likely (63%)
to attend a four-year PEI as they are to attend two-year schools (28%),
however students in schools with the largest caseloads are 3% less likely to
attend 4-year PEIs (40%) than they are to attend two-year colleges (43%).
The tapering of the slope for the line of students who do not attend college indicates that students at schools with the average size caseload have
about an 18% probability of not attending college, compared to 10% for
students in schools with the smallest caseloads.
Figure 3. Predicted probabilities of the effect of the counselor caseload
on students’ likelihood of attending college. Predicted probabilities from
the full models in Table 4, with control variables held at the mean.

22

 TCR, 116, 100301 The School Counselor Caseload and the High School-to-College Pipeline

Discussion and Conclusion
The purpose of this paper is to explore the relationship between the size
of high school counselor caseloads and students’ college expectations,
preparation, and enrollment patterns. A noticeable shortcoming in the
current school counseling literature is the limited research on how counselor caseloads affect college access. Carrell and Carrell (2006) even state
that as far as they are aware, “there is no direct empirical evidence in
support of lower student to counselor ratios” (p. 2). Although there is
the general belief that smaller counselor caseloads would affect the counseling services available (e.g., Bryan, Holcomb-McCoy, Moor-Thomas, &
Day-Vines, 2009; Bryan et al., 2011; Clinedinst & Hawkins, 2011; Corwin et
al., 2004), there is virtually no research to specify the ideal caseload size,
which is surprising because ASCA (2012b) clearly communicates their recommended caseload of 250 students for every counselor.
The descriptive analyses illustrate that students who are already disadvantaged are concentrated in schools with larger counselor caseloads,
further limiting their access to knowledgeable adults. Students whose
mothers have the lowest educational attainment are most represented
in schools with an average of 135 10th grade students per counselor; the
findings are similar for students whose parents have the lowest incomes.
Black and Latino students, who have been noted to be more likely to rely
on school personnel for college information and guidance (Freeman,
1997; Perez & McDonough, 2008), are also more concentrated in the
schools with the largest caseloads, whereas white students are overrepresented in schools with the smallest caseloads. Students who already
face significant barriers to college (such as limited finances or few college-educated family or community members) also face limited access to
their school counselors due to the fact that their counselors typically have
many students to manage.
Our analyses indicate that these inequalities in access to counselors have
important consequences for students as they prepare for college throughout high school and transition from high school to college. Even after controlling for student and school background characteristics, we find that
students in schools with high counselor caseloads are less likely to speak to
their counselors, less likely to formulate and act on college plans, and less
likely to attend four-year colleges. Notably, our findings suggest that the
association between counselor caseload and student behavior are more
pronounced in the later stages of the high school-to-college transition
than the early stages, net of the same control variables. We find that nearly
all 10th graders, regardless of school-level counselor caseloads, articulate
college expectations. However, as students progress through high school,
23

 Teachers College Record, 116, 100301 (2014)

large caseloads negatively impact students’ college preparation and attendance behaviors. Previous research indicates that early and consistent
expectations for college are an important step in progressing through the
preparation process and attending four-year institutions (Klasik, 2012).
However, the current study indicates that students are formulating these
expectations independently of their access to school counselors. Based
on these findings and the extant literature, we advise counselors to guide
students through the necessary steps of preparing for and enrolling in college: taking requisite coursework and admissions examinations, applying
for financial aid, applying to multiple institutions, and finally enrolling.
The counselor caseload was also significant in predicting students’ likelihood of taking the SAT/ACT. This is an important part of college preparation because many colleges and universities, in particular closed-access
institutions, use standardized tests to evaluate students’ likelihood for success at their school and may use scores as a placement tool (e.g., indicating
whether a student needs to enroll in remedial courses). Taking these exams
signals to both teachers and counselors a student’s intent to apply for and
enroll in college (Tuitt et al., 2011). The results demonstrate that counselors’ guidance impacts student outcomes when they are related to discrete
college preparation and attendance milestones such as taking college admissions tests and actually attending college. These results align with the
findings that college coaches can increase students’ enrollment in college
by focusing efforts on distinct tasks, such as completing aid applications and
applications to three or more institutions (Stephan & Rosenbaum, 2013).
While Rosenbaum et al. (1996) worry that the “college for all” message
conveyed by U.S. high school counselors leads large numbers of unprepared students to enroll in community college, this finding indicates
that counseling caseloads are unrelated to two-year college enrollment.
However, students enrolled in schools with the lowest counselor caseloads
are more than 50% more likely to enroll in four-year colleges than their
peers in schools with the highest counselor caseloads, net of controls.
Throughout our analyses, we find evidence to suggest that the relationship between counselor caseloads and student outcomes are nonlinear,
such that students in the schools with the highest caseloads are more likely
to articulate college plans, take the SAT/ACT, and enroll in four-year colleges than one might expect given the overall relationship between caseload and student college transitions. This finding may indicate that schools
with the largest counselor caseloads have developed alternative mechanisms to provide students with college encouragement and information.
One possibility is that teachers in these schools fill in for overburdened
counselors and help students plan for college. Another possibility is that
these schools rely heavily on extracurricular college outreach programs.
24

