THE ROLE OF THE NET PRICE CALCULATOR IN THE COLLEGE CHOICE PROCESS: A MIXED METHODS CASE STUDY OF A HIGH-COST

PRIVATE UNIVERSITY IN THE MIDWEST

A dissertation submitted

by

Melanie K. Weaver

toBenedictine University

in partial fulfillmentof the requirements for the degree of

Doctor of Educationin

Higher Education and Organizational Change

This dissertation has been accepted for the facultyof Benedictine University

__________________________________ _____________________ ___________Dissertation Committee Director Date

__________________________________ _____________________ ___________Dissertation Committee Chair Date

__________________________________ _____________________ ___________Dissertation Committee Reader Date

__________________________________ _____________________ ___________Program Director, Faculty Date

__________________________________ _____________________ ___________Faculty Date

__________________________________ _____________________ ___________Dean, College of Education and Health Services Date

Copyright by Melanie K. Weaver, 2016All rights reserved

ACKNOWLEDGEMENTS

There are so many people I wish to thank for their continued support, guidance,

and encouragement over the last four years. I am very grateful to Dr. Jan Perney, my

director, for all of the time he spent guiding me through the dissertation process. His

expertise and support were invaluable and truly appreciated. I also thank my committee

chair, Dr. Tamara Korenman, and committee member, Dr. Lawrence Lesick, for the time

they spent reviewing drafts and offering feedback and suggestions. I could not have

completed this project without the support and guidance of my director and committee

members.

I gratefully acknowledge the many individuals at my university who offered

encouragement and support as I made my journey through the doctoral program. I am

indebted to my past and present supervisors, co-workers, and staff members for their

understanding and willingness to support my goal of obtaining this degree.

I hold heartfelt appreciation for my family for their love and encouragement. I

am deeply grateful for my husband, William, and my children, Aeris and Anden, who

were patient through the many hours I invested to reach this goal and who have supported

me unconditionally. I also sincerely appreciate my parents who have always believed in

me and encouraged me to pursue my dreams. I offer special thanks to my sister Megan

who has always been there to listen and offer support and to my niece Myahrissa for

continually believing in me.

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Finally, I thank my friend Linda, who I met during our first class in the doctoral

program. I truly could not have made it through all of this without her friendship. Even

though we live hundreds of miles apart, she was always a phone call away when I needed

words of encouragement or a reminder that I was capable of completing this task.

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TABLE OF CONTENTS

ACKNOWLEDGEMENTS................................................................................................iii

LIST OF TABLES...............................................................................................................x

LIST OF FIGURES...........................................................................................................xii

ABSTRACT.....................................................................................................................xiii

CHAPTER ONE: INTRODUCTION..................................................................................1

Federal NPC Mandate..........................................................................................................2

Statement of the Problem.....................................................................................................4

Conceptual Framework........................................................................................................5

Rationale for the Study........................................................................................................7

Purpose of the Study............................................................................................................8

Research Questions and Hypotheses...................................................................................9

Quantitative Research Questions and Hypotheses.......................................................9

Qualitative Research Questions..................................................................................10

Justification for a Mixed Methods Approach to the Study................................................11

Organization of the Study..................................................................................................12

CHAPTER TWO: REVIEW OF THE LITERATURE.....................................................13

History of Federal Government Involvement in Higher Education...................................14

Recent Initiatives of the Federal Government............................................................16

Spellings Commission.........................................................................................16

Higher Education Opportunity Act of 2008........................................................17

Net Price Calculator (NPC).................................................................................18

Financial Aid Shopping Sheet.............................................................................18

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College Affordability and Transparency Center.................................................19

College Choice Models......................................................................................................19

Early College Choice Models.....................................................................................19

Contemporary College Choice Models......................................................................21

Chapman’s model of college choice....................................................................21

Hossler and Gallagher’s model of college choice...............................................21

Pitre, Johnson, and Pitre’s model of college choice............................................23

Perna’s model of college choice..........................................................................23

Factors That Influence College Choice..............................................................................26

Academic Success......................................................................................................26

Race and Ethnicity......................................................................................................28

Parents and Family.....................................................................................................31

Family characteristics..........................................................................................32

Parent education..................................................................................................33

Parent wealth.......................................................................................................34

Parent influence...................................................................................................37

Distance From Home..................................................................................................39

Gender.........................................................................................................................40

Cost and Financial Aid...............................................................................................41

Cost concerns.......................................................................................................41

Understanding of college costs............................................................................44

Financial aid........................................................................................................45

Student Choice for a Private College..........................................................................47

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Existing NPC Research......................................................................................................48

Summary............................................................................................................................49

CHAPTER THREE: METHODOLOGY..........................................................................51

Setting and Participant Sample of the Study......................................................................52

Data Sources......................................................................................................................55

Quantitative Data........................................................................................................55

Qualitative Data..........................................................................................................56

Data Collection..................................................................................................................58

Quantitative Data........................................................................................................58

Qualitative Data..........................................................................................................59

Data Analysis.....................................................................................................................60

Quantitative Data Analysis.........................................................................................60

Qualitative Data Analysis...........................................................................................62

Positionality of the Researcher..........................................................................................62

Limitations.........................................................................................................................63

CHAPTER FOUR: PRESENTATION OF THE DATA...................................................64

Quantitative Data Collection..............................................................................................65

Quantitative Descriptive Statistics.....................................................................................66

Quantitative Data Analysis................................................................................................68

Research Question One...............................................................................................68

Research Question Two..............................................................................................70

Research Question Three............................................................................................72

Qualitative Data Collection................................................................................................77

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Qualitative Descriptive Statistics.......................................................................................80

Qualitative Data Analysis..................................................................................................81

NPC Used to Narrow Choice......................................................................................81

Concerns About Accuracy..........................................................................................83

Surprising Results.......................................................................................................83

Factors Beyond Price..................................................................................................84

Athletics...............................................................................................................84

Location...............................................................................................................85

Academic Major..................................................................................................86

Limited Parental Involvement in the Decision...........................................................86

Incorrect Factors.........................................................................................................87

Summary of Quantitative and Qualitative Findings..........................................................88

CHAPTER FIVE: SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS......90

Summary of the Findings...................................................................................................90

Findings and Interpretations..............................................................................................92

Discussion of the Quantitative Results.......................................................................92

Discussion of the Qualitative Results.........................................................................97

Integration of the Quantitative and Qualitative Findings.........................................103

Relationship of the Findings to the Study’s Conceptual Model...............................105

Limitations.......................................................................................................................108

Implications for Practice..................................................................................................109

Recommendations for Future Research...........................................................................112

Conclusions......................................................................................................................113

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REFERENCES................................................................................................................115

APPENDIX A: Interview Questions...............................................................................124

APPENDIX B: Informed Consent Form.........................................................................126

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LIST OF TABLES

Table Page

1. Comparison of Institutional Characteristics...............................................................53

2. Comparison of Undergraduate Student Characteristics.............................................54

3. Characteristics of Each Student to be Interviewed....................................................57

4. Comparison of Demographics for Self-Identified Users and All NPC Users...........61

5. Descriptive Statistics for the Continuous Variables..................................................67

6. Frequencies for the Non-Continuous Variables.........................................................68

7. Crosstabulation Between Application to All-American University and

Use of the NPC..........................................................................................................69

8. Crosstabulation Between Enrollment at All-American University and

Use of the NPC..........................................................................................................70

9. Crosstabulation Between Application to All-American University and

Use of the NPC as a First Contact With the University............................................71

10. Crosstabulation Between Enrollment at All-American University and

Use of the NPC as a First Contact With the University............................................72

11. Standardized Canonical Discriminant Function Coefficients to Predict

Application to the University....................................................................................74

12. Classification Results to Predict Application at the University.................................74

13. Standardized Canonical Discriminant Function Coefficients to Predict

Enrollment at the University.....................................................................................76

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14. Classification Results to Predict Enrollment at the University..................................76

15. Characteristics and Size of Each Subgroup...............................................................78

16. Demographic Characteristics of Student Interviewees..............................................81

17. Relationships Between Quantitative Data, Qualitative Data, and Suggestions for

Practice....................................................................................................................110

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LIST OF FIGURES

Figure Page

1. Perna’s (2006a) model of student college choice......................................................6

2. Timeline for qualitative data collection and analysis..............................................60

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ABSTRACT

This study employed a mixed methods approach to research the role of the federally

mandated net price calculator (NPC) in the college choice process. Quantitative data

containing student-submitted entries from one university’s NPC were analyzed to answer

research questions regarding the timing and significance of NPC use on application and

enrollment at the university. Following the quantitative data analysis, student users of the

NPC were interviewed and responses analyzed using qualitative methods to answer

research questions related to perceptions of NPC results, reasons for NPC use, and the

role of the NPC in college choice. Findings from the quantitative analysis demonstrated

that very few students used the NPC tool. Of those students who did use the tool, those

who used the NPC as an initial contact with the university were less likely to

subsequently apply and enroll than students who used the NPC later in the inquiry

process. The quantitative analysis also found that students with a higher GPA, students

living in-state, students from a household with multiple family members, and those with a

lower parent AGI were more likely to apply. Students with a higher GPA and those

living in-state were more likely to enroll. Findings from the qualitative analysis revealed

six themes and three sub-themes including: (a) use of the NPC to narrow college choice;

(b) concerns about accuracy of the tool; (c) surprise at the results of the NPC; (d) limited

parental involvement; (e) use of inaccurate information; and (f) factors beyond price

which include the subthemes of athletics, location, and academic major.

xiii

CHAPTER ONE

INTRODUCTION

All-American University, a fictitious name for the university at which this study

was conducted, is a small, private university in the Midwest. Since the Great Recession,

the University has struggled to recruit students because of cost. A survey of 2014

admission applicants who did not enroll at All-American indicated that high cost was the

greatest influence for 45% of the students. Students cited concerns about their parent’s

ability to pay and rising tuition as major affordability concerns. The price sensitivity of

All-American admission applicants is likely a factor of the type of student that All-

American typically attracts. Over 80% of All-American’s enrolled students reside in the

state. Many of these students come from families with modest incomes and resources.

The median family income of All-American students is just over $90,000. In addition,

fewer than half of All-American students come from a household where both parents

have completed college.

Because cost is a significant concern for many prospective students at All-

American, enrollment staff members continually highlight the value of the University to

prospective students to encourage enrollment. An excellent job placement rate and

internship opportunities for students are attractive to many families and often help to ease

student concerns about cost. All-American knows that a conversation about value must

often go with a conversation about cost so as to encourage student application and

enrollment. A presentation of cost without a conversation about value concerns the

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enrollment management team at All-American and leaves the team wondering how the

net price calculator (NPC) affects application and enrollment at the University.

In order to comply with federal regulations, All-American developed a NPC and

provided the link on the school’s website, but personnel are concerned that this tool will

deter families from learning about the benefits of All-American. While the NPC provides

families with an estimate of the net price (sticker price minus financial aid), All-

American fears that families are deterred from further investigating the University after

using the NPC. The NPC does not give admission and financial aid counselors at All-

American an opportunity to have a value conversation with a family. The focus is only

on cost, one of All-American’s least attractive qualities to a student. Thus, enrollment

staff members at All-American University need more information about the true impact

of the NPC on recruiting efforts. Is it helpful or harmful in the admissions process?

Federal NPC Mandate

Within the past decade, the call for consumer information in higher education has

been ever increasing. New federal mandates have been issued; tools have been created;

and reports have been published. The Spelling’s Commission publication, A Test of

Leadership: Charting the Future of U.S. Higher Education, recommended “a robust

culture of accountability and transparency throughout higher education” (U.S.

Department of Education, 2006, p. 20). The commission made six overall

recommendations for new regulations including one for transparency and accountability

for the costs of college, something that was quickly becoming a national concern. The

NPC mandate by the federal government was born from this desire to provide students

and their families with information about college costs.

2

In the Higher Education Opportunity Act of 2008 (HEOA), a reauthorization of

the Higher Education Act of 1965, a requirement was added that any postsecondary

institution receiving Title IV assistance must post a NPC on its website to give

prospective full-time freshman students an “average yearly price” for attending the

college (U.S. Department of Education, 2008, p. 32). The government’s goal in this

regulation was to help students understand the “true cost” of college, all costs the student

would encounter minus what financial aid could be offered from all sources including

from the institution, state government, and federal government. All institutions were

required to post their NPCs by October 2011.

The HEOA mandate offered a federal template for colleges to use but allowed an

alternative option for colleges to develop their own NPC or purchase a NPC product from

a third party. Fear arose at many colleges that the federal calculator template was too

general and that net price estimates could be considerably flawed for many families

because the federal template used overall averages. For this reason, many colleges have

spent considerable financial resources to provide the required NPC, with many paying as

much as $20,000 annually (Flegenheimer, 2012). Although colleges have spent this

money, little is known about the impact of the NPC product on recruiting students.

While much research exists on the college decision process and how cost

information influences college search and decision making, very little research exists on

the use of the NPC and the impact of the NPC on the college decision process. Only a

handful of reports exist, and most of these are from 2012 or earlier. The lack of research

is likely due to the NPC mandate being less than three years old, but the impact of the

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lack of research is profound. This can be seen in the inconsistent ways colleges are

posting the NPC, promoting it, and using the data produced from it.

Statement of the Problem

Even though many colleges have invested in elaborate and complex third-party

NPCs, it is still unknown how the NPC affects student and family perceptions of cost.

Colleges need more information about the impact of the NPC on application and

enrollment.

Current research indicates that students and their families will often eliminate a

school based on sticker price alone. National surveys of prospective college students

show that over half of them have eliminated a college based on price and before any

financial aid is calculated (Hesel & Meade, 2012; Hesel & Williams, 2010). Encouraging

use of the NPC might decrease this percentage, but recent research indicates that if a

student is disappointed in the level of financial aid offered, the effect on enrollment is

very negative (DesJardins, Ahlburg, & McCall, 2006).

This confusion over whether the NPC hurts or helps student recruitment has

caused many colleges to avoid promoting their NPC. Some colleges have even tried to

“bury” the calculator on their websites to make it difficult to find. News articles with

titles such as “Good Luck Finding a Net Price Calculator” (O’Shaughnessy, 2011) and

“How to Find ‘Hidden’ Net Price Calculators” clearly show this trend (The Princeton

Review, 2012). Cheng (2012) reported that many NPCs were not easy to find on school

sites, and close to a third of the 50 schools reviewed reported links to the Department of

Education that would not help a family find the NPC. In a survey conducted by the Noel-

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Levitz (2013) firm, over 60% of students reported that they had not used a NPC because

they had not found one.

These actions have been interpreted by many to mean that colleges do not wish to

be transparent and do not want families to know about cost; however, for most colleges,

this is not accurate. Many private colleges believe that students and families should

understand costs and be able to plan for college, but fear that NPC data may be

misunderstood and deter a student from further exploring the institution. NPCs do not

present the value of a college beyond cost, such as job placement rates, and they do not

showcase the academic programs a college offers. In addition, NPCs use data entered by

families. If these data are entered incorrectly, or are not accurate, then an incorrect

financial aid estimate is presented to the student. This misinformation may cause

students to cross a prospective college off of their search lists.

More information is also needed to help identify the kind of students and families

who are using the NPC. Is it more affluent families? Are low-income and minority

students using the NPCs? The federal government’s intention with the mandate was to

provide open access and information to all students, but research is needed to determine

if all populations are using the NPC as intended.

Conceptual Framework

This research study on the NPC is shaped by Perna’s (2006a) model of college

choice. The model developed by Perna (2006a) states that student college choice is a

process of the student evaluating the costs and benefits of a college related to the

student’s academic abilities and the resources available to the student. Further affecting

the student’s college choice are layers of influence from a student’s habitus, school, and

5

community as well as influences from institutions of higher education, the economy, and

public policies. A visual representation of Perna’s (2006a) model is shown in Figure 1.

Figure 1. Perna’s (2006a) model of student college choice.

Perna’s model demonstrates the complexity of college choice when a student is

deciding to enroll at All-American. As indicated previously in this chapter, many

students at All-American University are sensitive to cost. University survey data indicate

that students weigh the cost of All-American along with its perceived benefits, such as

job-placement rate, hands-on learning, and opportunities to work one-on-one with

6

faculty. These survey results fit with the cost and benefit analysis central to Perna’s

model and also links to the third layer of institutional characteristics. In addition, school

location has proven to be influential because most students who enroll and attend All-

American University reside within the state.

Data from All-American also show that socioeconomic status is important in

student college choice. Students who feel their parents cannot afford to pay for an

education at All-American, or have little family support, will often choose a different

university to attend. There is also evidence that public policy, in Perna’s fourth layer,

does affect a prospective student’s college choice of All-American. Federal and state

policies that have created additional financial aid opportunities for students have

influenced students’ decisions to enroll at All-American. For example, new policies for

veteran benefits increased enrollment of veterans and their dependents at the university,

and policies that created new financial aid awards for certain academic majors were also

influential.

What is unknown is the level of influence of NPC results on college choice in

relation to other layers of Perna’s model. This research seeks to understand how the NPC

fits into the layers of Perna’s (2006a) model for prospective students at All-American

University.

Rationale for the Study

This study contributes to the research on NPCs in several ways. First, this study

helps college personnel to understand how and when students use a NPC. More

information is needed about why students decide to use a NPC, how they use it, and when

7

they choose to use it. This information can help enrollment management professionals to

target marketing messages to students.

Second, this research helps college personnel to understand how the raw file of

NPC users can be used to improve admissions recruiting. This study identifies significant

variables in the data that may be useful in the recruiting process and for signifying the

likelihood of a student applying and enrolling. If variables indicate a lower likelihood to

enroll, staff can use this information to recruit prospective students in a different way.

These data can also help college personnel to understand whether the NPC results are

perceived positively or negatively by prospective students.

Third, this research identifies which students are using the NPC. The data

analysis shows whether all populations are using the NPC, or if use is limited to certain

sub-populations, such as students with more family resources or those who have higher

academic standing. Colleges may need to adjust recruiting efforts if their research shows

that the NPC has not increased accessibility for all students. Results indicating which

students are using the NPC may also be beneficial for conversations about public policy

and the effectiveness of federal regulations.

Purpose of the Study

The purpose of this mixed methods study is to investigate the use of the NPC and

to identify characteristics of potential applicants that predict the likelihood of NPC users

applying to and enrolling in a small, high-cost, private university in the Midwest

compared to non-NPC users. This study seeks to understand how the NPC fits into the

college choice process, as outlined by Perna (2006a). The results of this study can help

8

inform enrollment management professionals who seek to use the NPC as a positive

recruitment tool.

Research Questions and Hypotheses

Quantitative Research Questions and Hypotheses

Three main research questions drive the quantitative portion of this study. The

following are the quantitative research questions and the hypotheses for each question.

