college and career readiness: psychosocial predictors of .../67531/metadc...accurate predictors of...
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APPROVED:
Jimmy Byrd, Major Professor Mary Harris, Minor Professor John Brooks, Committee Member Linda Stromberg, Committee Member James Laney, Chair of the Department of
Teacher Education and Administration Jerry Thomas, Dean of the College of
Education Mark Wardell, Dean of the Toulouse
Graduate School
COLLEGE AND CAREER READINESS: PSYCHOSOCIAL PREDICTORS OF
ACHIEVEMENT AND PERSISTENCE
David Hicks, M.Ed.
Dissertation Prepared for the Degree of
DOCTOR OF EDUCATION
UNIVERSITY OF NORTH TEXAS
December 2014
Hicks, David. College and Career Readiness: Psychosocial Predictors of
Achievement and Persistence. Doctor of Education (Teacher Education and
Administration), December 2014, 102 pp., 16 tables, 4 figures, references, 131 titles.
Purpose: The purpose of this study was to determine if traditional indicators of
college readiness were better predictors of students’ first semester college GPA and
persistence to the second year of coursework compared to non-traditional indicators of
college readiness. Specifically, this study analyzed the predictive validity of high school
class rank and ACT/SAT scores compared to that of the psychosocial skills measured
by the ACT Engage on students’ first semester college GPA and their likelihood of
enrollment in the second year of college coursework.
Methodology: Linear and logistic regression models were used to examine the
effect of gender, age, ethnicity, socioeconomic status, high school rank, Texas Success
Initiative college readiness scores, SAT or ACT scores, and the ten themes of the ACT
Engage Inventory (dependent variables), on students’ first semester college GPA and
rate of persistence to the second year (independent variables). A sample of 4,379 first
semester college freshmen participated in this study.
Findings: Results indicated that high school rank, ACT/SAT scores and
psychosocial skills measured by the ACT Engage theme academic discipline were
accurate predictors of college performance. Results regarding the predictive power of
traditional academic and non-traditional psychosocial predictors of persistence were
less definitive. Students qualifying for federal financial assistance and female students
showed the greatest likelihood of not returning for the second year of college.
Research Limitations: One limitation of this study occurred because separate
ethnicities were not evaluated as independent variables. Additionally, further research
should occur regarding the relationship between the independent variables of gender
and socioeconomic status and the dependent variable persistence.
Practical Implications: Due to the predictive power of high school class rank,
college entrance exam scores, and the psychosocial skill of academic discipline,
educators and policy makers should design targeted preparation and support initiatives
around improving students’ skills in these areas. Recommendations for such initiatives
were provided.
Value of Paper: This paper is valuable to educators at the secondary school and
university levels because results can be used to design preparation and support
programs in order to improve students’ performance and persistence at the college
level.
Copyright 2014
by
David Hicks
ii
ACKNOWLEDGEMENTS
I would like to extend my deepest thanks to everyone who has encouraged and
supported me on this journey. To my wife, Tammy, and children, Keaton and Aubrey,
thank you for understanding when I worked late, missed a game, or took my box of
research with us on vacation. I love you tremendously! To my parents, Alexander and
Marilyn Hicks, thank you for instilling in all of your children a love for learning and a
passion for excellence. It is because of your sacrifices, support and love that each of us
has been able to pursue our dreams. My brother Steve, my sisters Susan, Kathy, Laura,
and Paula, and step mother, Nancy Lee, have all provided much needed
encouragement throughout this process as well. I am eternally grateful for, and blessed
by, your love and support.
To my friends and mentors, Cyndi Boyd, Kathy Kee, John Crain, Lee Alvoid, and
Sheila Maher – thank you for believing in me personally and professionally; I can never
thank you enough for your friendship and for all of the opportunities you provided for me
to grow as an educator. To my friends, Barry and Judy Dodson, Dawn and David
Thompson, and Corrie and Chris Edmondson - thank you for your encouragement
throughout this journey; your friendship means more to me than you’ll ever know! To my
colleagues in Denton ISD: Jamie Wilson, Robert Bostic, Vicki Sargent, Karen Jones,
Shannon Dion, and Tami Clary – thank you for understanding when I seemed
preoccupied and for “clearing the path” so I could focus on completing this work.