 TCR, 116, 100301 The School Counselor Caseload and the High School-to-College Pipeline

Implications, Limitations, and Future Research
Our findings suggest that efforts to reduce counselor caseloads could
lead to improved student outcomes and more equitable access to higher
education. Smaller caseloads allow for a greater opportunity to develop
social capital, providing students with sources of college knowledge and
with each counselor potentially having increased availability for precollege counseling. Clinedinst and Hawkins (2011) argue that one way to
increase college completion is to implement state policies that will improve middle and high school counseling, which includes maintaining
reasonable school counselor and college counselor caseloads and managing counselors’ time on task. With this study and additional research,
school counseling positions may become better defined, more valued and
understood, and may enjoy greater support at district, state, and federal
levels. By communicating the importance of small counselor caseloads,
these findings may lead schools and districts to implement policies that
protect counselors’ time, such as redistributing noncounseling duties to
other employees or considering part-time or contracted employees (e.g.,
test administrators) during high-need times.
Counselors can help create and maintain a pervasive college-going culture, which may increase students’ college knowledge and improve college
attendance rates of traditionally underrepresented students, particularly
in schools with new or low college-going traditions. Part of developing a
college-going culture may include educating teachers, parents, and other
community partners about the importance of preparing early for college
and providing tools for how to talk with students about college. Districts,
particularly those with a strong college-going culture, may provide additional structural support for precollege counseling and prioritize counselors’ efforts to maintain or increase access to college and college preparation resources to all students.
However, these analyses are limited in several important ways. First, these
correlational analyses cannot conclusively isolate the causal relationship
between counselor caseloads and student outcomes. While our analyses
control for a limited set of student demographic family background characteristics, as well as students’ prior achievement, other factors such as
wealth, neighborhood quality, and commitment to college may confound
observed associations between counselor caseloads and student outcomes.
Second, as mentioned, this study takes into account the effects of several
demographic differences by controlling for these variables, yet we do so
in reference to white and female students and include a continuous variable for income. We call for future research to examine how the counselor
caseload distinctly impacts outcomes for students in various racial/ethnic,
25

 Teachers College Record, 116, 100301 (2014)