I. Will the percentage of potential applicants to All-American University

who self-identify while using the NPC and subsequently (a) apply to the

University and (b) enroll be significantly different than the percentage of

potential applicants who do not use the NPC and (a) apply and (b) enroll?

Hypothesis: The percentage of potential applicants to All-American

University who self-identify while using the NPC and subsequently (a)

apply to the University and (b) enroll will be significantly lower than

the percentage of potential applicants who do not use the NPC and (a)

apply to the University and (b) enroll.

II. Will the percentage of potential applicants to All-American University

who self-identify while using the NPC in their initial contact with the

University and subsequently (a) apply to the University and (b) enroll be

significantly different than the percentage of potential applicants who self-

identify while using the NPC later on during the inquiry process and

subsequently (a) apply to the University and (b) enroll?

Hypothesis: The percentage of potential applicants to All-American

University who self-identify while using the NPC in their initial

9

contact with the University and subsequently (a) apply to the

University and (b) enroll will be significantly lower than the

percentage of potential applicants who self-identify while using the

NPC later on during the inquiry process and subsequently (a) apply to

the University and (b) enroll.

III. Will high school GPA, ACT/SAT scores, use of the NPC, level of

financial aid estimated, parent income, number of children in the

household, state of residence, and parent marital status listed in the NPC

by self-identified users significantly predict an applicant’s likelihood to (a)

apply and (b) enroll at All-American University?

Hypothesis: A combination of student characteristics consisting of

high school GPA, ACT/SAT scores, use of the NPC, level of financial

aid estimated, parent income, number of children in the household,

state of residence, and parent marital status will significantly predict

an applicant’s likelihood to apply to All-American University.

Qualitative Research Questions

Five qualitative research questions guide the qualitative portion of this study. The

following are the qualitative research questions.

I. What are the perceptions of potential applicants regarding use of All-

American University’s NPC?

II. What perceptions do potential applicants to All-American University

report regarding the results of the NPC?

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III. What prompted potential applicants to All-American University to use the

NPC at the time they did?

IV. To what extent do potential applicants to All-American University report

that the use of the NPC influenced their decision to apply to the

University?

V. Were there other factors or individuals beyond the NPC that influenced

potential applicants to apply to All-American University?

Justification for a Mixed Methods Approach to the Study

The researcher uses a mixed methods approach to the study. The main research

questions are answered using a quantitative data analysis. This analysis seeks to

determine the relationship between characteristics of individuals and their families who

use and those who do not use the NPC and whether or not they apply and enroll at a high-

cost, small, private university in the Midwest. While quantitative data address the

relationship between specific student and family characteristics and decisions regarding

application and enrollment, these data cannot explain the process a student goes through

when making a college choice decision. Qualitative data collection and analysis are

needed to understand a student’s thought process.

The qualitative portion of this research seeks to understand the student’s analysis

of cost versus benefit as well as the perceived effect of other layers of influence as

defined in the college choice model developed by Perna (2006a). In this phase of the

research study, students are interviewed. Analysis of the interviews produces themes

surrounding student college choice and explores the role of the NPC as this relates to a

student’s decision to (a) apply to and (b) enroll at All-American University.

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Organization of the Study

This study is organized into five chapters. Chapter one introduces the problem

that is researched and the reason for the research. This chapter also identifies the

conceptual framework and the research questions and hypotheses that guide this research.

Chapter two, the literature review, begins with the history of federal government

initiatives in higher education as well as the history of college choice models. Current

college choice models are discussed, including the model of college choice developed by

Perna (2006a) that guides this research. The second half of chapter two reviews existing

research on student college choice and what is known about the influence of student

characteristics, family characteristics, and cost on college choice. This chapter also

addresses what is known from the limited research that exists on the NPC.

Chapter three, methodology, contains a description of how this study was

conducted by the researcher. The setting, participant sample, and design of the study are

all discussed in this chapter. Also included in this chapter are descriptions of the methods

of data collection and analysis employed in the study.

Chapter four provides a presentation of the data and includes the results of the

data analysis from both the quantitative and qualitative data collection phases.

Chapter five provides a summary as well as conclusions and recommendations. It

contains the findings from the research and the interpretation of the research results.

Also, the limitations of the study are discussed.

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CHAPTER TWO

REVIEW OF THE LITERATURE

In order to investigate students’ use of the NPC, it is important to first review the

background of federal government involvement in higher education. This involvement

led to regulations for the NPC and other efforts to clarify the cost of college during the

college selection process. This chapter begins by reviewing the history of federal

involvement and providing a summary of current regulations.

Next, this chapter explores early and contemporary college choice models that

have added to current understanding of student college decisions. These models include

important characteristics and variables that influence how students make their decisions.

Awareness of these models is important to developing an understanding of the role that

the NPC plays in college choice.

Finally, this chapter concludes with a review of the existing research that focuses

on college choice variables. Many factors influence the college choice decision

including: academics, race, parents and family, gender, cost, and financial aid. This final

section of the chapter explores what is already known about the relationship between

these factors and college choice and also reviews the small amount of existing research

on the NPC.

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History of Federal Government Involvement in Higher Education

Although the state governments have “primary responsibility” for all types of

education, the federal government has been involved in higher education for many years

(Mumper, Gladieux, King, & Corrigan, 2011, p. 114). While early federal government

involvement in higher education dates back to the mid-1800s, with the Morrill Land

Grant Act of 1862, the Higher Education Act of 1965 (HEA) began a new age of federal

regulation in higher education (Mumper et al., 2011).

HEA solidified the federal government’s role in offering financial aid to all

citizens. It expanded financial aid benefits beyond initiatives such as the post-World War

II G.I. Bill of 1944 for servicemen to all citizens and was the beginning of accessibility

for financial aid (Weeks & Gilkes, 2014). HEA was part of President Johnson’s Great

Society program and “part of a larger plan to use education to fight poverty” (Parsons,

1997, p. 37). Anyone wanting to attend college could now apply for benefits. HEA

created three types of financial aid programs that included a need-based grant, a student

loan program, and it packaged two existing aid programs with a new grant opportunity to

develop a program known as campus-based funds.

HEA also ushered in a new era of regulation for colleges and universities (Weeks

& Gilkes, 2014). Because colleges were now receiving federal funding, they became

subject to requirements for accreditation and reporting about operations (Fuller, 2014).

The federal government sought to ensure that funds were used appropriately and

produced the results intended by the legislation. In addition, the initial grant funding in

HEA went directly to colleges for dispersal and campus-based funds required an

14

institutional match (Mumper et al., 2011). The government wanted to monitor the

process to ensure funding was awarded and disbursed as intended.

HEA was established with a requirement for regular reauthorization by Congress.

At first, it was reauthorized every two years, but later required reauthorization every four

years. So far, reauthorization has occurred in the years 1968, 1971, 1972, 1976, 1980,

1986, 1992, 1998, and 2008 (Fuller, 2014). Each reauthorization brought changes to the

aid programs and new or different requirements for colleges. The 1972 reauthorization of

HEA made changes to the federal grant portion of funding, later to be known as the Pell

grant. Although colleges wished to retain control for dispersal of the grant funds,

Congress felt differently and adjusted the program so that federal grants were now

awarded directly to students (Parsons, 1997). This change gave students the freedom of

choice and the ability to decide which college they would attend with their federal grant

funding.

Other federal initiatives brought changes to student aid and the regulations for

colleges. Initiatives such as the Middle Income Student Assistance Act (MISAA), in

1978, sought to expand financial aid access so that more students could use federal loans

(Parsons, 1997). MISAA also expanded Pell grant access and increased funding levels in

other federal aid programs (Parsons, 1997).

Later on in the 1990s, more changes came to federal financial aid with further

expansion of loan eligibility with the unsubsidized student loan. Now any student,

regardless of income, could borrow from the federal government (Mumper et al., 2011).

The 1980s and 1990s also brought more requirements for institutions. Throughout these

two decades there was an increase in requirements for colleges to report data about

15

operations (Zumeta, 2001). The administration under President Clinton “took an early

and hard line on the accountability of postsecondary institutions participating in the

federal student aid programs” (Gladieux & King, 1995, p. 23). The legislation enacted

also required more “gatekeeping” by the federal Department of Education (ED)

(Gladieux & King, 1995, p. 23). All of this led to the 2000s, when the federal

government began focusing even more on college transparency, accountability, and

accessibility.

Recent Initiatives of the Federal Government

Spellings Commission. In 2005, the U.S. Department of Education Secretary

Margaret Spellings formed a Commission on the Future of Higher Education. Spellings

stated that the purpose of the commission was to “examine how we can get the most out

of our national investment in higher education” (Ruben et al., 2008, p. 1). The

commission was comprised of 19 members from a variety of backgrounds in education,

government, and business. For a year, the commission “undertook an extensive review of

documents from approximately 175 organizations, agencies, and institutions” (Ruben et

al., 2008, p. 4). The end result was a published report titled, A Test of Leadership:

Charting the Future of U.S. Higher Education (U.S. Department of Education, 2006).

Several of the six main recommendations directly referenced the need for new levels of

transparency and accountability from colleges.

Within these recommendations, the commission proposed numerous changes such

as the creation of consumer databases to provide information about “institutional

performance and aggregate students outcomes,” public reports on “colleges’ revenues

and expenditures,” incentives to colleges that increase access and productivity while

16

cutting costs, and measurement of student learning (U.S. Department of Education, 2006,

p. 21). While making these recommendations, the commission also asked federal and

state policymakers to “relieve the regulatory burden on colleges and universities” and

encouraged “a review of the hundreds of regulations” required of colleges (U.S.

Department of Education, 2006, p. 20).

Overall, the work of the commission promoted the idea that more transparency

and accountability was needed to sustain higher education in the future. Fewer than two

years after the Spellings Commission published its report, the reauthorization of HEA

was passed and brought to fruition many of the recommendations proposed by the

Commission.

Higher Education Opportunity Act of 2008. The Higher Education

Opportunity Act of 2008 (HEOA) “brought more than 150 new rules, regulations, and

requirements” and “more than doubled institutional reporting, disclosure, and provision

of information requirements” (Weeks & Gilkes, 2014, p. 3). The HEOA also required

ED to “report the top five percent of institutions with the highest tuition and fees and the

highest net cost and required institutions with the highest increase in costs to report on

how their leaders plan to cut costs” (Fuller, 2014, p. 58). Many of the new regulations

were associated with more college-required disclosures to consumers to increase

transparency. Some were specifically related to making college costs more transparent

and making it easier to obtain this information earlier in the admission process. The Net

Price Calculator, Financial Aid Shopping Sheet, and College Affordability and

Transparency lists all developed from HEOA regulations and recommendations.

17

Net Price Calculator (NPC). HEOA required that all institutions receiving

federal aid funds post a calculator to their websites that would allow a prospective student

to get an “average yearly price actually charged to full-time, first year undergraduate

students receiving student aid” (U.S. Department of Education, 2008, p. 32). The

purpose was to help students understand how much they would owe to an institution after

the disbursement of financial aid. HEOA also required that ED develop a net price

calculator template for institutional use and gave colleges two years, from the date that

the calculator became available, to publish a NPC on their websites (U.S. Department of

Education, 2008). The regulations allowed an institution to develop its own calculator,

but required specific pieces of information to be included such as the estimated total cost

of attendance (including tuition and fees, room and board, books and supplies, and other

expenses), estimated total grant and scholarship aid, and estimated net price (Cheng,

2012). In addition, regulations prevented colleges from requiring a student to enter

personal information, such as name and address, to use the calculator. Schools could ask,

but students did not have to answer.

Financial Aid Shopping Sheet. The regulations in HEOA also required ED to

develop a “model institution financial aid offer form” by gathering recommendations

from parents, students, guidance counselors, college representatives, and others regarding

what improvements needed to be made to financial aid offer forms, often known as

financial aid award letters (U.S. Department of Education, 2008, p. 92). HEOA required

that the model form include information about cost of attendance, gift aid awarded, loans

and work opportunities, and net price (U.S. Department of Education, 2008). The

18

regulations allowed for additional elements to be added at the discretion of the secretary

of education.

The main purpose of this regulation was to replace all college-developed award

letters with one federal template to ease the confusion and concerns of families that faced

trying to compare award letters displayed in varying ways. In 2012, the Financial Aid

Shopping Sheet was released as an answer to the HEOA regulation. Currently, the

Shopping Sheet is not mandatory for all schools. While some colleges have chosen to

adapt their award letters to the new Shopping Sheet format, others have not.

College Affordability and Transparency Center. The College Affordability

and Transparency Center (CATC) was born from HEOA requirements for consumer

information about affordability. The CATC website allows students and their families to

view College Scorecards which showcase affordability and value. It also allows families

to compare colleges on the basis of cost, academic majors, size, safety, and other aspects

through the College Navigator website and provides links to the NPCs of every

institution receiving federal financial aid. The lists of colleges by highest and lowest

prices that were mentioned previously are also located in the CATC. Here students can

find out which schools have the highest and lowest prices and which schools are

increasing costs at the highest rate.

College Choice Models

Early College Choice Models

Many researchers have studied student college choice and developed theories

about what factors are most influential in the college choice process. Early researchers

came from backgrounds in sociology, economics, and psychology and framed their

19

theories through the lens of their disciplines. Paulsen (1990) examined the characteristics

of these three discipline-based models.

Sociologists often focused on the early stage of college choice and looked at how

student aspirations and plans to attend college formed. Blau and Duncan’s (1967)

research on status attainment drove much of the research by sociologists. Status

attainment is associated with the social class of a student. The ability of students to move

upward is affected by a combination of their own efforts and the status of their parents.

Research in this area highlighted the importance of student background characteristics

such as family income, race, gender, and parent education in the formation of student

aspirations and plans for college. Sociologists also considered student academic ability

to be an important driver in college choice.

Economists who have studied student college choice focused on the investment

decision students must make. These researchers saw college choice as a cost-benefit

analysis. A student must decide if the benefit of education over his or her lifetime is

worth the investment. Like sociologists, economists also believed that family

characteristics, student background, and academic ability were important throughout the

college choice process. These characteristics interact with environmental and

institutional factors during college choice.

Studies by psychologists regarding student college choice have found that

students often select a college having a student population they feel is most like

themselves. Psychology-based studies often focused on the importance of institutional

characteristics in the college choice process. Aspects of colleges such as cost, distance

20

from the student’s home, majors offered, and level of selectivity were all considered

important.

Contemporary College Choice Models

Contemporary models of college choice started to develop in the 1980s

(Bergerson, 2009). These models combine aspects of sociology, economics, and

psychology into complex college choice models that focus on many different factors.

Many of these models also view the college decision process in steps.

Chapman’s model of college choice. Chapman (1981) developed a college

choice model that includes two phases: college search and college choice. In this model,

student characteristics (family income, academics, and aspirations) and external

influences (friends, family, college characteristics and cost, and college communication

efforts) interact with student expectations for college to influence where students apply

and enroll. This model was the first comprehensive college choice model to be

developed and was specifically created to help admissions officers determine how to

recruit students. While Chapman’s model is still cited in current literature, other models

that include an early stage, where students develop education aspirations, have become

more popular. The period of time when students develop college aspirations is likely

“the most powerful phase of predicting college attendance” (Paulsen, 1990, p. 36).

Hossler and Gallagher’s model of college choice. The college choice model

developed by Hossler and Gallagher (1987) is one of the most widely cited in literature

about college choice (Bergerson, 2009). Hossler and Gallagher define the college

decision process by three stages: predisposition, search, and choice.

21

Students in the predisposition stage are trying to decide if they want to go to

college (Hossler & Gallagher, 1987). Their aspirations for attending college are

influenced by a variety of factors, mainly sociological and economic, such as student and

family characteristics, school activities, and influential people in the student’s life.

Typically students go through the predisposition phase between grades seven and 10

(Perna, 2006a).

The search stage of the model is the period of time when students develop a

choice set of colleges in which they are interested (Hossler & Gallagher, 1987). This

stage typically occurs between grades 10 and 12 (Perna, 2006a). During the search stage,

both students and colleges are looking for each other. Students gather information about

colleges, and colleges gather information about students. Students develop their choice

sets by looking at college characteristics such as cost, type of school, degrees offered,

size, selectivity, and the distance from their homes (Paulsen, 1990). Hossler and

Gallagher (1987) indicate that the search stage is the most important for colleges in

developing a prospective student pool. This stage is also the time when the NPC

becomes most important because students may use the NPC and eliminate the college if

cost is perceived as a barrier.

The final stage of Hossler and Gallagher’s (1987) model is choice. The choice

stage occurs at the end of high school, in grades 11 and 12 (Perna, 2006a). During this

stage, students evaluate their college choice set and decide which college they want to

attend. Students’ decisions are influenced by what the colleges in their choice sets do to

encourage enrollment. Hossler and Gallagher suggest that activities not related to

financial aid may be more important than the aid award.

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Pitre, Johnson, and Pitre’s model of college choice. Pitre, Johnson, and Pitre

(2006) proposed a college choice model where the predisposition phase of college choice

includes “behavioral intentions” as an additional influence beyond economic and

sociological factors (p. 37). This model operates on the “Theory of Reasoned Action,”

where “behavioral intentions” are decided by students’ attitudes about the behavior and

by subjective norms (Pitre et al., 2006, p. 37). Subjective norms are what students

believe others expect from them. Pitre et al. maintain that a student’s college decision

will be influenced based on the student’s views about going to college and what the

student believes others will expect.

Perna’s model of college choice. Another recent college choice model is one

developed by Perna (2006a). Perna’s model incorporates the economic human capital

model and sociological concepts in the college decision process. In this model, students’

college decisions reflect the context of their specific situations. There are multiple routes

in choosing a college, not one path. The human capital concept is the key to this model

because students develop a cost/benefit analysis that is also influenced by student

academic abilities and family resources

Perna (2006a) emphasizes the “economic model of human capital investment” (p.

106) that maintains students evaluate the cost and benefits of going to college. This

evaluation includes monetary and non-monetary benefits associated with college choice.

Students who have more resources, or higher academic abilities, are more likely to invest.

This theory assumes that students make their decisions based on the information they do

have, which may or may not be complete. While this theory helps to explain college

choice behavior, it does not explain all differences in college choice based on family

23

characteristics. The “sociological model of status attainment” adds to understanding of

college choice (Perna, 2006a, p. 105).

The “sociological model of status attainment” looks at how student background

characteristics, mainly socioeconomic status, influence college choice (Perna, 2006a, p.

105). The model states that student educational aspirations are affected by a student’s

academic preparation and ability as well as family socioeconomic status. Students who

are more prepared and have higher academic abilities get more support and

encouragement from influential people in their lives and have higher aspirations.