Finally, I would like to thank my professors, Dr. John Brooks, Dr. Linda
Stromberg, Dr. Mary Harris, and Dr. Jimmy Byrd for partnering with me on this learning
journey. You always knew when to challenge, support, and most importantly, inspire.
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TABLE OF CONTENTS
Page
ACKNOWLEDGEMENTS ............................................................................................... iii
LIST OF TABLES ............................................................................................................ vi
LIST OF FIGURES ......................................................................................................... vii
CHAPTER 1 INTRODUCTION ........................................................................................ 1
Background of the Study ......................................................................................... 1
Statement of the Problem ........................................................................................ 7
Purpose of the Study ............................................................................................... 9
Theoretical Framework .......................................................................................... 10
Research Questions .............................................................................................. 12
Significance of the Study ....................................................................................... 12
Delimitations and Limitations ................................................................................. 13
Assumptions .......................................................................................................... 13
Definition of Terms ................................................................................................. 14
CHAPTER 2 REVIEW OF LITERATURE ...................................................................... 16
Introduction ............................................................................................................ 16
Educational Policy Reform at the State and National Levels ................................. 16
Indicators of College Readiness ............................................................................ 27
Summary ............................................................................................................... 38
CHAPTER 3 METHODOLOGY ..................................................................................... 40
Introduction ............................................................................................................ 40
Research Design ................................................................................................... 40
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Participants ............................................................................................................ 41
Variables Examined ............................................................................................... 44
Instrumentation ...................................................................................................... 48
Summary ............................................................................................................... 52
CHAPTER 4 RESULTS ................................................................................................. 54
Introduction ............................................................................................................ 54
Descriptive Statistics .............................................................................................. 55
The Impact of Academic and Psychosocial Factors on College Persistence ......... 62
Conclusion ............................................................................................................. 70
CHAPTER 5 DISCUSSION ........................................................................................... 73
Introduction ............................................................................................................ 73
Statement of the Problem ...................................................................................... 73
Discussion of Results ............................................................................................ 74
Conclusion ............................................................................................................. 83
REFERENCES .............................................................................................................. 85
v
LIST OF TABLES
Page
1. Unemployment and Earnings Rates for People 25 Years and Older .................... 3
2. Summary of Federal Legislation Related to Enhancing College Readiness ....... 20
3. Summary of State of Texas Legislation Related to Enhancing College Readiness .......................................................................................................... 25
4. Engage Inventory Category Definitions and Sample Questions ......................... 34
5. Ethnicity and Gender Distribution of Study Participants ..................................... 41
6. Descriptive Statistics for Study Participants ....................................................... 43
7. Descriptive Statistics for Study Participants ....................................................... 44
8. Internal Consistency Reliability of the Engage Scales ........................................ 50
9. Percent of 4-Year College Students Accurately Identified as At-Risk ................. 51
10. Descriptive Statistics for Study Participants ....................................................... 55
11. Correlation Between Gender, Age, Ethnicity, Pell Grant Eligibility ...................... 57
12. Regression of Students ...................................................................................... 59
13. Regression of Students ...................................................................................... 61
14. Correlation Between Gender, Age, Ethnicity, Pell Grant Eligibility ...................... 63
15. Logistic Regression ............................................................................................ 66
16. Logistic Regression ............................................................................................ 69
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LIST OF FIGURES
Page
1. Unemployment and underemployment rates by educational level........................ 4
2. Real median weekly earnings for college graduates, 1979-2009 ......................... 5
3. Six year college level graduation rates at the state and national level in 2009 ..... 6
4. Four keys to college and career readiness ......................................................... 33
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CHAPTER 1
INTRODUCTION
Background of the Study
Throughout the last 40 years, the United States economy has transformed from
an economy based on the principles of manufacturing and production to an economy
based on knowledge, creativity, and innovation. “In 1950, a growing number of
Americans, approximately 50%, worked in manufacturing…and less than 10% worked
in the creative sector of the economy. In (the 25 year period between 1980 and 2005),
20 million new jobs were added in the creative sector of the economy” (Florida, 2006, ¶
3). Although some researchers and economists downplay the value of a college
education in this environment (Vedder, 2012) or advocate that the “…college education
bubble has burst” (Barone, 2013, ¶ 12), most argue that a college education is
imperative, and that increasing the number of citizens who earn a bachelor’s degree still
holds tremendous benefits for the individual and for the nation as a whole.