income, immigrant, and primary language subgroups and school settings
(e.g., charter schools and school urbanicity) by analyzing subgroups separately. Third, although this study provides a view of how the size of the
counselor caseload affects students’ postsecondary choice process, this dataset does not have qualitative or frequency measures of students’ interactions with counselors. Because of this we cannot understand how these
student–counselor interactions occurred, who initiated them, the duration
or frequency of the meetings, or the type of guidance provided. It is plausible that several one-on-one meetings with a school counselor could have a
very different effect than one large-group assembly. Additionally, students’
interactions with college coaches or other noncredentialed personnel
would not be captured in the current study but could lead to sizable effects
in student outcomes. Chicago Public Schools employed college coaches
who assisted students in completing key actions in the college preparation
process. In these schools more students completed the Free Application
for Federal Student Aid (FAFSA) and three or more college applications,
as compared to schools without college coaches (Stephan & Rosenbaum,
2013). Employing college coaches may improve college preparation and
attendance rates without increasing the number of school counselors.
Using another dataset, such as the High School Longitudinal Study of
2009, which has a counselor survey in addition to the administrator instrument, could aid our understanding of school counselors’ use of time,
counselors’ caseloads, and schools’ college preparation resources. Followup studies using future waves of the ELS: 2002 data could also lead to
a better understanding of long-term effects of the size of the counselor
caseload regarding degree completion and earning potential.
Further investigation using a variety of analytical approaches and settings of how counselor caseloads affect student outcomes is warranted to
better illustrate the effectiveness of the school counselor and the impacts
of the size of the school counselor caseload. In addition to high schools,
middle school counseling programs should also be examined; monitoring counselor caseloads in middle school may increase students’ access
to academic pathways that lead to college eligibility and readiness (J. M.
Lee et al., 2011). Furthermore, precollege counseling may occur in less
formal spaces and from multiple sources. Exploring how counselors and
schools partner with community resources such as afterschool programs
or local community and industry leaders and how students use in-school
and out-of-school resources can result in a better allocation of counselors’
time and other resources.
Mixed-methods research in this area could provide useful information
on how counselors and counseling resources are allocated and utilized
and may add to the generalizability of the current findings (Carter &
26

 TCR, 116, 100301 The School Counselor Caseload and the High School-to-College Pipeline

Hurtado, 2007). Comparative analyses between schools with large and
small caseloads, and mixed-methods case studies in particular, may provide insight on how counselors employ college guidance techniques, to
which students, and the extent to which this guidance translates into observable actions (i.e., ordering and submitting high school transcripts for
college). Additionally, accounts from multiple school personnel, (e.g., administrators, counselors, teachers, and paraprofessionals) students, and
parents could provide for a well-rounded understanding of how school
counselors affect student outcomes. Student and counselor narratives may
illuminate the college choice process even further, allowing for a rich understanding of precollege counseling interactions and influences. These
suggestions are not exhaustive but can address some limitations of the current dataset and the limited research in the field. This paper attempts to
fill the current gap in research about the relationships between the school
counselor caseload and student outcomes and may open the door to additional empirical work exploring the profession of high school counseling
in regards to college access and attendance, as well as other indicators of
student success.

27

 Teachers College Record, 116, 100301 (2014)