The college choice model proposed by Perna (2006a) incorporates both the

economic and sociological models because college decisions “reflect an individual’s

‘situated context’” (p. 116). Perna maintains that there are multiple paths students could

take in the college decision process, and the path is influenced by many factors. Perna’s

model also emphasizes the importance of habitus. Habitus is “an individual’s

internalized system of thoughts, beliefs, and perceptions that are acquired from the

immediate environment” (Perna, 2006a, p. 113). These thoughts and beliefs help develop

a student’s expectations, aspirations, and ideas about college.

At the center of Perna’s (2006a) model, is the human capital comparison of

expected costs and expected benefits. Expected costs include the cost of attendance and

“foregone earnings” while expected benefits can be monetary or non-monetary (Perna,

2006a, p. 116). These costs and benefits are influenced by a student’s academic abilities

and family resources.

Further influencing the cost and benefit calculation, related to college decision,

are “four contextual layers” (Perna, 2006a, p. 116). The first layer is the individual’s

24

habitus. The habitus reflects individual characteristics such as race and gender and also

emphasizes the importance of cultural capital and social capital. Cultural capital

describes attributes that define a student’s social class such as language skills and

mannerisms while social capital refers to the student’s relationships and networks with

others.

The second layer is “school and community context” (Perna, 2006a, p. 117). In

this layer, relationships with teachers, counselors, and peers can affect student college

choice. The presence, or absence, of resources relationally provided by those in the

student’s school influences the college decision process.

The third layer is the “higher education context” (Perna, 2006a, p. 118).

Institutions of higher education can impact college choice based on the materials sent and

the education about college options provided. Higher education is also influential

because of specific school characteristics and admissions issues such as the total number

of students that can be accepted and the selectivity of the institution. Students might alter

their college choice sets if they know an institution can only accept a limited number of

students.

The final and fourth layer of Perna’s (2006a) college choice model is the “social,

economic, & policy context” layer (p. 119). Perna recognizes that outside influences

such as the economy and public policies can influence college decision. The national

financial aid system also plays a role with its complexities (Perna, 2006b).

All of these layers interact with cost benefits, cost comparisons, academics and

resources to influence a student’s college decision process. Perna’s (2006a) model helps

to explain differences in college choice that occur across groups of students, including

25

minorities. Students with differences in economic and sociological factors may act

differently during the college choice process. In addition, Perna’s model recognizes that

a cost and benefit analysis is central to a student’s college choice, but also acknowledges

that other factors can impact that analysis. Perna’s model distinguishes the intricacies

and complexities of college choice.

This study used Perna’s (2006a) model as a guide to investigate the role of the

NPC in college choice. The layers of the model will influence the selection of variables

and development of interview questions.

Factors That Influence College Choice

Many researchers (Ceja, 2006; DesJardins et al., 2006; Hearn, 1991; Hossler,

Schmit, & Vesper, 1999; Perna & Steele, 2011; Pitre, 2006; St. John, Paulsen, & Carter,

2005) have explored the relationship of characteristics identified in college choice models

to the college choice process. Research shows that these characteristics do influence

college choice in different ways, both individually and in combination. This section

explores the relationship between college choice and the individual characteristics of

academics, race and ethnicity, parent education, parent wealth, parent influence, distance

from home, gender, costs, and financial aid.

Academic Success

Research regarding the level of student academic success and its impact on

college choice and enrollment indicates that students who are more successful

academically have more opportunities and options than students of lesser academic

ability. Several studies have highlighted these benefits. Research has found that grades

predict not only the kinds of college aspirations that students have, but also college

26

attendance (Hossler et al., 1999; Hossler & Stage, 1992). Students who receive grades of

A and B in high school were more likely to attend a four-year college (Hossler et al.,

1999).

Students with good grades and test scores were also more likely to attend an

institution classified as higher spending per student (Hearn, 1988, 1991). SAT scores

have even been shown to predict the number of college applications a student submits.

Students with higher SAT scores are more likely to submit a larger number of college

applications (Hurtado, Kurotsuchi, Briggs, & Rhee, 1996). In addition, students with

lower test scores may choose not to apply to schools they were once interested in.

Research conducted by DesJardins et al. (2006) found that at one public research

institution, the average ACT score of applicants to the college was higher than the

average ACT score of students who sent their test score reports to the institution. This

indicates that students with lower scores did not continue on to the application phase.

Additional research has focused on the selectivity of the institution a student

attends and how that corresponds to academics. Hearn (1991) performed research using

surveys of high school seniors in America and found that students who were stronger

academically were more likely to attend a selective college. In this study, Hearn defined

selectivity by looking at average SAT scores for all students at the college. Later though,

Karen (2002) replicated the study performed by Hearn (1991) using updated survey data

and discovered that academics did not predict the selectivity of the college attended. The

goal of this updated study was to determine if anything had changed regarding student

college destinations. The contradiction of these later results indicates that more research

is needed to determine if academics do relate to the selectivity of the college attended.

27

Race and Ethnicity

The literature regarding student characteristics and their relation to college choice

frequently addresses the impact of race and ethnicity. Many studies have been performed

regarding this topic and overall these have found that race and ethnicity are predictors of

the likelihood a student will go to college and what kind of college he or she will choose.

The research agrees that Asian and White students have different experiences in college

choice than do African American, Hispanic/Latino, and other ethnicities. Hurtado et al.

(1996) found that Asian American and White students were more likely to follow the

college choice models discussed previously in this chapter. Hispanic students were the

least likely to fit the models.

Early research indicates that African American and Hispanic students have a

disadvantage in parent wealth that influences college choice (Hearn, 1988). Parent

wealth and its relation to college choice are discussed later in this chapter, but it is

important to note here its impact for minority students. In relation to parent wealth,

Hearn (1988) also found that Hispanic students are more likely to attend a lower cost

college. When financial aid is offered, that can change. Research conducted by Confer

& Mamiseishvili (2012) reviewed the college choice process of minority students who

enrolled at Christian colleges and found that students with parent incomes of less than

$30,000 were actually more likely to enroll because grants and scholarships were

positively related to the choice of the college. In their study regarding ACT score senders

at a public institution, DesJardins et al. (2006) found that because African American and

Latino students had a higher probability of receiving financial aid and on average

28

received more aid than White students, they were more likely to apply for admission than

White students of comparable ability.

Other financial factors also influence enrollment. Research has shown that the

parents of first-generation Native American and Hispanic students often encourage their

children to attend college close to home so they can save money (MacAllum, Glover,

Queen, & Riggs, 2007). Minority students do consider the college’s distance from their

home when choosing where to enroll. In the study of students at Christian colleges,

researchers found that minority students were more likely to enroll at the institution if it

was fewer than 50 miles from their home (Confer & Mamiseishvili, 2012). Biswas,

Perkins, & Izard (2012) also found that distance from home was important for minority

students.

Research regarding minority students has also focused on the type of institution

these students are more likely to attend. Several studies have found that African

American students were more likely to attend an institution that is less selective (Hearn,

1984, 1991; Karen, 2002). Selectivity of an institution is determined by the academic

abilities of the institution’s student population and is often calculated using average test

scores such as ACT or SAT. African American students were also more likely to attend

institutions that are classified as higher-spending (Hearn, 1988; Hearn, 1991). Hispanic

students were also slightly more likely to choose a higher-spending institution (Hearn,

1984). Higher-spending is classified by determining institution expenditures on a per

student basis. This college choice trend of African American and Hispanic students may

relate to the institution’s ability to offer scholarships and grants.

29

Looking beyond financial factors, many studies have focused on the academic

abilities and aspirations of minority students and how those translate to college choice

and enrollment. Pitre (2006) compared the college aspirations of ninth grade African

American and White students and found that both groups of students aspired to go to

college. Even though African American students aspired to go to college, the research

indicated that they may lack information about college in general and the criteria colleges

consider for admittance. This same study also found, for both groups of students, that

student aspiration for college was tied to beliefs about how well their high school had

prepared them for college.

In a study using longitudinal data to look at college application behaviors,

Hurtado et al. (1996) found that Asian Americans had the highest aspirations for a

college degree. In the research, 74% of Asian Americans reported it was likely they

would attend a four-year college. This compares to 62% of White students, 60% of

African American students, and 53% of Hispanic students. Asian American students also

anticipated applying to a larger number of colleges than other students.

Other studies have found similar differences in the expectations and actions of

Asian American students compared to other minorities. Kim (2012) found that of all

ethnicities, Asian students were the most likely to go to college. Asian American

students were also more likely to have taken or plan on taking standardized tests such as

the SAT (Hurtado et al., 1996). African American students do not follow the same

trends. From 1992 to 2000, the period reviewed in Kim’s study, African American

students were the least likely to enroll in college. Other research reviewing survey data

30

from 1972 to 1992 found a decrease in the likelihood that African American students

would apply to college (Turley, Santos & Ceja, 2007).

Academic ability also plays a role in college choice and aspiration. Research has

shown that higher academic minority students were more likely to travel further from

home for college than students of lower academic ability (MacAllum et al., 2007).

However, even higher academic minority students were at a disadvantage compared to

White students. Filter (2010) studied factors that influenced student enrollment at their

first-choice college for high schools students having an A average and found that

minority students were less likely to enroll at their first-choice college than White

students. This likely relates to factors previously discussed such as family wealth and the

tendencies of specific minorities.

An understanding of college characteristics that influence minority student

college choice is also helpful for this research. Biswas et al. (2012) performed a web

survey with students at 17 institutions and found several college factors that minority

students found were of higher importance than other students in the study. Those factors

included college aspects such as the number of minority faculty, presence of a

multicultural curriculum, diversity of the student body, and the college’s reputation for

diversity. The importance of minority faculty differed between students who chose a

public college and those who chose a private institution, with students at private colleges

rating the presence of minority faculty higher than public college students.

Parents and Family

In many ways, family impacts student aspirations and decisions regarding college.

College choice research consistently cites family characteristics, parent education, family

31

wealth, and family makeup as influential factors on college choice (Cabrera & La Nasa,

2001; Conley, 2001; Hearn, 1991; Hossler et al., 1999; Hossler & Stage, 1992; Hurtado

et al., 1996; Turley et al., 2007). Research also shows parent expectations and

encouragement regarding college for their children was influential in whether they attend

college and what kind of college they attend (Ceja, 2006; Hossler et al., 1999; Myers &

Myers, 2012; Smith & Fleming, 2006).

Family characteristics. Several studies have focused on the role family makeup

plays in college choice. Siblings have an impact in different ways. Hearn (1984) found

that students with more siblings were somewhat less likely to attend institutions that are

highly selective or high spending. Students with more siblings were also more likely to

have more problems academically than students with fewer siblings (Conley, 2001).

However, the presence of siblings is not always a negative factor. Research regarding

underserved and minority populations has found that having older siblings was a benefit

for students going to college (Ceja, 2006; MacAllum et al., 2007). Parents who may not

otherwise know about the process of going to college gain experience with older children

and the college process, making it easier for the siblings who follow. Research also has

shown that students of older parents tended to be more academically successful than

students of younger parents (Conley, 2001).

A small amount of research exists on the benefit of having two biological parents

in the household during a student’s high school years. Lillard and Gerner (1999) used

data from a longitudinal survey of high school sophomores and seniors, with additional

follow up surveys, to investigate the relationship between the number of parents in the

household and college application and attendance by their children. This research found

32

that students who lived with two biological parents while in high school were more likely

to apply to college and those who applied were more likely to be admitted. These

students were also more likely to attend a four-year college and a more selective college

than students who did not live with both biological parents. These tendencies are likely

to occur because of the negative effects family disruption can have on students. Lillard &

Gerner cited effects such as poor school performance, less participation in extracurricular

activities, and lower family income, which occur either as a result of family disruption or

cause the disruption, as negatively affecting college choice.

Parent education. Research has shown the education level of parents to be

related to the decisions their children make regarding college. Hearn (1988) found that

both father and mother education was more significant in college choice than family

income and size. Parent education level was positively connected to the level of

education that their children attain (Conley, 2001). Parent education level also predicted

the likelihood of a student going to college, including student aspirations for college and

the end result of student college attendance (Hossler et al., 1999). Turley et al. (2007)

found that students whose parents were college graduates were more likely to apply to a

four-year college and Hurtado et al. (1996) found that for White students, the number of

applications submitted to colleges was significantly related to parent education.

Level of parent education also influences the type of institution a student attends.

Parental education level was positively associated with the selectivity of the college their

children attend (Hearn, 1984, 1991; Pascarella, Pierson, Wolniak, & Terenzini, 2004;

Turley et al., 2007). Similarly, Avery & Hoxby (2003) found that students whose parents

attended more selective colleges were more attracted by college selectivity and were less

33

deterred by costs and financial aid; research by Hurwitz (2012) demonstrated that

students were more likely to apply to a school that a parent attended. Related to cost,

Hurtado et al. (1996) found that a mother’s education was positively related to choosing a

high-cost college for White students, but for African Americans, this relationship was

negative.

Parent wealth. Related to parent education is parent wealth. The wealth, or

socioeconomic status (SES) of a family, is often a predictor of college choice and

enrollment. Students from families with a higher SES typically have more options and

freedom in choosing a college. A number of research studies have demonstrated this

finding.

Early research has shown that students from lower SES backgrounds were more

likely to select a lower-cost college (Hearn, 1984, 1988). These students were also more

likely to select colleges with lower selectivity and lower per student spending (Hearn,

1984, 1991). Later research echoes these findings. Lillis & Tian (2008) found that

students from families with more wealth were more likely to consider a higher-cost

college and less likely to consider a lower-cost college. In addition, Hurtado et al. (1996)

found that the number of college applications students submitted was related to family

wealth. Students with higher family wealth were more likely to submit more applications

to colleges, but lower SES students applied to a few schools or none at all during high

school (Hurtado et al., 1996).

College application translates to college enrollment. Kim (2012) found that

specific income levels predicted college enrollment, with students from families earning

more than $75,000 a year being more likely to enroll in college than students from lower

34

income bands. Students from families with incomes of less than $25,000 a year were

least likely to go to college after high school (Kim, 2012). Perna and Titus (2004) found

similar results when they looked at the impact of SES on college enrollment. Family SES

did predict college enrollment, with low SES students being the least likely to enroll in

college directly following high school. When students from low SES families did enroll

in college, they were more likely than higher SES groups to enroll at an in-state, two-year

public university rather than a four-year public or out-of-state institution (Perna & Titus,

2004). Conley (2001) found that parent income also predicted the number of years of

schooling, both high school and beyond, which a student received and also predicted the

likelihood of a student graduating from college.

Some studies have sought to determine how the relationship between parent

income and college enrollment has changed in the last few decades. One study compared

student data from 1979 and 1997 and found that family resources were less influential on

college enrollment now than they were in earlier years (Reynolds & Pemberton, 2001).

Findings by Turley et al. (2007) indicated that the effect of parent income on college

attendance had not changed from 1972 to 1982 to 1992. The 1997 study conducted by

Reynolds & Pemberton (2001) used a second set of student data that was five years

newer than the data Turley et al. used. This could indicate that the role of wealth is

decreasing, but further research is needed.

Other research highlights the role parent income still plays in college choice. A

qualitative study by Bloom (2007) examined high school seniors attending urban high

schools. Two of the three high schools where data were collected had students enrolled

who were largely minority and came from families that qualified for the school’s free

35

lunch program. Bloom found the consistent themes of money as an issue in the

consideration of college. Many of the students in the study indicated a daily struggle to

financially survive and could not comprehend how to pay for the cost of college.

Students from the high school with higher family wealth, voiced less concern regarding

the cost of college.

A few student factors are not as influenced by parent wealth. Hossler & Stage

(1992) found that parent expectation and student aspiration were not significantly related

to family income. Hossler et al. (1999) also demonstrated that family income did not

influence student aspirations for the ninth grade students studied, but it is important to

note that, later on, family income did affect the type of college where the student actually

enrolled. In addition, students with high academic abilities were less likely to be

influenced by parent wealth in college choice (Hearn, 1988).

Cabrera and La Nasa (2001) examined parent guidance and SES to understand the

relationship to college choice. In this study, SES was defined by parent education and

occupation, family income, and the type of items in the home. Cabrera and La Nasa

found that only 23% of parents from the lowest SES group had first-hand college

experience that they could draw upon to help guide their students. This translated into a

low percentage of these students having applied to a four-year college by their senior

year. In contrast, over 99% of parents from the highest SES group had first-hand college

experience, and their students were about three times more likely to have applied to a

four-year school by senior year. Lower SES students were also less likely to have

siblings who had finished high school and were classified as being college ready

themselves.

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A study undertaken by Lovenheim and Reynolds (2013) reported parent wealth in

a different way by studying the family home value and how it relates to college choice

and attendance. The research found that home value predicted what type of college

students attended. A relationship was found to exist between the increases in home

prices during the four years before a student turned 18 years old and the student’s

decision to attend a more prestigious college. For every $10,000 increase in home value,

the more likely it was that a student would attend a major public university and less likely

to attend a community college. Important for this study was the finding that an increase

in home value was not related to the likelihood of applying to private colleges.

Parent influence. In addition to parent education and parent wealth, parent

expectations and encouragement have been shown to play a role in student college

choice. Through interviews and focus group research, Dale (2010) found that parents

were the most influential people in student college choice. The more encouragement

parents offered, the more likely their student was to attend college. Hossler et al. (1999)

found a relationship between parental encouragement and college attendance. For those

students who had strong encouragement from a parent to attend college, 75% attended

some type of postsecondary institution (Hossler et al., 1999). In addition, parent

influence was found to be more important early in a student’s high school career rather

than later. Myers and Myers (2012) investigated the relationship between the degree of

communication between parents and their student’s college choice. They found that

when both parents and students were prepared for college and had greater aspirations,

more communication occurred. The researchers also found that parents who were more

involved in their student’s schooling were more likely to have a discussion about college

37

attendance with their student. Cabrera and La Nasa (2001) found that college readiness

was tied to parent involvement. The more parents were involved and discussed topics

with their students such as grades, school activities, taking standardized tests, and going

to college, the more likely a student would be college ready.

Student value of parental influence is also important in college choice. Filter

(2010) performed research to determine if students who performed well academically and

valued parental influence would enroll at the top college of their choice. The research

revealed that the more a student valued parental influence, the more likely they were to

enroll at their top-choice college.

It is important to note that the level of parent encouragement and influence varies

by ethnicity. Hossler and Stage (1992) studied parent influence and expectation and

found that parents of minority students generally had higher expectations for education

than non-minority parents, even though minority students had lower GPAs.