Human capital, developed as a result of a post high school education, forms the
foundation of the knowledge-based economy in the United States, and our nation is at
risk of not having enough:
America is slowly coming out of the Recession of 2007 - only to find itself on a collision course with the future. Not enough Americans are completing college … By 2018, we will need 22 million new workers with college degrees—but will fall short of that number by at least 3 million postsecondary degrees . . . At a time when every job is precious, this shortfall will mean lost economic opportunity for millions of American workers (Carnevale, Smith, & Strohl, 2010).
While the supply of educated workers is likely to fall short of demand, the demand
continues to rise as six out of every 10 jobs already requires at least some
postsecondary education and training. (Carnevale & Desrochers, 2003)
1
Opportunities for employment increase exponentially with a college degree. For
example, in 2010, one in three people in the United States with less than a high school
diploma was either unemployed or underemployed, and between 2007 and 2010, the
broader rate of unemployment and underemployment grew by more than ten
percentage points (nearly 5 million workers) for high school graduates, while growing by
less than 5 percentage points (2 million workers) for those with a college degree
(Greenstone & Looney, 2011).
A college degree positively impacts individual income as well. According to 2011
U.S. Bureau of Labor Statistics data and as shown in Table 1, college graduates in the
class of 2010 experienced a 5.4% unemployment rate and a mean income of $72,020,
compared to a 10.3% unemployment rate and a mean income of $39,988 for those with
only a high school education. Additionally, mean earnings for those holding a
professional degree reached $124,176, while mean earnings for those with some
college but no degree reached only as high as $46,228.
Researchers at the Brookings Institution Hamilton Project also analyzed the
impact of a college degree on lifetime earnings, or the sum of earnings over a career,
and found the total premium is $570,000 for a bachelor’s degree and $170,000 for an
associate’s degree (Owen & Sawhill, 2013).
2
Table 1
Unemployment and Earnings Rates for People 25 Years and Older
2010 Unemployment Rate Level of Education Completed 2010 Mean Earnings
14.9% Less than high school diploma $28,184
10.3% High school graduate, no college $39,988
9.2% Some college, no degree $46,228
7.0% Occupational program $46,332
7.0% Associate degree $49,764
5.4% Bachelor’s degree $72,020
4.0% Master’s degree $82,576
1.9% Doctoral degree $103,844
2.4% Professional degree $124,176
Note: From U.S. Bureau of Labor and Statistics, Current Population Survey, unpublished tables, 2011.
Given the current recovering status of the United States and global economies, for an
individual to have attained a post-secondary degree provides increased insulation
against the challenges faced by living in a recession driven unemployment. As shown in
Figure 1, the Hamilton Project at the Brookings Institution reported in 2010 that
unemployment/ underemployment rates for high school drop outs, graduates, and
college graduates peaked at 32%, 21,%, and 8% respectively (Greenstone & Looney,
2011).
3
Figure 1. Unemployment and underemployment rates by educational level.
Note. Adapted from “A broader look at the U.S. employment situation and the importance of a good education,” by M. Greenstone and A. Looney, February, 2011, Washington DC: Brookings Institution Press.
Furthermore, when reviewing the median weekly pay for different educational
attainment groups shown in Figure 2, it is clear that college graduates have not only
been less negatively impacted by the 2007 recession than members of other groups,
but their median earnings have begun trending in a positive direction to a greater
degree than the earnings of the members of other groups.
4
Figure 2. Real median weekly earnings for college graduates, 1979-2009.
Note. Adapted from The U.S. Bureau of Labor and Statistics as reported in “The Value of College,” by David Leonhardt, May 17, 2010, The New York Times.
Such an increase in this segment of the population, combined with expected increases
in college attendance by the over-25 age group, will only heighten the existing demand
and further emphasize the importance and value of a college education (National
Center for Education Statistics, 2011).