References
American School Counselor Association. (2012a). State school counseling mandates and legislation.
Retrieved
from
http://www.schoolcounselor.org/school-counselors-members/
careers-roles/state-school-counseling-mandates-and-legislation
American School Counselor Association. (2012b). Student-to-school counselor ratio 2010–2011.
Retrieved from http://www.schoolcounselor.org/asca/media/asca/home/ratios10-11.
pdf
American School Counselor Association. (2012c). The role of the professional school
counselor. Retrieved from http://www.schoolcounselor.org/asca/media/asca/home/
RoleStatement.pdf
American School Counselor Association. (2012d). Why secondary school counselors? Retrieved
from
http://www.schoolcounselor.org/school-counselors-members/careers-roles/
why-secondary-school-counselors
Bryan, J., Holcomb-McCoy, C., Moor-Thomas, C., & Day-Vines, N. L. (2009). Who sees the
school counselors for college information? A national study. Professional School Counseling,
12(4), 280–291.
Bryan, J., Moore-Thomas, C., Day-Vines, N. L., & Holcomb-McCoy, C. (2011). School
counselors as social capital: The effects of high school college counseling on college
application rates. Journal of Counseling & Development, 89, 190–199.
Burnham, J. J., & Jackson, C. M. (2000). School counselor roles: Discrepancies between
actual practice and existing models. Professional School Counseling, 4(1), 41–48.
Cabrera, A. F. (1994). Logistic regression analysis in higher education: An applied perspective.
In J. C. Smart (Ed.), Higher education handbook of theory and research (Vol. 10, pp. 225–256).
New York: Agathon Press.
Cabrera, A. F., & La Nasa, S. M. (2000). Understanding the college-choice process. New
Directions for Institutional Research, 107, 5–22. 
Carrell, S. E., & Carrell, S. A. (2006). Do lower student to counselor ratios reduce school
disciplinary problems? Contributions to Economic Analysis & Policy, 5(1), 1.
Carter, D. F., & Hurtado, S. (2007). Bridging key research dilemmas: Quantitative research
using a critical eye. New Directions for Institutional Research, 133, 25–35.
Coleman, J. S. (1988). Social capital in the creation of human capital. The American Journal
of Sociology, 94(Supplement: Organizations and Institutions: Sociological and Economic
Approaches to the Analysis of Social Structure), S95–S120.
College Board. (2011). The completion agenda 2011 progress report. New York: Author.
Corwin, Z. B., Venegas, K. M., Oliverez, P. M., & Colyar, J. E. (2004). School counsel: How
appropriate guidance affects educational equity. Urban Education, 39(4), 442–457.
doi:10.1177/0042085904265107
Eccles, J. S., Vida, M. N., & Barber, B. (2004). The relation of early adolescents’ college plans
and both academic ability and task-value beliefs to subsequent college enrollment. The
Journal of Early Adolescence, 24(1), 63–77. doi:10.1177/0272431603260919
Engberg, M. E., & Wolniak, G. C. (2010). Examining the effects of high school contexts
on postsecondary enrollment. Research in Higher Education, 51, 132–153. doi:10.1007/
s11162-009-9150-y
Farmer-Hinton, R. L. (2008). Social capital and college planning: Students of color using
school networks for support and guidance. Education and Urban Society, 41(1), 127–157.
doi:10.1177/0013124508321373
Farmer-Hinton, R. L., & McCullough, R. G. (2008). College counseling in charter schools:
Examining the opportunities and challenges. The High School Journal, 91(4), 77–90.

28

 TCR, 116, 100301 The School Counselor Caseload and the High School-to-College Pipeline

Freeman, K. (1997). Increasing African Americans’ participation in higher education:
African American high-school students’ perspectives. The Journal of Higher Education,
68(5), 523–550.
González, K. P., Stoner, C., & Jovel, J. E. (2003). Examining the role of social capital in access
to college for Latinas: Toward a college opportunity framework. Journal of Hispanic Higher
Education, 2(2), 146–170. doi:10.1177/1538192702250620
Hamrick, F. A., & Stage, F., K. (2004). College predisposition at high-minority enrollment
low-income schools. The Review of Higher Education, 27(2), 151–168.
Hardy, M. A. (1993). Regression with dummy variables. Newbury Park, CA: Sage Publications,
Inc.
Ingels, S. J., Pratt, D. J., Wilson, D., Burns, L. J., Currivan, D., Rogers, J. E., & HubbardBednasz, S. (2007). Educational longitudinal study of 2002 (ELS:2002) Base-year to second
follow-up data file documentation. Washington, DC: U.S. Department of Education, National
Center for Education Statistics.
Jarsky, M. K., McDonough, P. M., & Nunez, A. M. (2009). Establishing a college culture in
secondary schools through P-20 collaboration: A case study. Journal of Hispanic Higher
Education, 8(4), 357–373.
Kimura-Walsh, E., Yamamura, E. K., Griffin, K. A., & Allen, W. R. (2009). Achieving the
college dream? Examining disparities in access to college information among high
achieving and non-high achieving Latina Students. Journal of Hispanic Higher Education,
8, 298–315.
Kirst, M. W., & Venezia, A. (Eds.). (2004). From high school to college: Improving opportunities for
success in postsecondary education. San Francisco, CA: Jossey-Bass Publishers.
Klasik, D. (2012). The college application gauntlet: A systematic analysis of the steps to fouryear college enrollment. Research in Higher Education, 53(5), 506–549.
Krei, M. S., & Rosenbaum, J. E. (2001). Career and college advice to the forgotten half: What
do counselors and vocational teachers advise? Teachers College Record, 103(5), 823–842.
Lee, J. M., Jr., Edwards, K., Menson, R., & Rawls, A. (2011). The college completion agenda: 2011
progress report. College Board Advocacy & Policy Center.
Lee, V. E., & Ekstrom, R. B. (1987). Student access to guidance counseling in high school.
American Educational Research Journal, 24(2), 287–310.
Massé, J. C., Perez, R. J., & Posselt, J. R. (2010). Revisiting college predisposition: Integrating
sociological and psychological perspectives on inequality. Equity & Excellence in Education,
43(3), 279–293. doi:10.1080/10665684.2010.492271
McDonough, P. M. (1997). Choosing colleges: How social class and schools structure opportunity.
New York: State University of New York Press.
McDonough, P. M. (2005). Counseling and college counseling in America’s high schools. Alexandria,
VA: National Association for College Admission Counseling.
Muhammad, C. G. (2008). African American students and college choice: A consideration
of the role of school counselors. NASSP Bulletin, 92(2), 81–94. doi: 10.1177/
0192636508320989
National Association for College Admission Counseling. (2011). State of college admission,
2011. Washington, DC: Author
Perez, P. A., & McDonough, P. M. (2008). Understanding Latina and Latino college choice:
A social capital and chain migration analysis. Journal of Hispanic Higher Education, 7(3),
249–265. doi:10.1177/1538192708317620
Perna, L. W. (2000). Differences in the decision to attend college among African Americans,
Hispanics, and whites. The Journal of Higher Education, 71(2), 117–141.