In a qualitative study of the involvement of African American parents in the

college choice process, Smith and Fleming (2006) found that the gender of their child

influenced parent expectations. African American parents were more likely to expect

their daughters to go straight to a four-year college from high school, but were willing to

consider more types of postsecondary enrollment for their sons. In addition, African

American parents were more likely to be involved in planning for high school and college

with their daughters. Expectations regarding living arrangements during college were

also different. Smith and Fleming found that African American parents were more

willing to let their daughters live on campus and more likely to encourage their sons to

live close to home because of concerns about their sons getting into trouble. The

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researchers also found that once the parent and student agreed on postsecondary goals,

gender did not make a difference in level of parent support. African American parents

supported sons and daughters at the same level.

Ceja (2006) performed a qualitative research study to understand how parents of

Chicana high school students influence college choice and found that the parents had a

minimal understanding of the college choice process. These parents wanted their

daughters to get an education, but were unable to help navigate the process of choosing a

college. Many of these parents could only help by providing financial and emotional

support. Ceja also found that some parents of Chicana students did not have enough

English language skills to help with college choice, but Chicana students having older

siblings often found the process easier because their parents had been exposed to the

process of choosing a college.

Beyond ethnicity, parent education and socioeconomic status also impact

influence and expectations. Hossler and Stage (1992) found that parent level of

education was directly related to parental expectations about college. MacAllum et al.

(2007) used focus groups to learn more about the college choice process of students who

were first generation or were from low-income families and found that their parents

encouraged them to get an education, but were minimally involved in the college search

process because of limited knowledge.

Distance From Home

Some research points to distance from home as an influential factor in student

college choice. Mattern & Wyatt (2009) used data from the National Student

Clearinghouse merged with data from the College Board to understand how distance

39

from home relates to college choice. The researchers found that 72% of students chose to

attend a college in their home state and the median distance traveled to college from

home was 94 miles (Mattern & Wyatt, 2009). A few student populations were likely to

travel farther for college. Those populations included students with higher test scores and

higher high school GPAs and students whose parents had a higher income and more

education (Mattern & Wyatt, 2009). However, research by Filter (2010) indicated that

even for high-academic students, distance influenced enrollment at their first-choice

college. Filter found that these students were more likely to enroll at colleges closer to

home. Hurwitz (2012) also found distance between a student’s home and the college

under consideration had an impact on college decisions. Application to selective colleges

decreased as distance from home increased (Hurwitz, 2012).

In their analysis of ACT score sender data, DesJardins et al. (2006) found that

students were initially willing to consider an out-of-state public college, but many did not

enroll. The research found that 19% of the ACT scores received by the public college

were from out-of-state students, but only 8.2% of the freshman class enrolled from out of

state.

Gender

A few research studies have referenced gender differences in relation to college

choice. Mentions of gender were minimal and did not offer much information about the

role gender played in college choice. From the literature that exists, it appeared that

females were more likely to attend a less selective institution than males (Hearn, 1984;

Karen, 2002). Evidence of gender differences related to attendance at higher-spending

institutions was contradictory. Hearn (1984) found that females were slightly more likely

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than males to attend a higher-spending college, but Hearn (1991) found the opposite.

Hurtado et al. (1996) found that White females were more likely to apply to more

colleges than White males, and Hossler and Stage (1992) found that parent expectations

were higher for female students. In addition, Hossler and Stage (1992) found that female

students had higher college aspirations.

Similarly, Reynolds and Pemberton (2001) used survey data from 1979 and 1997

to study college choice and found that high school females had higher expectations for

attending college than high school males. Turley et al. (2007) found an increase in the

likelihood of females applying for college when they reviewed data from 1972, 1982, and

1992.

Cost and Financial Aid

Because the main purpose of the NPC is to provide an estimate of college cost for

a family during the college choice process, this research requires an understanding of

what the current literature says about the impact of college cost and financial aid on

college choice. This section will explore the role family cost concerns play in college

choice. Family perceptions and understanding of cost will also be explored.

Cost concerns. Family concerns about the cost of college are influential in the

college decision-making process. These concerns can influence which colleges a student

considers and, ultimately, where the student enrolls. Ikenberry and Hartle (1998) used

focus groups and surveys with adults across the country to study what the public

understands about college costs and found that, generally, the public was worried about

the cost of college. Parents rated college costs as a bigger worry than health care for their

child and the quality of public schools. Of those responding to the survey, 71% stated

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that a four-year degree was “not affordable for most Americans” (Ikenberry & Hartle,

1998, p.7). Although many indicated affordability was a worry in general, when asked

about their own personal ability to afford a college education, the respondents were

positive. Of the respondents, 70% felt they could pay for a four-year private education.

This was even consistent across income bands, education levels, and minority groups.

Ikenberry & Hartle also found that many survey respondents felt colleges could cut costs

and still provide the same academic quality. In addition, the respondents indicated a

concern that colleges were not trying to be affordable for families and were not charging

a reasonable price. Also of interest was the perception of 80% of respondents that

colleges made a profit. In general, the public lacked an understanding about why costs

increase. Faculty salaries were often blamed for college costs.

Research also showed that students will eliminate a college from consideration

because of cost, even before financial aid opportunities are known. In a national online

survey, over half of the students responding indicated that they had eliminated colleges

from consideration based on cost before financial aid was awarded (Hesel & Meade,

2012; Hesel & Williams, 2010). Only 28% of the students surveyed looked at the net

price, cost after financial aid, when deciding which colleges to consider (Hesel &

Williams, 2010).

Several research studies focused on the role of cost in college choice for

subpopulations such as high-academic students, minority students, and those from low

socioeconomic backgrounds. For high-academic students, research showed that cost was

influential. Dale (2010) found, through focus groups and interviews, that high-academic

students rated cost as very high on the list of factors that influence college choice. In

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addition, Filter (2010) found that increases in out-of-pocket costs for high-academic

students negatively affected college choice and the likelihood of them enrolling at their

top-choice institution.

Similar to students with high academic achievement, research regarding students

from low socioeconomic backgrounds revealed that cost plays a central role in their

college choice. MacAllum et al. (2007) found that low-income families rate cost and

financial aid as one of the top two most important aspects of choosing a college. Parents

rated cost and financial aid as the most important, while students rated it second behind

academic program. The researchers also found that first-generation families were very

concerned about getting cost and financial aid information during the college choice

process.

Perna and Steele (2011) performed research at 15 high schools, within five

different states, to understand more about high school student views and beliefs about

financial aid. The researchers found that at schools with higher resources (schools that

had the fewest students on free and reduced lunch, the highest percentage of White

families, and highest academic performance), families were less worried about paying for

college and were more worried about which college to select. At schools with more

middle- and low-income students, families were more concerned about paying for

college. At all 15 schools, there were families that planned to select a college based on

price and were concerned with finding a less expensive institution.

Regarding ethnicity and its role in concerns about college cost, Hurtado et al.

(1996) investigated differences between White and African American students with

regard to college choice. Hurtado et al. found that both White and African American

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students who were concerned about costs were less likely to apply to a larger number of

colleges. The research also found that generally, students who applied to a larger number

of institutions were more likely to choose a high-cost institution, but African Americans

did not follow the same trend.

One research study gave more information about when, in the college choice

process, parents and students began to use cost information. Myers and Myers (2012)

found that while the type of college and academic requirements of college were discussed

earlier, the financial aspect of attending college was not discussed until the college choice

phase. This typically occurred around the 12th grade.

Understanding of college costs. Research on what students and families know

about college costs and how they use the information during the college choice process

clearly indicated that many families did not have an accurate idea of what college really

costs. Ikenberry and Hartle (1998) found that while the public thought they had a good

understanding about college costs, many overestimated the cost of college. From surveys

and focus groups, the researchers found that the respondents overestimated the total cost

of attendance of a four-year public college by an average of 99%. Estimates for just

tuition alone for four-year public colleges were even higher, with an average

overestimation of 212%. The researchers found that the respondents also overestimated

the costs for four-year private and community colleges. Somewhat surprising was the

finding that even parents of students who were currently enrolled in college tended to

overestimate.

Perna and Steele’s (2011) research conducted at 15 high schools across five states

found that parents and students did not understand and could not accurately explain

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college costs and financial aid. Only about half of the parents and students in this

research knew that price differences existed between in-state and out-of-state schools and

between public and private colleges. Regarding financial aid, most participants knew that

it was based on merit and need, but still felt financial aid was a mystery until after college

admission.

Grodsky and Jones (2007) found that neither race, ethnicity, income, nor

education affected a parent’s ability to estimate tuition. Similar to Ikenberry and Hartle

(1998), Grodsky and Jones found that parents of all types tended to overestimate tuition

by a substantial amount, an average overestimation of 175% of actual price. The

researchers did find that disadvantaged parents were less likely to attempt to estimate

costs than more advantaged parents, and White parents were twice as likely to provide an

estimate than African American and Hispanic parents. Parent education and family

income were also predictors of the willingness of a parent to give an estimate on college

costs. The higher the parent education or family income, the more likely a parent would

estimate tuition.

Financial aid. Similar to college costs, the level of financial aid offered also

impacts college enrollment. Generally, the more financial aid offered, the more likely a

student is to attend that college. Hurwitz (2012) studied the role of financial aid and its

impact on college choice and found that for every additional $1,000 of aid offered, the

probability of a student selecting that college rose by 1.66%. This also varied by level of

parent income. For students whose parent income was $50,000 or less, an additional

$1,000 of financial aid increased the likelihood of enrollment by 3.04%; however, for

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students whose parent income was above $250,000, the likelihood of enrollment

increased by only .54% (Hurwitz, 2012).

DesJardins et al. (2006) studied ACT score report senders and found that financial

aid must be higher in order to achieve an equal likelihood of application for low-income

students compared to high-income students. DesJardins et al. also found that if a college

disappointed a student with the level of aid offered, the effect on enrollment could be

very negative. St. John, Paulsen, and Carter (2005) used survey data to understand how

financial aid affected college choice by race. The researchers found “diverse patterns of

educational choice both across and within racial groups” (St. John et al., 2005, p. 564).

Findings indicated that for African Americans, cost and financial aid were key factors in

college choice.

Financial aid plays an important role with many different types of students.

Avery and Hoxby (2003) found that financial aid was also important in the college choice

process for students who had strong SAT scores and higher family income. The

researchers found that if all else was equal, these students were more likely to choose a

college if it offered larger grants, loans, and greater opportunities for work study.

Students were less likely to choose a school if the tuition or room and board was higher.

It is interesting to note that an increase in enrollment probability correlated with an

increase in loans and work study awarded. The researchers also found that students from

medium-income families reacted a little more positively to financial aid than students

from low-income families, and that students were more likely to react more positively to

funds being labeled as a scholarship as opposed to a grant. Front-loaded awards were

also more attractive to students.

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Ikenberry and Hartle (1998) researched what the public knew about financial aid

and discovered that generally the public was not familiar with various aspects of financial

aid. The participants did not know much about where financial aid comes from or how

they can get it. Many of those surveyed did not believe that loans were financial aid,

even if the loans offered a subsidy benefit, but did see work study as financial aid.

Additionally, 59% of the families surveyed did believe that financial aid existed for

families similar to their own. This finding existed across different incomes and levels of

education.

Student Choice for a Private College

Currently, little research exists regarding why students choose to enroll at a

private college. The research that does exist, points to factors such as parent income,

parent education, student academics, as well as financial aid as key indicators of private

college enrollment. Studies that have investigated those factors are examined in this

section.

Using data from 1975, Tierney’s (1980) research regarding the consideration to

attend a private college found that students who considered a private college came from

families whose parent income and education level was above the national norm. Later

research studies agreed that parent income and education were driving forces behind

private college enrollment (Hu & Hossler, 2000; Kim, 2012). In addition, parent

expectations regarding their child’s education were connected to student likelihood to

enroll at a private college (Kim, 2012). Children having parents who expected them to

complete a bachelor’s degree or higher were more likely to enroll at a private college

(Kim, 2012).

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Student academic ability along with college aspirations and expectations were

also important in predicting private college enrollment. Studies have found that students

with higher academic achievement were more likely to enroll at private colleges, and

students wishing to pursue a bachelor’s degree also had a greater likelihood of enrollment

(Hu & Hossler, 2000; Kim, 2012; Tierney, 1980). In addition, students who attended a

private college were typically more willing to travel farther from home, including out of

the state (Kim, 2012; Tierney, 1980).

As one would expect, financial aid also impacts private college enrollment.

Tierney (1980) found that the more financial aid students received at a private college,

the more likely they were to enroll. Higher levels of state and institutional financial aid

indicated a greater likelihood for student enrollment (Kim, 2012; Perna & Titus, 2004).

This was especially true for low-income students who were more likely to enroll at a

private college when offered higher levels of financial aid (Kim, 2012: Perna & Titus,

2004).

Existing NPC Research

Very little research currently exists on the use of the NPC and its effect on the

college decision process. The research that does exist only explains more about how

many students and parents are using a NPC and what they expect from it. The Noel-

Levitz (2013) firm surveyed 5,679 college-bound high school students about their use of

the NPC and found that over 60% of the students had never used the NPC. Similarly, in

early research prior to the 2011 NPC mandate, Hesel and Williams (2010) found that

only 26% of students and/or parents had used some type of financial aid calculator. This

research was later repeated by Hesel and Meade (2012) who found that the number of

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calculator users had increased to 35% of students and 3.5% of parents. It is important to

note that both of these studies referred to any financial aid calculator and were not

specific to the government-mandated NPC.

Hesel and Williams (2010) also found that Asian students were slightly more

likely to indicate using a financial aid calculator compared to Hispanic and African

American students. Income also played a role in the use of a calculator. Families that

earned more than $100,000 were three times more likely to have used a calculator than

families who earned less than $40,000 (Hesel & Williams, 2010). Within those families,

parents were more likely to be the calculator user for the highest income group while

students were typically the calculator user for the lowest income group (Hesel &

Williams, 2010)

The Noel-Levitz (2013) firm studied student and parent expectations from using a

NPC and found that more than 70% of calculator users just expected an estimate of

financial aid. Only 28% of users expected an exact offer. In gauging reaction to use of a

NPC, Noel-Levitz found that 33% of calculator users reported that it did alter their

perception of a school, with 12% reporting the NPC did have a negative effect. My

research study seeks to expand the research related to the NPC so as to develop an

understanding of the role the NPC plays in a student’s college decision.

Summary

The college choice process is complex and is influenced by many different

factors, including the student’s environment, parents and family, and college costs.

While college choice research is plentiful, and tells us that cost in an important factor in

the choice process, very little research exists to explain how the NPC influences college

49

choice. This study explored the role of the NPC in college choice and sought to

understand student use of the NPC, including why the NPC was used and how the results

were perceived. The following chapter presents the methods, setting and participant

sample, data sources, data collection, data analysis, and limitations of this research study.

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CHAPTER THREE

METHODOLOGY

This research study employed a mixed methods research design. Creswell and

Plano Clark (2011) stated that a mixed methods design is useful when “one data source

may be insufficient” or “results need to be explained” (p. 8). In this study, quantitative

data could not explain all variations in college choice. The college choice process is a

complex decision-making process as outlined by Perna’s (2006a) model of college choice

where there are multiple paths a student may take in choosing a college. These paths are

better explained by adding a qualitative research component in which the researcher can

expand on the quantitative results through student interviews. For this reason, an

explanatory sequential design was used.

An explanatory sequential design is a fixed mixed methods design with an

independent level of interaction between the quantitative and qualitative strands of

research. Creswell and Plano Clark (2011) defined the purpose of explanatory sequential

design as using “a qualitative strand to explain initial quantitative results” (p. 82). In this

study, the quantitative strand was collected and analyzed before the qualitative data were

collected and analyzed. The quantitative strand of research had priority in this study. In

addition, there were different points at which the strands of research were mixed. This

research study employed “mixing at interpretation” (p. 66). Each strand of research was

performed and analyzed before combining results for interpretation.

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Perna’s (2006a) model of college choice framed the methodology of this study.

This model identifies several layers of influence in the college decision process,

including student and family characteristics as well as influence by external entities such

as the student’s school and community and influence by higher education institutions and

public policies. The model also maintains that central to the process is a cost and benefit

analysis by the student. The quantitative portion of this research examined the

relationships between use of the NPC and student and family characteristics such as

parent income, marital status, number of children in the household, and student academic

preparation, and whether or not the student applied to and enrolled at the university. The

qualitative research explored how the NPC was perceived as impacting the student’s cost

and benefit analysis and how external entities influenced college choice.

Setting and Participant Sample of the Study

The researcher used student inquiry and application data from All-American

University, a fictitious name for the university used in this study. The results of the study

can be generalized to other high-cost, private institutions in the Midwest because these

institutions have institutional and student characteristics similar to those of All-American

University. Table 1 compares the institutional characteristics, and Table 2 compares the

student characteristics of All-American University to other small, high-cost, private

colleges in the Midwest. Data for All-American University and the comparison

universities were obtained through the Integrated Postsecondary Education Data System

(IPEDS) Data Center of the National Center for Education Statistics (NCES). All data

were reported for the 2013–2014 academic year. The comparison universities were

limited to only private, not-for-profit, four-year colleges and universities in the

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Midwestern states. The Midwest, as defined by the U.S. Census Bureau, includes Iowa,

Illinois, Indiana, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, South

Dakota, and Wisconsin. In addition, only colleges that had tuition and fees higher than

$30,000 and overall enrollments of 1,000 to 4,999 students were included as comparison

universities. In total, 60 institutions are represented in the comparison data.

Table 1

Comparison of Institutional Characteristics

Comparison Universities

Characteristic All-American Mean Median

Full-time instructional staff on 9, 10, 11 or 12 month contract 226 152 149

Full-time non-instructional staff 312 293 263Published in-district tuition and fees 36,720 36,259 35,108% of full-time first-time undergraduates receiving any financial aid 99 96 99

% of full-time first-time undergraduates receiving Pell grants 29 27 26

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Table 2

Comparison of Undergraduate Student Characteristics

Comparison Universities

Characteristic All-American Mean Median

Total undergraduate enrollment 2,702 2,067 2,039Total men 1,396 926 886Total women 1,306 1,141 1,108Asian 35 69 53

Black or African American 91 96 84

Hispanic 43 104 84

Native Hawaiian or Other Pacific Islander 2 1 1

White 2,250 1,540 1,497

American Indian or Alaska Native 1 7 5

ACT Composite 25th percentile score 23 23 23ACT Composite 75th percentile score 29 28 28

In comparison to the mean and median of high-cost, small, private universities in

the Midwest, All-American University overall has more students and more staff

members. Although All-American is larger than the mean and median of comparison

universities, a review of ACT percentile scores show that All-American’s student

population is very similar in terms of academic capabilities. In addition, All-American’s

price for tuition and fees is comparable to the mean of comparison universities and a

similar percentage of All-American students receive financial aid compared to the

median. All-American also has a similar population of Pell grant recipients compared to

the mean and median. The data suggest that students who are enrolling at All-American

are likely similar in academic abilities and financial need when compared to students

enrolling at other high-cost, small, private universities in the Midwest.