It is clear that an educated workforce holds a great deal of value and importance,
as the United States must compete internationally for economic stability. Higher
education has become a gatekeeper to future opportunity and financial independence
for each citizen. What is not clear is why there are not more high school graduates more
adequately prepared for success at the college level, and why do not more college
students, once admitted, achieve their goal of graduation? Greene and Forster (2003)
report that 32% of all high school graduates are actually prepared for college level work,
and in minority populations the numbers are even lower, with a 20% college
preparedness rate for African American students and a 16% rate for Hispanic students.
Low preparation rates continue to be a significant challenge for university
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administrators. However, they also face funding shortfalls as state leaders continue to
“redefine relationships by pressuring institutions to become more accountable, more
efficient, and more productive in the use of publicly generated resources” (Alexander,
2000, p. 411). Ultimately in this era of accountability, funding formulas for universities
are increasingly tied to their output rather than driven by needs of their input (Gilbert,
1999; Layzell, 1998). Thus, as more students arrive with even greater needs, and
pressure from political leaders continues to mount, university administrators must find a
way to increase their graduation rates, which as late as 2009 averaged 55.5% in the
United States, with a low of 26.9% and a high of 69.2% among the states (see Figure
3). As a result of such evidence, university leaders face a growing crisis every year
regarding the preparation and persistence of each freshman class of students they
consider for admission.
Figure 3. Six year college level graduation rates at the state and national level in 2009. Note. Adapted from, “Graduation Rate Survey,” 2010, National Center for Education Statistics.
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In order to address this crisis and ensure that more students are prepared for
college and motivated to persist toward graduation, educators at every level must
change how they prepare, evaluate, and support students toward a higher level of
college performance and persistence. Knowing the academic and psychosocial skills
that are most indicative of college success and retention is critical if educators are to
answer the charge of producing graduates who are prepared to compete on a national
and international scale.
Statement of the Problem
Developing a deeper understanding of the academic and psychosocial indicators
that best predict college achievement and persistence requires consideration not only of
those indicators that have traditionally been used but also those that more recent
research indicates are important. Traditional measures of academic proficiency such as
high school performance measured by class rank and American College Test/Scholastic
Aptitude Test (ACT/SAT) standardized test scores have been found to reliably predict
first year college Grade Point Average (GPA) (Noble & Sawyer, 2002; Geiser, 2008).
Non-traditional indicators of college readiness are also promising, as evidenced by both
practical experience and empirical research (Robbins, Lauver, Le, Davis, Langley, &
Carlstrom, 2004; DeBerard, Spielmans, & Julka, 2004; Kitsantis, Winsler, & Huie, 2008).
Whether referred to as attitudinal and behavioral skills, social skills, job search skills, or 21st Century skills, one thing is clear: our high-school, college, and workforce program graduates generally lack mastery of these skills. It is up to us, as educators, program administrators, and communities, to work together and assure all student and adult learners have a strong awareness of the soft skills they need to succeed in any endeavor (Dobyns, 2013, ¶10). Hiring managers already know the value of applicants with strong psychosocial
abilities and often go to great lengths to evaluate and select such candidates. Two key
7
findings from a 2013 survey conducted for the Association of American Colleges and
Universities reinforce this notion:
1. Ninety-three percent of the employers surveyed reported that strong
psychosocial skills such as a candidate’s demonstrated capacity to think
critically, communicate clearly, and solve complex problems, are more
important than the choice of an undergraduate major, and
2. Ninety-five percent of the employers surveyed reported that their companies
put a priority on hiring people with strong intellectual and interpersonal skills
(Hart, 2013).