29

 Teachers College Record, 116, 100301 (2014)

Perna, L. W. (2006). Studying college access and choice: A proposed conceptual model. In
J. C. Smart (Ed.), Higher education: Handbook of theory and research (Vol. 21, pp. 99–157).
New York: Springer Press.
Perna, L. W., Rowan-Kenyon, H. T., Thomas, S. L., Bell, A., Anderson, R., & Li, C. (2008).
The role of college counseling in shaping college opportunity: Variations across high
schools. The Review of Higher Education, 31(2), 131–159.
Plank, S. B., & Jordan, W. J. (2001). Effects of information, guidance, and actions on
postsecondary destinations: A study of talent loss. American Educational Research Journal,
38(4), 947–979. doi:10.3102/00028312038004947
Rosenbaum, J. E., Miller, S. R., & Krei, M. S. (1996). Gatekeeping in an era of more open
gates: High school counselors’ views of their influence on students’ college plans.
American Journal of Education, 104(4), 257–279.
Rosenbaum, J. E., Stephan, J. L., & Rosenbaum, J. E. (2010). Beyond one-size fits-all college
dreams. American Educator, 34(3), 2–13.
Sears, S. J. (1993). The changing scope of practice of the secondary school counselor. School
Counselor, 40(5), 384–388.
Solorzano, D. G., Villalpando, O., & Oseguera, L. (2005). Educational inequities and
Latina/o undergraduate students in the United States: A critical race analysis of
their educational progress. Journal of Hispanic Higher Education, 4(3), 272–294.
doi:10.1177/1538192705276550
Stanton-Salazar, R. D., & Dornbusch, S. M. (1995). Social capital and the reproduction of
inequality: Information networks among Mexican-origin high school students. Sociology
of Education, 68(2), 116–135.
Stephan, J. L., & Rosenbaum, J. E. (2013). Can high schools reduce college enrolment gaps
with a new counseling model? Educational Evaluation and Policy Analysis, 35(2), 200–219.
Tuitt, F. A., Van Horn, B. N., & Sulick, D. F. (2011). Transmitting the right signals: The
continued significance of promoting college entry to students of color. Enrollment
Management Journal, 5(1), 10–31.

CHENOA S. WOODS is a doctoral candidate in the School of Education at
the University of California, Irvine. Her research explores how underrepresented minority students and students from low-income backgrounds
prepare for the transition between high school and college within their
social contexts.
THURSTON DOMINA is an associate professor in the School of Education
at the University of California, Irvine. His research pairs the demographic
and economic empirical methods with sociological theory to better understand the relationship between education and social inequity in the
contemporary United States. His most recent publication explores the relationships between merit aid programs and students’ achievement and
college trajectories.

30