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Data Sources

Quantitative Data

The data for the quantitative strand of research came from All-American

University’s NPC, and application and enrollment data saved in All-American

University’s student information system (SIS). The SIS collects and records all student

inquiries of interest, admission applications, financial aid applications, and enrollment

decisions. The SIS also records student enrollment and financial aid through graduation.

All-American’s NPC was published on the school website as required by federal

regulations. All-American University contracted with a third-party NPC provider and

paid the provider each year to maintain the NPC on All-American’s website. The public

could access and use the NPC at any time. The purpose of the NPC was to give a

prospective freshman an estimate of how much All-American would cost to attend for

one year. This estimated cost was displayed immediately after the student entered

specific information such as high school GPA, ACT or SAT scores, parent marital status,

size of parent household, parent income, parent assets, student income, and student

assets. All data were entered by the NPC user.

All students using All-American’s NPC were presented with an option to enter

student name, address, telephone number, and e-mail address when first entering the

NPC. All-American presented the option to enter name and contact information, but, in

compliance with federal regulations, the school could not require students to complete

this section. All-American found that just over 40% of the school’s NPC users reported

name and contact information when using the NPC. The other NPC users could not be

identified. Each week, the third-party provider sent All-American a cumulative data file

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of all information entered by NPC users. This file contained student-entered information

as well as information regarding the costs and financial aid options presented to each

NPC user.

The quantitative strand of research also used data collected in All-American

University’s SIS. These data had been collected and stored in All-American’s SIS each

year since the mid-1990s. All-American University used a web-based reporting tool to

extract data files from the SIS.

Qualitative Data

During the qualitative phase of this research study, the researcher selected

students from the NPC data file and requested interviews. It was the goal of the

researcher to find students who used the NPC and applied and enrolled at All-American

University as well as students who used the NPC and did not enroll. The researcher’s

intent was to select eight interviewees who were prospective students for admission for

the 2015–2016 academic year.

Stratified random sampling was used to select interviewees. Teddlie and Yu

(2007) indicated that stratified random sampling is used when “the researcher wants

various subgroups in the sample to also be representative” (p. 79). There were eight total

subgroups the researcher intended to represent from the population in this study. As can

be seen in Table 3, the subgroups are divided by three characteristics: application

submitted, ACT or SAT equivalent composite score, and the level of net price displayed.

Students are grouped by whether (a) an application was submitted or (b) an application

was not submitted, by ACT composite score of (a) 26 or higher or (b) 25 or lower, and by

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level of net price displayed when (a) net price is equal to or above the mean or (b) net

price is lower than the mean.

Table 3

Characteristics of Each Student to be Interviewed

Interviewee Application Submitted ACT Score Mean of Net Price

1 Yes At or above 26 At or above the mean2 Yes At or above 26 Below the mean3 Yes At or below 25 At or above the mean4 Yes At or below 25 Below the mean

5 No At or above 26 At or above the mean

6 No At or above 26 Below the mean

7 No At or below 25 At or above the mean

8 No At or below 25 Below the mean

The interviews sought to understand why students used the NPC, the positive or

negative reactions to the cost estimate provided by the NPC, and the role the NPC played

in the student’s college choice process. The researcher also sought to understand how the

NPC compared to student expectations for net price and to discover if there were other

factors, or individuals, unrelated to the NPC that influenced their decision to apply and

enroll or not apply and enroll at All-American University. The college choice model

developed by Perna (2006a) suggests that college choice can be affected by several layers

of influence beyond factors such as cost. The aim of the researcher was to learn more

about the layers of influence for the college decisions of those students interviewed. The

interviews with students were semi-structured, using open-ended questions (see

Appendix A). All interview questions were developed by the researcher to address the

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purpose of this research. Student identity was protected throughout the study by the use

of pseudonyms.

Data Collection

Quantitative Data

The quantitative data file was downloaded in August 2015 through the secure

portal hosted by the NPC provider. The data were sorted to remove information on

students graduating high school in 2016 or later. The researcher sought only to study

those students who were qualified to submit a college application and make an official

college decision. Students graduating in 2016 and beyond were not eligible to apply to

All-American University until at least August 2015 or later. In addition, information on

any transfer and current college students who had used the NPC was removed from the

NPC data file.

The data file was also sorted to remove any user records in which the students did

not list their name (self-identify). Because this study sought to connect the NPC records

with application and enrollment data, a student name was required. If random characters

were listed in the first and last name fields, those records were also removed. In addition,

all records with the names “Jane Doe” and “John Doe” were removed to ensure that only

valid entries were analyzed.

The NPC data file also included more than one record for some students if they

used the NPC more than once. Only records from the student’s first use of the NPC were

retained in the data file. The researcher believed this record most accurately represented

the student’s circumstances. Later entries often contained different test scores, GPAs, or

parent income information because the student had explored how changes in these fields

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affected the financial aid award offer. The first record of NPC use was also likely the

student’s first impression of cost for All-American University.

A data file was also downloaded in August 2015 from All-American’s SIS

through a web-based reporting tool. This file included all inquiry and admission data for

students who were eligible to enter college in the fall of the 2015–2016 academic year or

earlier. This SIS data file was merged with the NPC data file, connecting individual

student records across the two systems.

Qualitative Data

During the quantitative analysis phase, the researcher used e-mail to reach out to

student NPC users and request participation in an interview. The researcher anticipated

needing to contact many students in order to find eight students who met the sampling

criteria listed in Table 3 and were willing to participate in an interview. Students were

randomly chosen from each of the eight subgroups in the population and contacted about

participating in an interview. When requesting an interview with the student, the

researcher confirmed that the student was the NPC user. In some cases, a parent might

have used the NPC and entered the student information, which meant the student might

have been unfamiliar with the NPC process and results. Only students who were the

actual NPC user were interviewed.

The researcher scheduled an interview time with each student selected.

Interviews occurred either in person, or through phone, or a videoconferencing platform.

It was anticipated that phone or videoconferencing would be necessary for interview

participants who chose not to attend All-American University. Audio recordings were

made of each interview. Each student being interviewed was asked to sign an informed

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consent form before the interview began (see Appendix B). Students who choose not to

sign the form were not interviewed. Figure 2 shows a timeline for the qualitative data

collection and analysis.

August 2015 Collect and analyze quantitative data, begin contacting NPC

users randomly from each subgroup to find willing interviewees

September 2015 Select students to interview, schedule and complete interviews

October 2015 Transcribe and code interviews, analyze results

Figure 2. Timeline for qualitative data collection and analysis.

Data Analysis

Quantitative Data Analysis

The researcher began quantitative data analysis by comparing self-identified NPC

users to the entire NPC user population. To determine if the sample participants who

self-identified on the NPC were representative of all those potential applicants who used

the NPC, it was necessary to compare the demographics for those students who self-

identified to the whole NPC user population (see Table 4). A review of the demographics

shows that self-identified applicants did accurately represent the whole population of

NPC users. The only comparison with marked difference is the mean for expected family

contribution. This difference exists because of outliers, as evidenced by the similar

medians for the same category.

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Table 4

Comparison of Demographics for Self-Identified Users and All NPC Users.

Self-Identified Users All NPC Users

Characteristic Median Mean Median Mean

High school grade point average (GPA) 3.8 3.6 3.8 3.6ACT Composite score 26 26 27 26.4SAT Composite score 1,200 1,172 1,180 1,169Expected family contribution (EFC) 11,998 27,387 12,613 52,312

Total grants awarded 22,600 23,023 22,000 21,992

Net price presented 26,039 25,396 26,039 25,656

The combined file with NPC and SIS data was analyzed using Statistical Package

for the Social Sciences (SPSS) version 22. For analysis of quantitative research question

one, a chi-square test was used to determine if there was a significant relationship

between the use of the NPC (yes vs. no) and (a) application to (yes vs. no) and (b)

enrollment at (yes vs. no) All-American University.

A chi-square test was also used for quantitative research question two to

determine if there was a statistically significant relationship between the time in the

college choice process that the NPC was used (initial contact vs. later than initial contact)

and (a) application to (yes vs. no) and (b) enrollment at (yes vs. no) All-American

University.

Finally, data for quantitative research question three was analyzed using a

discriminant analysis to determine to what extent GPA, ACT/SAT scores, the use of the

NPC, level of financial aid estimated, parent income, number of children in the

household, state of residence, and parent marital status listed in the NPC predicted a

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student’s likelihood to (a) apply to (yes vs. no) and (b) enroll at (yes vs. no) All-

American University.

Qualitative Data Analysis

Each student interview was transcribed and coded to search for themes. The

researcher sought to find themes that addressed why the student used the NPC and how

NPC results were perceived to influence the student’s college choice process. It was

anticipated that themes would emerge regarding the importance of cost in the college

decision process and that the NPC results were either positively or negatively perceived

and influenced a student’s decision to apply to All-American University.

The researcher also sought to understand how the layers of influence in Perna’s

(2006a) college choice model interacted with NPC use to influence student college

choice. In Perna’s model, four layers of influence on college choice are identified

including student habitus, community, higher education institutions, and public policies.

The researcher looked for themes that emerged from the student interviews related to

those layers. These themes helped the researcher to understand the applicability of the

Perna model for prospective students at All-American University.

Positionality of the Researcher

The positionality of the researcher was that of an insider. The researcher has

worked at All-American University for ten years. Although the researcher was

responsible for maintaining All-American University’s NPC and was part of the

enrollment management team at All-American, the researcher remained objective

throughout the study.

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The researcher assured student participants that knowledge of whether or not they

used the NPC had no bearing on student acceptance to the university or financial aid

offered from the university. Participants were informed that all demographic data will be

kept confidential.

Limitations

This study was limited by the number of students who chose to submit name and

contact information when completing the NPC. Students who used the NPC but did not

submit name and contact information could not be matched with data from the SIS. In

addition, the researcher could not verify if the student was the NPC user. In some cases,

a parent or other family member might have completed the NPC on behalf of the student.

The researcher was only able to verify the NPC user for those students interviewed.

All academic and income information submitted on the NPC was entered by the

student user. This researcher assumed that all student-submitted data, including GPA,

ACT and SAT scores, and family income, were accurate and true. This study was also

limited by the honesty of the students who were interviewed and by whether or not they

had the knowledge to sufficiently answer the interview questions. To encourage honesty,

the researcher assured all participants that their responses were not linked to their identity

in any way. The participants were informed that if the findings of the study were

published, the identity of the participants would be concealed. Participants were also

assured that their responses would not have any effect on their application or acceptance

to All-American University. In addition, participants were assured that their interview

would have no effect on financial aid and academic records.

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CHAPTER FOUR

PRESENTATION OF THE DATA

The purpose of this study was to investigate the use of the NPC and to identify

characteristics of potential applicants that predicted the likelihood of NPC users to apply

and enroll at a small, high-cost, private university in the Midwest compared to non-NPC

users. This chapter presents the results of both the quantitative and qualitative analyses.

For the quantitative analysis, three statistical tests were performed using SPSS

version 22. To answer the first research question, a chi-square test was used to measure

the relationship between use of the NPC and application to and enrollment at All-

American University. For the second research question a chi-square test was performed

to determine the relationship between the time in the college choice process that the NPC

was used and application to and enrollment at the university. The third research question

was answered using a discriminant analysis to determine if specific student

characteristics from the NPC data file could predict a student’s likelihood to apply to and

enroll at All-American.

For the qualitative analysis, seven interviews with students were conducted to

understand why each student used the NPC, the effect of the NPC on their application

and enrollment decision, and to understand other factors that also influenced their college

decision.

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Quantitative Data Collection

The analysis of quantitative data required data files from two different sources.

The first data file was downloaded in September 2015 from a secure portal provided by

the host company of All-American’s NPC. The downloaded file included NPC user

information from the time the NPC was implemented in 2010 to the date the data file was

pulled for analysis. The data required sorting in several ways before they could be

merged into SPSS.

First, all information on students who indicated a graduation date of 2016 or later

was removed from the data file. Information on any students indicating that they were a

current college or transfer student when they completed the NPC was also removed.

When the calculator was first implemented, year of graduation was not asked of the

student. For this reason, early records without this information were not included in the

analysis. The researcher wished to ensure that only first-time freshman students were

included in the analysis.

Second, all records were removed that did not contain a name and a birthdate.

These data fields were required to match student names with the enrollment data file.

Third, records with names such as “John Doe” or a random string of characters were

removed to ensure that only valid NPC entries were included in the analysis. Finally,

duplicate entries for the same NPC user were removed. Often students used the NPC two

or three times to see how a change in income, GPA, or test score would impact the

financial aid offer given. The first instance of use, determined by the date listed in the

file, for each NPC user was retained in the file. All subsequent instances of use were

removed. After all sorting was done, 1,536 NPC user entries remained in the data file.

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A second set of data files was downloaded from All-American’s SIS using a web-

based reporting tool. This set included four data files, one for each of the last four

recruitment cycles, which included high school graduates from 2012, 2013, 2014, 2015.

These years of graduation corresponded to the years of graduation reported by students

who used the NPC. The files contained data on all inquiries, applicants, and enrolled

students for that year’s recruitment cycle. All transfer students’ information was

removed from the data files as well as that of all non-degree seeking students. If non-

degree seeking students had a separate record in a later file indicating they were now

degree seeking, the second record was included in the analysis. This happened most

frequently with high school students who took courses from All-American while

concurrently earning their high school diplomas. Finally, all SAT scores were converted

to the 2008 ACT equivalent score using the concordance table issued by ACT. In total,

133,168 admission records from four years of recruitment data were included in the final

data file.

The two data files, from the NPC and the SIS, were merged using student name

and birth date to match records. There were 472 records in the NPC file that could not be

matched to the SIS file because the student had never inquired or applied to All-

American. The student’s only contact with All-American was the NPC. These students

were included in the merged file with an indication that no record of inquiry or

application existed. The merged data file was loaded into SPSS for analysis.

Quantitative Descriptive Statistics

Descriptive statistics were run for each variable included in the SPSS file. All

student records were given an indicator (Y vs. N) for application, enrollment, and use of

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the NPC. Only students with a NPC user record had an entry for the variables: GPA,

ACT, Net Price, Household Size, Parent AGI, NPC Used before Application, NPC First

Contact, Out-of-State Residence, and Parents Together.

The study proposal initially included descriptive statistics for level of financial aid

estimated, number of children in the household, and parent marital status. Net price was

used in place of level of financial aid estimated because it reflects the amount out of

pocket that the student would pay after all grants and scholarships were applied. Because

the purpose of the NPC is to present a net price, the researcher thought it was best to use

net price in place of level of aid. Household size was used in place of number of children

in the household because the NPC file only included household size and number of

children could only have been obtained through assumptions about the demographics of

each family. Finally, an indicator regarding whether the NPC user’s parents were still

together was used in place of parent marital status. This allowed the researcher to focus

on the parental relationship that may impact a student college decision the most. Table 5

contains the descriptive statistics for the variables used in the quantitative analysis.

Table 5

Descriptive Statistics for the Continuous Variables

Variable N M SD

GPA 1,536 3.62 .42

ACT 1,404 26.05 3.80

Net Price 1,536 25,390.03 8032.28

Household Size 1,444 4.33 1.83

Parent AGI 1,536 106,309.42 153,756.44

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Parent adjusted gross income (AGI) reported on the NPC varied widely with low

and high extremes. Four students reported a parent AGI over $1,000,000 and one student

reported an AGI of -$10,000. The median parent AGI reported was $90,000.

As indicated previously, the data from the NPC were all self-entered by the

student user. Some fields in the NPC require an entry and others do not. This results in

an inconsistency in N between variables. Table 6 shows the frequencies of variables used

in the quantitative analysis.

Table 6

Frequencies for the Non-Continuous Variables

Variable Yes No Total

Applied 12,939 120,229 133,168

Enrolled 2,613 130,555 133,168

NPC User 1,536 131,632 133,168

NPC Used Before Application 421 338 759

NPC First Contact 806 730 1,536

Out-of-State Residence 471 1,025 1,496

Parents Together 1,159 359 1,518

Quantitative Data Analysis

The results of the data analysis for each of the three research questions are

presented in this section. In all cases, the large sample size used in the analysis caused

inflation of the chi-square values.

Research Question One

The first quantitative research question asked: Will the percentage of potential

applicants to All-American University who self-identify while using the NPC and

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subsequently (a) apply to the University and (b) enroll be significantly different than the

percentage of potential applicants who do not use the NPC and (a) apply and (b) enroll?

As can be seen in Table 7, the percentage of students who had applied to All-

American University but had not used the NPC is 94.1%, whereas the percentage of

students who had applied to the university and had used the NPC is only 5.9%. The

difference in percentages is significant (chi-square = 2800.75, p<.01), indicating that

students who applied to All-American are nearly 16 times more likely not to have used

the NPC than to have used the NPC.

Table 7

Crosstabulation Between Application to All-American University and Use of the NPC

NPC User

No Yes Total

Applied Count % Count % Count %

No 119,453 99.4 776 0.6 120,229 100.0

Yes 12,179 94.1 760 5.9 12,939 100.0

Total 131,632 98.8 1,536 1.2 133,168 100.0

As can be seen in Table 8, the percentage of students who enrolled at All-

American but had not used the NPC is 88.8%, whereas the percentage of students who

enrolled at the university and had used the NPC is 11.2%. The difference in percentages

is significant (chi-square = 2365.73, p<.01). This indicates that enrolled students are

nearly eight times more likely to have not have used the NPC.

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Table 8

Crosstabulation Between Enrollment at All-American University and Use of the NPC

NPC User

No Yes Total

Enrolled Count % Count % Count %

No 129,312 99.0 1,243 1.0 130,555 100.0

Yes 2,320 88.8 293 11.2 2,613 100.0

Total 131,632 98.8 1,536 1.2 133,168 100.0

Research Question Two

The second quantitative research question was: Will the percentage of potential

applicants to All-American University who self-identify while using the NPC in their

initial contact with the University and subsequently (a) apply to the University and (b)

enroll be significantly different than the percentage of potential applicants who self-

identify while using the NPC later on during the inquiry process and subsequently (a)

apply to the University and (b) enroll?

As shown in Table 9, for NPC users only, the percentage of students who had

applied to the university and who had used the NPC as their first contact with the

university is 26.4%, whereas the percentage of students who had applied to the university

and whose first contact with the university was not the NPC is 73.6%. The difference in

percentages is significant (chi-square = 30.18, p<.01), indicating that students who made

first contact with All-American other than the NPC are nearly three times more likely to

apply than those whose first contact was the NPC.

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Table 9

Crosstabulation Between Application to All-American University and Use of the NPC as a First Contact With the University

NPC First Contact

No Yes Total

Applied Count % Count % Count %

No 171 56.3 133 43.8 304 100.0

Yes 559 73.6 201 26.4 760 100.0

Total 730 68.6 334 31.4 1,064 100.0

Table 10 shows that the results are similar for enrolled students. The percentage

of students who enrolled at the university and whose first contact with the university was

the NPC is 20.1%, whereas the percentage of students who enrolled at the university and

whose first contact was not the NPC is 79.9%. The difference in percentages is

significant (chi-square = 151.82, p<.01). This indicates that NPC users who enrolled at

All-American University are nearly four times more likely to have made first contact

with the university in some other manner than the NPC.

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Table 10

Crosstabulation Between Enrollment at All-American University and Use of the NPC as a First Contact With the University

NPC First Contact

No Yes Total

Enrolled Count % Count % Count %

No 496 39.9 747 60.1 1,243 100.0

Yes 234 79.9 59 20.1 293 100.0

Total 730 47.5 809 52.5 1,536 100.0

Research Question Three

Quantitative research question three asked: Will high school GPA, ACT/SAT

scores, use of the NPC, level of financial aid estimated, parent income, number of

children in the household, state of residence, and parent marital status listed in the NPC

by self-identified users significantly predict an applicant’s likelihood to (a) apply and (b)

enroll at All-American University? As previously mentioned, level of financial aid

estimated was replaced with the variable of net price to best reflect the purpose of the

calculator. Parents together was used in place of parent marital status in order to reflect

the relationship most influential to a student’s college decision, and number of children in

the household was replaced with household size due to data available in the NPC file.

Discriminant analysis was used to determine if student GPA, ACT, net price, state

of residence, parents together, household size, and parent AGI could predict student

likelihood to apply to All-American University. The sample for this analysis consisted

only of the students who had submitted NPC information to the university. Of the

students who had submitted the NPC, 249 did not supply information for at least one of

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the predictors, thus reducing the sample size for this analysis to 1,287. The canonical

correlation was .116 (p = .015), indicating a very week positive correlation between the

predictors and the likelihood of application to the university. The value was statistically

significant (p=.015) due to the large sample size.

Table 11 shows the standardized canonical discriminant function coefficients that

indicate the importance of each variable to the discriminant function. A combination of

the discriminant function coefficients and the values of the predictor variables yields a

discriminant score for each student. The mean of the discriminant scores is .125 for

students who did not apply and -.110 for students who did apply. There are four

variables that have beta weights with absolute values greater than .20. The discriminant

scores and the means for the groups indicate that students who reported (a) having a

higher GPA, (b) being an in-state resident, (c) coming from a larger household, and (d)

having parents with a lower AGI are more likely to apply to the university, and students

who reported (a) having a lower GPA, (b) being an out-of-state resident, (c) coming from

a smaller household, and (d) having parents with a higher AGI are less likely to apply to

the university. The most discriminating variable by far is state of residence (in-state vs.

out-of-state).

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Table 11

Standardized Canonical Discriminant Function Coefficients to Predict Application to the University

Variable BetaGPA -.236ACT .184Net Price -.063Out-of-State Residence .861Parents Together .113Household Size -.365Parent AGI .315

Table 12 shows the ability of the discriminant function to correctly classify

students as either likely to apply, or not likely to apply to the university. Of the 601

students who did not apply, 230 (38.3%) are not predicted to apply, and 371 students

(61.7%) are predicted to apply. Of the 686 students who did apply, 193 (28.1%) are not

predicted to apply, and 493 (71.9%) are predicted to apply. Overall, only 56.2% of the

original grouped cases are correctly classified.

Table 12

Classification Results to Predict Application at the University

Predicted Group Membership

No Yes Total

Applied Count % Count % Count %

No 230 38.3 371 61.7 601 100.0Yes 193 28.1 493 71.9 686 100.0

Discriminant analysis was also used to determine if student GPA, ACT, net price,

state of residence, parent marital status, household size, and parent AGI could predict

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student likelihood to enroll at All-American University. The sample for this analysis

consisted only of the students who had submitted NPC information to the university. Of

the students who had submitted the NPC, 249 did not supply information for at least one

of the predictors, thus reducing the sample size for this analysis to 1,287. The canonical

correlation was .162 (p=.001), indicating a slight correlation between the predictors and

the likelihood of enrollment at the university. The value was statistically significant

(p=.001) due to the large sample size.

Table 13 shows the standardized canonical discriminant function coefficients that

indicate the importance of each variable to the discriminant function. The mean of the

discriminant scores is .098 for students who did not enroll and -.274 for students who did

enroll. For this analysis, there are two variables that have beta weights with absolute

values greater than .20. The discriminant score and the means for the groups indicate that

students who reported (a) a higher GPA and (b) being an in-state resident are more likely

to enroll at the university, and those who reported (a) a lower GPA and (b) being an out-

of-state resident are less likely to enroll at the university. Similar to the prediction of

application to the university, the most discriminating variable by far is state of residence

(in-state vs. out-of-state).

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Table 13

Standardized Canonical Discriminant Function Coefficients to Predict Enrollment at the University

Variable BetaGPA -.311ACT .048Net Price .072Out-of-State Residence .912Parents are Together -.198Household Size -.136Parent AGI .183

Table 14 shows the ability of the discriminant function to correctly classify

students as either likely to enroll or not likely to enroll at the university. Of the 1,022

students who did not enroll, 419 (41%) are predicted not to enroll, and 603 students

(59%) are predicted to enroll. Of the 265 students who did enroll, 68 (25.7%) are

predicted not to enroll, and 197 (74.3%) are predicted to enroll. Overall, only 47.9% of

the original grouped cases are correctly classified.

Table 14

Classification Results to Predict Enrollment at the University

Predicted Group Membership

No Yes Total

Enrolled Count % Count % Count %

No 419 41.0 603 59.0 1,022 100.0Yes 68 25.7 197 74.3 265 100.0

Qualitative Data Collection

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The qualitative portion of this mixed methods research sought to understand why

students used the NPC, how the NPC influenced a student’s college decision process, and

other factors beyond the NPC that were also considered by the student when making a

college decision. The main qualitative research questions of this study were:

I. What are the perceptions of potential applicants regarding use of All-

American University’s NPC?

II. What perceptions do potential applicants to All-American University

report regarding the results of the NPC?

III. What prompted potential applicants to All-American University to use the

NPC at the time they did?

IV. To what extent do potential applicants to All-American University report

that the use of the NPC influenced their decision to apply to the

University?

V. Were there other factors or individuals beyond the NPC that influenced

potential applicants to apply to All-American University?

The researcher sought to interview students who represented a range of academic

abilities and financial circumstances. Also important was representation of students who

had used the NPC and applied to All-American, and those who had used the NPC but had

not applied. Students in these two populations might have made decisions differently and

the researcher wanted to consider all viewpoints.

The researcher used stratified random sampling to select interviewees. Eight

subgroups were identified as appropriate representations of the NPC user population

based on the submission of an application for admission, student ACT score, and the net

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price presented to the student while using the NPC. All students in the NPC data file who

graduated from high school in 2015 were identified as potential interviewees and were

sorted by the eight subgroups. In total, this was 412 students. ACT scores were divided

in relation to the mean score of 26 for NPC users, and net price was divided in relation to

the mean net price of $25,762 for NPC users. Table 15 shows each of the subgroups,

characteristics, and number of potential interviewees.

Table 15

Characteristics and Size of Each Subgroup

Interviewee

Application Submitted ACT Score Net Price Number of

Students1 Yes At or above 26 At or above $25,762 59

2 Yes At or above 26 Below $25,762 37

3 Yes At or below 25 At or above $25,762 55

4 Yes At or below 25 Below $25,762 44

5 No At or above 26 At or above $25,762 55

6 No At or above 26 Below $25,762 39

7 No At or below 25 At or above $25,762 61

8 No At or below 25 Below $25,762 62

Each student was assigned a random number using a formula in Microsoft Excel.

All students were sorted within their appropriate subgroup using the random number

assigned. Students with the lowest number in each subgroup were contacted first with a

request for an interview.

Initially 40 e-mails were sent to five students from each of the eight subgroups.

From those initial e-mails, three students, one each from interviewee categories two, four,

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and eight, volunteered to participate in an interview. An additional round of five e-mails

was sent to potential interviewees from the remaining five subgroups and one student

from interviewee category five volunteered. The researcher had more difficulty securing

participants from the remaining four subgroups. The researcher began sending e-mail

requests in groups of 10 to candidates in the remaining four subgroups. After sending

two more rounds of ten e-mails, two student participants were secured from interviewee

categories one and three. A participant for interviewee category seven was not obtained

until all students in the subgroup had been e-mailed. For interviewee category six, a

participant could not be obtained.

The researcher scheduled a time to interview with each willing participant.

Before the interview, each participant was e-mailed a consent form and was required to

sign and return it to the researcher. Electronic signatures were accepted. Prior to

conducting the interview, the researcher also verified that each student remembered using

the NPC. All seven students who volunteered for interviews indicated that they

remembered using the calculator. The researcher spoke to each student by telephone and

asked seven open-ended questions regarding the student’s experience using the NPC.

The following questions were asked of each interviewee:

1. What did you like about using the NPC? What did you dislike about using the

NPC?

2. What was your reaction to the net price estimate provided by the NPC?

3. How did the NPC results compare to your expectations for net price?

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4. At what point in your college search process did you choose to use All-

American University’s NPC? Why did you decide to use the NPC at that

time?

5. Did the NPC influence your decision about whether to apply to and/or enroll

at All-American University? In what way?

6. Were there other factors beyond the NPC that influenced your decision about

whether to apply to and/or enroll at All-American University? Please explain.

7. Were there any specific individuals who influenced your decision about

whether to apply to and/or enroll at All-American University? Please explain.

The interviews were recorded using an audio recorder and the researcher also took hand-

written notes.

Qualitative Descriptive Statistics

The students interviewed had a variety of academic abilities and came from a

variety of family and financial backgrounds. Table 16 displays demographic

characteristics for each student interviewed. Students are represented in the table by an

assigned pseudonym to protect their identity.

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Table 16

Demographic Characteristics of Student Interviewees

Student Application Submitted

ACT Score

NPC Net Price GPA House-

hold SizeParent AGI

Parents Together

Out-of-State

ResidenceMichael Yes 30 32,985 4.00 4 133,211 Yes Yes

Jenna Yes 29 18,600 3.98 6 84,253 Yes Yes

Jacob Yes 20 41,117 2.92 4 50,000 Yes No

Ashley Yes 23 9,460 3.70 9 48,000 No No

Emma No 30 33,185 3.85 5 250,000 Yes Yes

Sam No 17 34,385 3.20 4 80,000 Yes No

Mark No 25 10,110 4.00 5 40,000 No No

Qualitative Data Analysis

All student interviews were transcribed and coded by the researcher. The

researcher sought themes related to why the students used the NPC, what role the NPC

played in the college decision process, and to look for other factors that influenced

student college decision. Coding of each student interview uncovered several common

themes.

NPC Used to Narrow Choice

All of the students interviewed indicated that they had used the NPC during their

process of narrowing down the number of schools being considered. For some of the

interviewees, the NPC was used early in the process to help determine where they would

submit an application for admission. This was especially true for students whose

estimated net price was below the average, indicating less family resources, and whose

ACT scores were below the average. Both Mark and Ashley reported using the NPC to

narrow school choice before submitting an admission application. Mark shared, “Before

I even scheduled a visit, I would use their calculator.” Ashley had a similar experience:

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I was determining on where I was going to apply based on how much it cost for

everything. If it was going to be quite a bit of money, I would just kind of narrow

down my list based on which schools cost less and still get a good education.

Sam and Emma also responded that they had used the NPC before applying to a

university. For Mark, the results of the NPC dissuaded him from applying to All-

American. Mark indicated that he was looking for a financial aid offer from a school

“that would give me nearly everything.” Ashley had the opposite experience and found

the NPC estimate from All-American to be better than she expected; this prompted her to

submit an application for admission.

Other interviewees had already applied to All-American before they used the

NPC. Two of these interviewees had above average ACT scores. Michael said, “I

applied to all of the schools and then afterwards I checked and made sure how much the

exact cost for everything was.” Jenna also used the NPC after applying saying that she

used the tool “kind of towards the end when I had narrowed it down to my last couple of

choices and it was really just going to come down to the price for the most part.” She

went on to say that she used the NPC so she “didn’t have to wait all the way until I got

my actual financial aid package.” For Jenna, the NPC helped give her an early idea of

her official award package, but it did not drive her application decision. She added that

using the NPC “reduced my stress” of waiting for the official award offer.

In addition, students reported using multiple NPCs to narrow college choice.

Every student that was interviewed indicated using more than one NPC during their

college choice process, with as few as two and as many as 20 NPCs. The average

number of NPCs used was seven. The students with a net price below the average had

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the highest number of uses. Mark reported using around 20 different NPCs; Jenna

reported using eight and Ashley seven. The remaining interviewees, who had a higher

net price, averaged about three NPCs each.

Concerns About Accuracy

The first question asked of each interviewee focused on what they liked about

using the NPC and what they disliked. Many of their answers were vague and hinted that

enough time had passed since using the tool that the details were a little blurry. One clear

concern that arose from five of the seven students was the accuracy of the tool. In this

regard, Jacob commented: “One thing I didn’t really like is that it can’t be as accurate as

you want it to be just because it’s obviously way different than what my actual cost is

now after everything has been said and done.” Emma echoed his thoughts saying,

“There’s a lot of variables that you put into the net price calculator that may or may not

play out the way you think they will.” Ashley wished the NPC could be “more precise on

what the actual cost would be,” and Mark stated that “one of the things I universally did

not like about any of them is the vagueness.” Jenna spoke about using the tool with her

father and said that there were parts where her dad “wanted to put in some more

information” so as to “get a closer feel for the price.”

Surprising Results

Five of the students interviewed indicated that the results they received from the

NPC were surprising, or were different in some way from what they anticipated. Three

students actually used the word “surprised” to describe their results. Some were

surprised in a positive way and for others, it was negative. Emma said her reaction was

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“oh gosh that’s a lot of money,” and Jacob indicated being surprised at how high his net

price was.

For Ashley, the results were very positive. She shared, “I was really surprised

because I didn’t think I could be able to afford All-American.” Ashley confided that the

award offer was “almost twice as much than what I thought.” Michael had a similar

reaction and stated, “I was actually surprised at how [pause] I mean it was cheaper than I

expected.” Jenna and Mark both agreed that the estimate seemed like something their

families could afford even though Mark was looking for a larger financial aid offer.

Factors Beyond Price

One of the clearest themes that emerged from the interviews was that not one

student made their college decision based on price alone. All students interviewed

referenced other factors that were considered when making their college decision.

Athletics. Three students spoke about their desire to play a specific sport. For

Mark, who referenced his NPC results as a large contributing factor in not applying to

All-American, soccer was also a consideration for him. Mark reflected on the soccer

program at All-American and said that he sought an institution he could play soccer at

and “didn’t see possibly the opportunity of playing for that program with the players they

had currently.” Mark admitted that soccer was a “large reason” for not applying, but that

“it was also based on price.” He openly added that “if the school would have given me a

full ride, I would have played for whoever.”

Michael also spoke about his desire to play soccer and Jenna remarked that she

was “looking to run cross country and track.” She stated that her desire to participate in

the sport was “part of how I found this school” and the reason she applied to All-

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American. Jacob also discussed athletics as a contributing factor in his college decision

process. One of the reasons Jacob chose All-American was because of his desire to

wrestle. He liked the wrestling coach and the teammates he would wrestle with.

Location. The location of All-American and the size of the town in which it is

situated also influenced the college choice decisions made by four of the seven students.

Three of these four students had ACT scores below the average. Ashley explained that

her college decision was based on choosing a school within commuting distance from

home because she “didn’t want to live on campus and pay that extra amount.” Jacob also

indicated that All-American, being “a little bit closer to home than the other schools,”

was a positive factor in his choice to enroll. For Sam, who lived in a community close to

All-American, the short distance was a negative factor. He spoke about how he “just

wanted to get away a little bit” and ultimately opted against applying to All-American for

that and other reasons.

Emma reported that the distance between All-American and where she grew up

was a negative factor, and she also talked about the size of the community in which All-

American is located. All-American is located in a community with a population of just

over 5,000. Emma spoke about how she grew up in a small town about the same size and

that the size of the community “was something I really wanted to get away from.” She

added, “I didn’t think I was really going to appreciate the small town atmosphere again.”

Emma shared that she ended up choosing a school that was located in a city with a

population of over 400,000. Also, while none of the others expressed it, Emma

referenced a “kind of feeling you get” as a reason for choosing a different institution.

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Academic Major. Several of the students interviewed discussed their decision to

attend, or not attend, All-American because of the academic major they desired to pursue.

The importance of a major was only identified as an additional consideration by those

students whose net price was above the average. For Michael, the major and uniqueness

of the academic major offered by All-American was a positive factor. Emma looked at

the same academic major, but found the course requirements intimidating because they

did not allow a lot of room for the exploration of other majors. She expressed concern

that “you are accepted right away” and it can be “scary” to figure out what to choose as a

major. Sam also did not choose All-American because of programs. Although All-

American offered the major he wanted, another school offered a minor he could combine

with the major that he found very attractive. Sam also viewed All-American as being a

school known for a specific major, and he did not see himself at All-American because he

was not interested in that major.

Limited Parental Involvement in the Decision

The last question asked of each student interviewed focused on the individuals

who influenced their decision to apply, or not apply, and enroll at All-American

University. When first asked the question, none of the students immediately discussed

their parents. Jacob mentioned being influenced by the wrestling coach and a friend who

had decided to attend All-American. Sam spoke about talking with his guidance

counselor and asking his counselor which schools would be good to consider. Sam also

mentioned talking to friends who were planning to attend All-American and a friend who

was planning to attend the college that Sam ended up choosing.

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With prompting from the researcher specific to parents and/or guardians, each

student described the role their parents played in their college decision. None of the

students who were interviewed indicated that their parents told them where they could or

could not attend. Michael said that he and his mother had looked at a book about

colleges and “then we picked our favorite options,” and Mark mentioned his parents’

desire for him to attend the schools they had graduated from. Sam spoke about his

parents wanting him “to stay close to home,” and Jenna explained that her father had

helped her use the NPCs to look at price. However, ultimately, the interviewees stated

that the final decision was left to them.

Several students talked about their parents allowing them to make their own

decision. Jacob said that his parents “wanted me to make the decision I wanted to make

so they didn’t really try to convince me to go anywhere.” Emma emphasized that her

“mom was very adamant about that she was not going to make the decision for me.”

Jenna explained that her parents wanted her to “see the big picture and where this price

compared to other ones, but they weren’t trying to sway me one way or the other.” Jenna

added, “They wanted to let me make my own decisions.” Michael’s experience was

similar to the others. He talked about his mom “guiding me along,” and that “she wanted

whatever she thought was best for me so she just decided to let me choose because I

know best for myself.”

Incorrect Factors

Something noticed by the researcher throughout the interviews was the use of

incorrect information or faulty assumptions made by three of the students, all of whom

came from the group of students who were estimated a higher than average net price.

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Sam commented that when he used the NPC for All-American, it did not give him an

estimation of financial aid. He remembered it showing cost but nothing else. Sam

understood that the NPC should give a financial aid estimate and remembered getting one

from a different college’s NPC that he used. The All-American NPC data file showed

that Sam was offered $8,000 in financial aid through the NPC, which was contrary to

what Sam remembered.

In Jacob’s case, wrong financial information was entered which prompted a very

small offer of financial aid from the NPC. Fortunately, Jacob explored this further and

pursued a full financial aid package from All-American. During his interview, he

mentioned the difference in the NPC estimate and his award package.

Finally, Emma disclosed her concerns with All-American not using a weighted

GPA to calculate scholarships offered to students. This statement was incorrect because

All-American does use weighted GPAs. Like Sam, it seems that Emma used incorrect

information in her college decision process.

Summary of Quantitative and Qualitative Findings

The quantitative analysis sought to determine the percentage of NPC users that

applied to and/or enrolled at All-American University. The analysis also sought to

determine any differences that existed in the percentage of applicants and/or enrolled

students who used the NPC in their first contact with the university versus students who

used the NPC later on in the inquiry process. The quantitative analysis also sought to

determine if specific student characteristics reported on the NPC could predict the

student’s likelihood of enrolling at All-American.

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Through use of a chi-square test, findings indicated that applicants to All-

American were significantly more likely not to have used the NPC than to have used the

NPC. The findings also indicated the same significant results for enrolled students. A

second chi-square test revealed that for students who used the NPC, but not as a first

contact with All-American, were significantly more likely to apply than a student who

used the NPC as a first contact. Results were the same for enrolled students, indicating

those students were significantly more likely to enroll if their first contact with All-

American was through a form other than the NPC.

A discriminant analysis test revealed little relationship between student GPA,

ACT, net price, state of residence, parents remaining together, household size, and parent

AGI and the likelihood of application to the university. A slightly stronger relationship

was found between the predictors and the likelihood of enrollment at the university.

The qualitative analysis used semi-structured interview questions to learn more

about why students used the NPC and how it and other factors influenced college

decisions. Six themes and three subthemes emerged: (a) use of the NPC to narrow

college choice; (b) concerns about the accuracy of the tool; (c) surprise at the results of

the NPC; (d) factors beyond price that influenced the college decision with the subthemes

of athletics, location, and academic major; (e) limited parental involvement in the

decision; and (f) the use of inaccurate information in the decision process. Differences

were noted between students whose ACT scores were below average and those whose

scores were above average. Differences were also noted between the group of students

quoted a lower than average net price and those quoted a higher than average net price.

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CHAPTER FIVE

SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS

The Higher Education Opportunity Act of 2008 (HEOA) created a new

requirement that all colleges and universities receiving Title IV assistance provide a Net

Price Calculator (NPC) on their website. The purpose of the calculator was to increase

transparency with college costs and allow prospective students and their families to get

an estimate of the net price, the total cost minus financial aid, to attend a college. Even

though NPCs have been posted on college websites since October 2011, very little

research exists on the effect of the NPC on student college choice. The purpose of this

research study was to analyze the use of the NPC by prospective students at a small,

high-cost, private university in the Midwest and to understand how the NPC fits into the

college choice process.

This chapter presents a summary of the study and discusses its findings,

limitations, implications for practice, and recommendations for future research.

Summary of the Findings

The intent of this mixed methods study was to understand the use and role of the

NPC in the college choice process. The researcher used a quantitative data analysis

followed by a qualitative data analysis and later combined both analyses for

interpretation. All data were collected from All-American University, a small, high-cost,

private university in the Midwest.

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The conceptual framework used in this study was Perna’s (2006a) model of

college choice. Perna’s model maintains that student college choice is a process of

evaluating the costs and benefits of college with consideration given to the student’s

academic abilities and the resources available. Further impacts on college choice are four

layers of influence that include the student’s habitus, community, colleges being

considered, and public policies.

Quantitative data, gathered from the NPC and All-American University’s SIS,

were analyzed using a chi-square test and discriminant analysis. Qualitative data were

gathered through interviews with prospective All-American students. Open-ended

questions were used in the interviews to gather information.

The chi-square tests revealed that students who applied to All-American were

nearly 16 times more likely not to have used the NPC than to have used it. Use among

enrolled students was somewhat higher, but still over 88% of enrolled students had not

used All-American’s NPC. A second chi-square test analyzed the application behavior of

NPC users based on whether the NPC was the student user’s first contact with the

university. The tests revealed that NPC users who had made first contact with All-

American in a form other than the NPC were nearly three times more likely to apply than

those students whose first contact was the NPC. For enrolled students, the results were

similar with these students being nearly four times more likely to have made first contact

with All-American in a form other than the NPC.

The final quantitative analysis performed was discriminant analysis to determine

if certain characteristics of NPC users could predict the likelihood of the student user to

apply and/or enroll. A weak positive correlation was found between the predictors and

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student likelihood of applying to All-American. The most discriminating variable was

state of residence (in-state vs. out-of-state). The analysis found that students who (a) had

a higher GPA, (b) lived in-state, (c) came from a larger household, and (d) had parents

with a lower AGI were more likely to apply to All-American. Students who (a) had a

lower GPA, (b) lived out-of-state, (c) came from a smaller household, and (d) whose

parents had a higher AGI were less likely to apply to the university. For enrolled

students, (a) having a higher GPA and (b) living in-state increased the likelihood of

enrollment. The likelihood of enrollment decreased for (a) students with a lower GPA

and (b) those who lived out-of-state. Similar to accepted students, state of residence was

by far the most discriminating variable for enrolled students.

Qualitative data were gathered through interviews with prospective students who

had used All-American University’s NPC. Four of the students interviewed had applied

to All-American and three had not. The interviewees were asked seven open-ended

questions about their experience using the NPC and making a college decision. Six

themes and three subthemes emerged from the interviews. The themes were: (a) use of

the NPC to narrow college choice; (b) concerns about accuracy of the tool; (c) surprise at

the results of the NPC; (d) limited parental involvement; (e) use of inaccurate

information; and (f) factors beyond price which include the subthemes of athletics,

location, and academic major.

Findings and Interpretations

Discussion of the Quantitative Results

The quantitative portion of this research study was guided by three research

questions. The first quantitative research question was: Will the percentage of potential

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applicants to All-American University who self-identify while using the NPC and

subsequently (a) apply to the University and (b) enroll be significantly different than the

percentage of potential applicants who do not use the NPC and (a) apply and (b) enroll?

This researcher hypothesized that the percentage of applicants who self-identified while

using the NPC and subsequently (a) applied to the University and (b) enrolled would be

significantly lower than the percentage of potential applicants who did not use the NPC

and (a) applied to the University and (b) enrolled. The study’s results proved this

hypothesis to be correct. Only about 6% of students who applied to All-American

University and 10% of students who enrolled had self-identified as a user of the NPC.

Most prospective All-American students have not used All-American’s NPC.

These results were not surprising considering the findings from other recent NPC

studies. The Noel-Levitz (2013) firm surveyed over 5,000 high school students who

were college bound to ask about their use of school NPCs. The surveys found that over

60% of students had never used a NPC. Noel-Levitz listed this as their number one

report finding. Hesel and Williams (2010), whose study took place prior to the NPC

federal mandate, also found that only 26% of students and/or parents had used a financial

aid calculator. Although the goal of the federal government in implementing the NPC

requirement was to increase transparency of college costs, many students and families

have not taken advantage of the opportunity.

The second quantitative research question asked was: Will the percentage of

potential applicants to All-American University who self-identify while using the NPC in

their initial contact with the University and subsequently (a) apply to the University and

(b) enroll be significantly different than the percentage of potential applicants who self-

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identify while using the NPC later on during the inquiry process and subsequently (a)

apply to the University and (b) enroll? This researcher hypothesized that the percentage

of potential applicants who self-identify while using the NPC as their initial contact with

the University and subsequently (a) apply and (b) enroll will be significantly lower than

the percentage of applicants who self-identify while using the NPC later on during the

inquiry process and subsequently (a) apply and (b) enroll.

Results from the quantitative analysis showed this hypothesis to be true. Students

who used the NPC as an initial form of contact with All-American were less likely to

apply and/or enroll than students who used the NPC as a later form of contact with the

University. Of the students who used the NPC and applied to All-American, only 26%

were students who used the NPC as a first contact with the university. Students who

made contact with the university in other ways, before using the NPC, were nearly three

times more likely to apply to All-American than those whose first contact was the NPC.

The results were similar for enrolled students. Almost 80% of NPC users who enrolled at

All-American had used the tool later on in the inquiry process. Students who chose to

use the NPC as the first form of contact with the university enrolled at a much lower rate.

These findings demonstrate that students who choose to explore cost as a first

interaction with All-American are eliminating consideration of the university based on

the net price presented within the NPC. In its survey, the Noel-Levitz (2013) firm found

that 33% of NPC users said the tool altered the user’s perception of a school, with just

12% of the NPC users reporting a negative effect. In this researcher’s study, it is

unknown how many students found the effect to be negative; however, the percentage of

students who did not choose to move forward with an application to All-American

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indicates that more of this study’s participants found the net price negative than the

participants in the Noel-Levitz (2013) study. Alternatively, the results of this study may

indicate that students using the NPC as a first form of contact with All-American are still

considering many different colleges and are using the NPC to compare price before

deciding which schools to apply to. Previous studies have shown that students will

eliminate colleges from consideration based on cost before financial aid is awarded, but

these studies have not surveyed how many students eliminate colleges based on net price

(Hesel & Meade, 2012; Hesel & Williams, 2010).

The third quantitative research question asked was: Will high school GPA,

ACT/SAT scores, level of financial aid estimated, parent income, number in the

household, state of residence, and parents together listed in the NPC by the self-identified

users significantly predict an applicant’s likelihood to (a) apply and (b) enroll at All-

American University? This researcher hypothesized that a combination of these variables

would significantly predict a prospective student’s likelihood to (a) apply and (b) enroll

at the University.

The results of the analysis show that only a weak positive correlation existed

between the predictor variables and likelihood of application. The variables as a group

were not strong predictors of a student’s likelihood to apply or enroll. A few variables

did stand out as stronger predictors of application than others, including (a) having a

higher GPA, (b) being an in-state resident, (c) coming from a larger household, and (d)

having parents with a lower AGI. For enrolled students, the overall results were similar,

but only two variables were found to be stronger predictors of enrollment. Those two

variables were (a) a higher GPA and (b) being an in-state resident.

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The finding that students with a higher GPA are more likely to apply and/or enroll

at All-American than students with a low GPA corresponds with earlier research that

found students with good grades and good test scores were more likely to attend a higher-

cost institution (Hearn, 1988, 1991). The strength of the other variables, including a

larger household size and lower parent AGI, and their impact on the likelihood of

application is more puzzling. Hearn (1984) found that students having more siblings

were somewhat less likely to attend a college that was highly selective or had a higher

spending level per student than other colleges. The age of Hearn’s study may indicate

that number of siblings no longer impacts college decision the way it once did. The

difference might also be attributed to who is included in a household, such as number of

parents. A two-parent household is often larger than a single-parent household. So

coming from a larger household may increase the likelihood of application because it is a

two-parent household. Lillard and Gerner (1999) found that students who live in a

household with both of their biological parents, specifically during high school, are more

likely to apply to college. These students are also more likely to attend a four-year

college and a more selective college than students living with only one biological parent

(Lillard & Gerner, 1999).

The finding that students whose parents have a low AGI have an increased

likelihood of applying to All-American also contradicts much of the past research.

Several studies have found that students from lower SES backgrounds are less likely to

select a higher-cost institution (Hearn, 1984, 1988; Perna & Titus, 2004). It is important

to remember that this finding in the study of All-American was only specific to NPC

users. It may be that students from higher-income households were disappointed in the

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net price displayed and, therefore, chose not to apply to All-American. These students

likely would have only qualified for an academic scholarship and, at maximum, a small

need-based grant and may have been looking for larger offers. This finding might also be

explained by reviewing the research of Reynolds and Pemberton (2001) who found that

from 1979 to 1997, the influence of family resources on student college enrollment had

decreased. It is possible that family resources have continued to decrease as an

influencer of college enrollment.

By far the strongest predictor of application or enrollment for NPC users was

being an in-state resident. This finding is supported by other research. Mattern and

Wyatt (2009) studied student data from several national databases and found that 72% of

the students studied chose to attend a college that was located in the student’s home state.

DesJardins et al. (2006) found that while students initially considered a public university

out of state, many did not actually enroll at the university. Of the ACT score reports

received at the public university, 19% came from out-of-state students but the university

enrolled just over 8% of freshmen from out of state (Desjardins et al., 2006). This

research study, and the others mentioned, demonstrates that while students may be

initially willing to consider colleges in a different state, the likelihood of actually

enrolling is low.

Discussion of the Qualitative Results

The qualitative strand of this research study was guided by five research questions

including:

I. What are the perceptions of potential applicants regarding use of All-

American University’s NPC?

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II. What perceptions do potential applicants to All-American University

report regarding the results of the NPC?

III. What prompted potential applicants to All-American University to use the

NPC at the time they did?

IV. To what extent do potential applicants to All-American University report

that the use of the NPC influenced their decision to apply to the

University?

V. Were there other factors or individuals beyond the NPC that influenced

potential applicants to apply to All-American University?

The coding of interviews of seven students, four who did apply to All-American

and three who did not apply, revealed six themes and three subthemes related to the

student college decision process and the role of the NPC. The first theme to emerge was

the use of the NPC to narrow student college choice. All seven of the students

interviewed reported that they had used the NPC to narrow the list of colleges being

considered. Some used the NPC earlier on in the process than others. Students who were

quoted a below average net price, indicating a lower family income and more financial

need, tended to use the NPC before application to a university. Two of the three students

in this category, who also fell in the below average ACT category, used All-American’s

NPC as a way of determining if they should apply to the university. These students were

focused on how much the college would cost and were not willing to submit an

application until they determined that the college was affordable. As mentioned

previously, research by Hesel and Meade (2012) and Hesel and Williams (2010)

determined that many students do eliminate colleges from consideration on the basis of

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cost. Two students in the above average net price category also used the NPC before

application to All-American, and ultimately decided not to apply, but did not cite cost as

the primary reason. These students had used the NPC to get a better idea of cost, but

decided not to apply because of desired majors and other reasons.

Other students used the calculator later on in the process after they had applied to

All-American University. These students were looking for an early financial aid package

and did not want to wait until the spring to make their college decision. Both found the

net price from the NPC affordable and made their decision to attend All-American.

In addition, significant differences in the number of NPCs used by each student

were discovered from the interviews. Students whose net price was below the average

were far more likely to use the NPCs of many different colleges. One student from this

group reported using twenty NPCs, another reported seven, and a third reported eight.

Interviewees from the above average net price group used less, with an average of about

three NPCs each. Clearly cost was of great concern to the students having less family

resources. Other research has also found the significance of cost for families with limited

resources. MacAllum et al. (2007) found that low-income families list costs and financial

aid as one of the top two considerations when choosing a college.

The second theme that emerged during analysis was student concerns about

accuracy of the tool. Five of the seven interviewees felt the tool could be more accurate

or allow for the input of more information. Many of the students were not very specific

about what in the tool they would like to be different. This could be because too much

time had passed since using the NPC, or it could indicate a general uneasiness about the

accuracy of the results. Many of the interviewees made decisions about application and

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enrollment due to the NPC results and may have felt some concern about basing

decisions on an estimate. Research conducted by the Noel-Levitz (2013) firm indicated

that most students and parents understand the results are just an estimate and do not

expect more than that; however, 28% of this study’s participants did have an expectation

of an exact offer from the NPC. Even though most of the interviewees understood the

NPC results to be only an estimate, they were concerned about accuracy because the

results were used to make important college decisions.

The third theme that emerged from the interviews was an element of surprise

regarding the NPC results. Five out of the seven interviewees received different results

from what was expected. For some, the results were positive and for others negative. A

study conducted by Ikenberry and Hartle (1998) highlighted why students and families

are surprised by cost and financial aid estimates, especially those who find the institution

more affordable than expected. The researchers found that the public often overestimates

the cost of college by a significant factor. The subjects in their study overestimated the

cost of a four-year public university by an average of 99% (Ikenberry & Hartle, 1998).

The costs for private and community colleges were also overestimated. The NPC is often

a student’s first introduction to cost and financial aid so surprise is a common reaction

when the results do not match what the student expected to find.

Theme four from the qualitative analysis highlighted the many factors beyond

costs that students consider. Although cost was a major decision factor for some of the

interviewees, all interviewees spoke about other factors that played a role to some extent

in their college decision. Those factors separated into three subthemes: athletics, location

and major.

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Three of the seven students interviewed spoke about their desire to participate in

collegiate athletics and chose a college where they liked the athletic program and would

be able to participate. The students were looking for a college that was affordable, but

also offered the option to continue participating in their favorite sport.

Four students spoke about the role that location played in their college decision.

Two students found All-American the perfect distance from home, while one student

found it was too far and another found it to be too close. The students with issues

regarding the distance from home to All-American decided not to apply to the University.

Hurwitz (2012) also discovered distance between a college and the student’s home to

have an impact on college decisions. Hurwitz found that applications to selective

colleges decrease as the distance from home to the college increases. The interviewee

whose home was furthest from All-American chose not to apply and cited the distance as

one of the factors considered.

Finally, the student’s intended academic major was cited as a factor, outside of

cost, that impacted the college decision. Of importance is the finding that only students

whose net price was above average cited academic major as a factor. These students

indicated that they decided for or against the University based on their desired major and

if it was offered by All-American. It is unknown why major was cited only by students

having greater family wealth. Possibly these students used academic major to develop a

list of choice schools in the same way that students with less family resources used net

price. In addition, students with fewer resources may have been more willing to adjust

their major based on which colleges were affordable. Further research is needed on the

role academic major plays in college decision making.

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A fifth theme that emerged was parental involvement in the college decision. The

students were all asked a question regarding the role that “individuals” played in their

college decision. The researcher anticipated that parents would be the first “individuals”

mentioned by the interviewees. Several studies have emphasized the importance of

parents in the college decision. Dale (2010) found that parents are the most influential

people in a student’s college choice and that the more encouragement parents offer the

more likely a student is to attend college. Hossler et al. (1999) also found a positive

relationship between student college attendance and parent encouragement. The

responses of the interviewees in this study were surprising. None of the students

mentioned parents right away. One talked about a guidance counselor, another about a

coach, and a couple about friends, but none talked about parent involvement until

specifically asked.

Once prompted, the interviewees did talk about the role their parents took in the

college decision process. None of the students was told by their parents where they could

or could not attend. One student said her parent played no role in the college selection

process, while the rest talked about their parents being supportive and trying to help them

gather facts to make a decision. It is unknown whether this type of parental involvement

is typical for all students or specific to the students interviewed. The process of finding

these seven students to interview demonstrates that parents are more involved in some

cases than in others. It was evident that many of the e-mail addresses listed on the NPC

user records were parent e-mail addresses so the e-mails from the researcher requesting

an interview may have reached the parents only. None of those students responded to the

interview request. Even several students who appeared to have used a student e-mail

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address wrote back that they had never used the NPC. In one case, a grandmother wrote

back that she had used the NPC for her grandson and was willing to talk with the

researcher. In these cases, it is likely the parents, and possibly other family members,

were more involved and led the conversation about price and financial aid related to the

college decision compared to the students who volunteered to participate in the

interviews.

A final sixth theme was the use of incorrect information with the NPC was

revealed during the interviews. This issue was especially prevalent with students who

were quoted an above average net price. One student entered incorrect financial

information prompting a very small offer of financial aid that ended up being larger in the

final award package. Another student very clearly remembered using the NPC, but said

that no financial aid was offered. Review of the NPC data file showed this was incorrect

and the student was indeed offered financial aid in the NPC results. A third student

misunderstood All-American’s scholarship practices and assumed the University would

not consider her weighted GPA.

This theme highlights the concerns that many enrollment managers have

surrounding use of the NPC. If a student does not input correct information into the

NPC, then the financial aid estimate is incorrect and the student makes a college decision

on faulty information. This is especially an issue when students choose to take a school

off their list before they have even applied or received an official award package.

Integration of the Quantitative and Qualitative Findings

This study purposefully employed a mixed-methods design so as to use

quantitative analysis to discover what the data from the NPC indicated about application

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and enrollment behavior and to use qualitative interviews to understand why students

behave in those ways. Combining both the quantitative and qualitative analyses

highlights two important findings.

First, students who use the NPC as the first form of contact with the University

are much less likely to apply to All-American than students who use the NPC later on in

the inquiry process. The quantitative results of this study showed this to be the case. The

qualitative interviews also support this finding. All three students who were interviewed

but did not apply to All-American used the NPC as their first inquiry to the University.

Only one of the four students who did apply, used the NPC as a first point of inquiry, and

that student was very focused on cost. If the NPC results had not met her expectations,

she stated that she would not have applied. For students with higher family incomes,

factors beyond cost may play a more significant role than for students with lower family

incomes. Three of the four interviewees who came from families with higher incomes

cited academic major as a primary reason for applying, or not applying, to All-American.

Two of these students had used the NPC as a first point of contact and did not apply.

Even though the other two students were disappointed with the financial aid offered, their

intended academic major was the prominent factor in deciding to enroll. None of the

students from lower income families discussed academic major as being a factor, and two

of the three said that cost was a main driver in their college decision.

Second, while the quantitative results show that some student characteristics such

as a lower family income, larger household, and living in-state indicate a stronger

likelihood to apply and/or enroll, the qualitative results show that other factors may be

more influential on a student’s college decision. In fact, of the variables tested in the

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discriminant analysis, only net price and location were mentioned by students during the

interviews as having an impact on college decision. The factors most frequently

mentioned by interviewees as influencing the college decision were often characteristics

of the university. Athletics and academic major were mentioned by several of the

students as well as location. It may be that university characteristics become most

important once a student has decided on going to college and has developed a list of

schools to consider. Other family characteristics may play a larger role in the student’s

initial decision to pursue a college degree and the type of institution to attend. At the

point students used All-American’s NPC, those students had decided, to some degree, to

consider a four-year, private institution because they felt it was possible given all

circumstances.

Relationship of the Findings to the Study’s Conceptual Model

As stated previously, this study was guided by Perna’s (2006a) model of college

choice. A review of the findings in relation to Perna’s model indicates congruency. At

the center of the model is a cost/benefit analysis performed by the student and affected by

many factors and levels of influence. All seven interviewees performed a cost/benefit

analysis as they considered application to All-American University. The benefits

considered varied by student and included financial aid offered, opportunity to participate

in athletics, college location, and the student’s desired academic major. Ultimately, some

students found the cost to be too high compared to the benefits, whereas others found the

costs and benefits were balanced and chose to invest in an All-American education.

Perna’s model posits that student academic preparedness and family resources

influence the cost/benefit analysis. This was true for the interviewees in this study.

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Family income did play a role in how each student evaluated the cost of All-American

and the decisions each made related to the investment they were willing to make. Those

with smaller family incomes were more focused and concerned about overall cost and

made their college decision differently than students with higher family incomes. They

considered more colleges in their search and used more NPCs in order to find the college

with the best balance of costs and benefits.

Even though academic preparedness was a likely factor in college choice, it was

not mentioned by interviewees as a factor. Likely, the determination of academic

preparedness occurred before students used the NPC. Students felt they could succeed

academically at All-American and moved forward in the college selection process by

using the NPC and evaluating cost.

The first layer in Perna’s model is that of habitus. Habitus includes student

characteristics, culture, value of college, and knowledge about going to college. Results

from the quantitative analysis point to a few characteristics as influencing student choice

to apply and/or enroll at All-American. Characteristics such as location of the student’s

home and size of the household had some significance in the student’s likelihood to

enroll. Also related to this layer, all students interviewed valued college. While not all

enrolled at All-American, they did enroll at some type of four-year university. Each

student had the knowledge and family support to pursue a college education.

The second layer of Perna’s model relates to the resources available from the

student’s school and community. The quantitative portion of this study did not contain

variables that related to the school and community so a relationship could not be tested.

In the qualitative portion, the only reference to this layer was made by one student who

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briefly discussed help from a guidance counselor during his college search process and

another who mentioned a teacher suggesting All-American because of the academic

major the student wanted to pursue. Certainly the student’s school, including teachers

and counselors, does impact the college decision process for students, but this study did

not capture much regarding this influence.

Layer three of Perna’s model indicates that the characteristics and actions of the

institutions influence student college choice decision. This study identified several cases

of influence based on college characteristics. Both the quantitative and qualitative

strands of research identified the location of All-American University as important in the

college decision. The qualitative research also found that the academic majors offered by

the University were important as well as its extracurricular options such as athletics.

University characteristics such as these became part of the benefits considered along with

the cost. Actions of the University were mentioned just once during the qualitative

interviews when a student stated that the outreach from the wrestling coach encouraged

him to apply and enroll at All-American.

Finally, layer four of Perna’s model relates to the influence that public policy can

have on the student college decision. Similar to layer two, the influence of this fourth

layer was not fully explored in this research study. Federal financial aid options were a

part of the overall financial aid offer given to each student, so public policy may have

been influential in this way. Certainly, some students, especially those offered federal

grants, may not have applied and/or enrolled at All-American had the grant not been

offered. In addition, the NPC itself is a result of public policy. Findings from this study

suggest that NPC results do affect student college decisions. It is likely that some

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students would have made a different college decision had they not used the government-

mandated NPC.

Limitations

This study has several limitations. First, not all students who used the NPC listed

name and contact information. Because of this, their NPC user records could not be

analyzed in this research study. While it is anticipated that the results would still be

similar if all records had been analyzed, this assumption cannot be confirmed.

This study is also limited to the honesty and accuracy of the student NPC users.

All NPC data analyzed were entered by students. The researcher assumed all information

was accurate and true. Results from the qualitative interviews show there were errors in

the way at least one interviewee entered information when using the NPC. Likely others

made mistakes as well in providing accurate information. During the interviews, the

researcher also discovered that at least one student made errors in interpreting the

information presented in the NPC. There is a strong likelihood that others also

misinterpreted the NPC results.

The quantitative strand of this study is also limited because there is no verification

that the student was the NPC user in each case. An assumption was made that each user

was the student, but contact made during the process of finding interviewees indicates

that likely others used the NPC for the student. It is unknown if every student viewed the

NPC results and used the information in making a college decision. Quite possibly, some

parents and other family members used the NPC and did not share the results with the

student.

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Finally, this study is limited because an eighth interviewee could not be secured.

This eighth interviewee represented the population of students that had a higher than

average ACT score, a lower than average net price, and chose not to apply to All-

American. It is not anticipated that the overall results of this study would have varied

much with data from this interviewee, but it is important to note the absence of the

interview.

Implications for Practice

The findings of this study are helpful to enrollment managers. Table 17

summarizes the quantitative and qualitative findings and their relation to suggestions for

practice.

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Table 17

Relationships Between Quantitative Data, Qualitative Data, and Suggestions for Practice

Topic Quantitative Finding Qualitative Finding Suggestions for Practice

Use of NPC Applicants to All-American, and current enrolled students at All-American, were not likely to have used the NPC tool for learning more about cost and financial aid at the University.

To promote use of the NPC, colleges and universities should market this tool to prospective students.

Impact on College Decision

Prospective students who used the NPC as their first-contact with the university were not likely to apply and/or enroll.

NPC was used to narrow college choice.

Colleges must ensure that NPCs provide an accurate estimate of financial aid. The college’s financial aid awarding algorithm should be used instead to calculate estimates rather than using average award packages.

Students using the NPC as a first-contact should receive print and/or email communications that highlight the value of the university in relation to cost.

Students using the NPC later in the inquiry process should receive personal communication from enrollment staff members encouraging application and enrollment.

Significant Student Characteristics and University Factors

Students with a higher GPA, students living in-state, those from a household with multiple family members and those with a lower parent AGI were more likely to apply. Students with a higher GPA and those living in-state were more likely to enroll

Students considered cost and location of the University as well as the academic majors offered at the University when deciding whether to apply and/or enroll at All-American. The opportunity to participate in athletics was also a consideration.

Colleges should promote academic and social opportunities on webpages linking to the NPC. When possible, this information should also be promoted on the NPC results page.

Enrollment staff should use student characteristics to personalize communications to students. Characteristics should also be used to prioritize how enrollment staff time and resources are used.

Accuracy of Student Users and the NPC

Students were concerned about accuracy of tool but didn’t always use accurate information. They were often surprised by the results of the NPC.

The NPC must be easy to use and be as simple as possible while still maintaining accuracy. Results should be displayed clearly, and students should be encouraged to get a formal financial aid offer before making a college decision.

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The results show that students are using the calculator to make decisions. Even

though research by the Noel-Levitz (2013) firm have shown that students understand the

calculator produces only an estimate, results from both the quantitative and qualitative

strands of research show that some students chose not to move forward in applying to

All-American because of the NPC results. This means that a college’s NPC must be as

accurate as possible. NPCs that offer students an average award package could

negatively impact application and enrollment at the university, especially for students

whose NPC results reflect less financial aid than what ends up being offered.

The findings of this research are also helpful in understanding how to

communicate with the NPC user population. Many practices in enrollment management

focus on determining which students have a positive likelihood to enroll and channel

recruitment efforts towards these students. The results demonstrate that students who

have reached out to All-American in other ways, before using the NPC, are more likely to

enroll than those who use the NPC as the first form of contact. Focus should be given to

communicating in different ways with these two populations. The population that used

the NPC later on in the inquiry process already has some affinity with the institution

beyond cost. These students should be given more time and attention by enrollment staff

because they should be easier to enroll than the students who used the NPC as the first

point of inquiry. They have already reached out to All-American in more than one way

and likely the University is on their list of colleges. Contact such as personal phone calls,

e-mails, and written notes, among other things, would be beneficial to encourage

enrollment.

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Students using the NPC as a first inquiry should receive contact from a university

that speaks to the value of the institution. This communication needs to highlight the

benefits of the university, beyond cost, that should be considered in the cost/benefit

analysis. Students using the NPC as the first point of contact may know very little about

the university. While the likelihood of these students enrolling is not strong,

communication efforts to emphasize the university’s value and benefits may help.

The findings of this research can also inform lawmakers and policy advocates.

The intent of the NPC was to provide transparency about college costs, but the results of

this study show that most students still are not using the tool. Very few of the applicants

and enrolled students at All-American had used the NPC. National studies, such as the

one performed by Noel-Levitz (2013) also verify low usage of the tool. Lawmakers

should review this lack of use when considering new policies to implement. More

research is needed to understand why students are not using the tool and to explore ways

the tool can be improved or changed to better suit student needs.

Recommendations for Future Research

This study is limited to a small, private, high-cost university in the Midwest. It is

recommended that the study be expanded to larger institutions as well as to different

sectors such as public or for-profit. The research should also be performed at universities

in different regions of the United States. These kinds of expanded studies will determine

if prospective students at other universities act in similar ways, or if the actions of All-

American’s prospective students are unique.

Also, as previously noted, more research is needed to understand why many

students are not using the NPC tool. It is unknown if students are aware of the tool.

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Lack of use because students feel the tool is not helpful is very different from a lack of

awareness. More information is needed to understand why the tool is not widely used.

Opportunities for future research also exist in the finding from the qualitative

interviews regarding the significance of an academic major. In this study, only students

from the higher than average net price category spoke about major as an influencer in the

college decision process. It is unknown whether this finding is unique to students

interviewed for this study, or if the influence of academic major is different for students

having fewer family resources.

Finally, future research is needed to understand who is using the tool and why. It

was evident during this research study that many parents do play a part in use of the NPC,

even grandparents in at least one case. It is recommended that parents be interviewed

about their use of the NPC. A survey of the NPC user would also be helpful in gaining

some data about who is using the tool and why they are using it. Enrollment managers

would benefit from these findings because messaging could be appropriately targeted to

both students and parents that contains the information each group finds important.

Conclusions

This study sought to expand research regarding the use of NPCs by prospective

college students. Previous research on NPCs is limited, leaving enrollment management

professionals with little information regarding the impact of the NPC on the college

decision process. Results from this study highlight several findings of importance to

enrollment managers. Findings show that not many students used the NPC. Of those

who did use the tool, most used it to make decisions regarding which colleges to consider

during the college decision process. Some students even used the NPC to eliminate a

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college from consideration before an application was made to the institution. The study

also demonstrated that while cost was a critical factor in the college decision process, it

was typically not the only influential factor. Students in this study also considered

college characteristics and opportunities when they made their enrollment decision. Even

though not all aspects of the Perna’s (2006a) model of college choice were investigated,

the findings of this study are consistent with the model.

Enrollment managers may use the findings of this study to shape communication

and outreach to NPC users, but should be cautioned that this study’s findings are from

one private university in the Midwest and are based on one cohort of students who used

the NPC during their college search process. Findings of this study indicate that

enrollment staff should focus efforts on students who use the NPC later on in the inquiry

process. These students have a greater likelihood of application and enrollment and may

be convinced to apply and/or enroll through additional contact. Conversely, students

using the NPC as a first point of inquiry with the university are less likely to apply for

admission. Enrollment managers should, at minimum, establish a communication plan to

send special messaging immediately after NPC use to the first-inquiry users regarding the

benefits and value of the university. Some of these users may reconsider the university if

value is carefully presented along with cost. Overall, this study found that the NPC is a

tool students use to help make a college decision and with strategic communication,

enrollment managers may use the database of users to encourage application and/or

enrollment to the university.

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APPENDIX A

INTERVIEW QUESTIONS

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Appendix A

Interview Questions

1. What did you like about using the NPC? What did you dislike about using the

NPC?

2. What was your reaction to the net price estimate provided by the NPC?

3. How did the NPC results compare to your expectations for net price?

4. At what point in your college search process did you choose to use All-American

University’s NPC? Why did you decide to use the NPC at that time?

5. Did the NPC influence your decision whether to apply to and/or enroll at All-

American University? In what way?

6. Were there other factors beyond the NPC that influenced your decision whether to

apply to and/or enroll at All-American University? Please explain.

7. Were there any specific individuals that influenced your decision whether to

apply to and/or enroll at All-American University? Please explain.

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APPENDIX B

INFORMED CONSENT FORM

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Appendix B

Informed Consent Form

To: Potential Interview Participant

From: Melanie Weaver

Subject: Informed Consent to Participate in Study

Date: ________________________

Dear: _______________________,

My name is Melanie Weaver, and I am an Ed.D. student at Benedictine University. I am

researching student use of the online Net Price Calculator (NPC) provided by Ohio

Northern University. I am particularly interested in these main areas: (1) What positive

or negative perceptions do potential applicants report regarding the results of the NPC?

(2) To what extent did potential applicants report if the use of the NPC influenced their

decision to apply to the university? (3) What prompted potential applicants to use the

NPC at the time that they did? This research will add to the body of knowledge about

NPC purpose, usage, and value.

Thank you for your willingness to participate in the interview. Your participation is

voluntary. You do not have to answer any questions you do not want to answer. If at any

time you do not want to continue with the interview, you may decline. Your time and

involvement is deeply appreciated. The entire interview will take approximately 30

minutes. The interview will be recorded. At any time, you may request to see or hear the

information I collect.

The interview will be tape recorded and the interviewer will take notes. This is done for

data analysis. The tape will be transcribed by the interviewer and kept confidential in a

password-protected computer. All individual identification will be removed from the

hard copy of the transcript. Participant identity and confidentiality will be concealed

using coding procedures. For legal purposes, data will be transcribed on to a flash drive

and transmitted to a Benedictine University faculty member for secure and ultimate

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disposal after a period of seven years. Dr. Tamera Korenman is the Benedictine

University faculty member who will secure and ultimately dispose of the information.

Her information is at the end of this form. The researcher will also maintain a copy of

the data on a password-protected computer.

Excerpts from the interview may be included in the final dissertation report or other later

publications. However, under no circumstances will your name or identifying

characteristics appear in these writings. If, at a subsequent date, biographical data were

relevant to a publication, a separate release form would be sent to you.

Please sign this form on the line provided below to show that you have read and agree

with the contents. Please return it by e-mail to me at melanie.weaver@gmail.com. An

electronic signature is acceptable.

____________________________________________________

Your electronic signature above

(If you have problems with the electronic signature please call me at 419-302-5687.)

This study is being conducted in part to fulfill requirements for my Ed.D. degree in

Higher Education and Organizational Change at the graduate school of Benedictine

University in Lisle, Illinois.

The study has been approved by the Institutional Review Board of Benedictine

University. The Chair of Benedictine University’s Institutional Review Board is Dr.

Alandra Weller-Clarke. She can be reached at (630) 829 – 6295 and her email address is

aclarke@ben.edu. The chairperson of this dissertation is Dr. Tamera Korenman. She can

be reached at korenmantama1@gmail.com for further questions or concerns about the

project/research.

Sincerely,

Melanie Weaver

Benedictine University

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