University educators must also begin to emphasize psychosocial skill data when
selecting and supporting students because, while current research literature
acknowledges the value of traditional academic indicators such as an SAT or ACT
score or high school class rank (Conley, 2007), other studies indicate there is even
greater predictive power in the relationship between psychosocial skill development and
the attainment of a college degree. (Robbins, Lauver, Le, Davis, Langley, & Carlstrom,
2004). Understanding the importance of evaluating students’ psychosocial skill
attainment and using this information to select and support students is a critical action
step for university administrators (Le, Casillas, Robbins, & Langley, 2005; Hattie, Biggs,
& Purdie, 1996; Evans & Burck, 1992). Additionally, stronger college GPAs and greater
levels of persistence toward degree completion are increasingly being used by national
and state level leaders to evaluate the effectiveness of universities. Furthermore,
because every student is unique, there is not a one-size-fits-all formula for effectively
matching university level support programs with students’ needs. Knowing students’
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psychosocial strengths and weaknesses, as well as the predictive nature of these
attributes, can arm university leaders with important information, save students time and
money, and ultimately lead to greater economic prosperity as more citizens earn college
degrees.
The problem for this study, therefore, is to examine the predictive power of both
traditional (high school class rank and ACT/SAT scores) and non-traditional
(psychosocial skill) indicators of college readiness and persistence. Vroom’s (1964)
expectancy theory suggests there is a relationship between expectancy, instrumentality,
and valence, or as applied to this study, between psychosocial themes such as
motivation, social engagement and self-regulation, and the resulting outcomes of
academic performance and persistence in college. Understanding this relationship holds
great promise for both university leaders and their students. The Engage inventory from
ACT evaluates the presence of the following psychosocial skills: academic discipline,
general determination, goal-striving, commitment to college, communication skills, study
skills, social activity, social connection, academic self-confidence and steadiness, and
will be used to predict the academic success and persistence of first year college
students at a regional, public university in Texas.
Purpose of the Study
Despite the demand by business leaders that students graduate from college
equipped with well-developed psychosocial skills, and the abundance of research that
indicates psychosocial skills are a factor in university students’ success, most colleges
still rely on traditional predictors of success such as high school class rank, or ACT/SAT
scores when selecting students, or college course grades and college GPA when
9
designing academic support systems for them. Few high schools and colleges measure
students’ psychosocial aptitudes and use this information for the selection and support
processes. Therefore, the purpose of the current study is to apply Vroom’s theoretical
framework to determine if high school students’ levels of college readiness can be
better predicted by evaluating the same students’ high school class rank, ACT/SAT
scores, or their psychosocial skills. Student responses to the ACT Engage were used to
measure students’ psychosocial skill development according to ten constructs identified
by Robbins et al. (2004). This study includes analysis of traditional indicators of college
readiness and persistence (high school class rank and ACT/SAT composite scores) and
non-traditional indicators of readiness and persistence (Engage psychosocial
characteristics) for approximately 4,379 first year college students at a regional, public
university in Texas. The results of the study are intended to inform university leaders
regarding the need for selected support interventions for given classes of freshmen
students.
Theoretical Framework
The theoretical framework for this study is provided by the expectancy theory of
Vroom (1964). Expectancy theory is a cognitive process theory of motivation based on
the idea that people believe there are relationships between the effort they put forth at
work, the performance they achieve from that effort, and the rewards they receive from
their effort and performance. Vroom asserts that one’s behavior is based on individual
characteristics such as personality, skills, knowledge, experience and abilities, and
one’s motivation to complete a certain task is the product of the interactions of three
factors (Vroom, 1964):
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1. Expectancy - someone will be motivated to try a task to the degree he/she
believes that a particular level of performance is attainable
2. Instrumentality - the belief that if one does certain things, he/she will achieve
a certain outcome
3. Valence - the positive or negative value associated with one’s
attainment of a certain outcome
According to Vroom’s theory, students with a high degree of expectancy (they
believe they have the skill, resources, and support to be successful in college), a high
degree of instrumentality (they believe that if they perform well, they will receive a
desired outcome), and a positive valence (belief in the importance placed on the
expected outcome), are the same students who are best prepared to enter college and
persist through graduation. Specifically related to measuring college readiness and
persistence, there are psychosocial factors that influence college students’ behavior (as
measured by ACT’s Engage), and the motivation to successfully complete the first year
of college by earning a satisfactory GPA is a product of each student’s belief that such a
goal is:
1. Within reach and attainable (expectancy)
2. Achievable, based on specific actions to be taken by the student
(instrumentality)
3. Associated with a positive outcome valued by the student like an increase in
knowledge or lifetime earnings (valence).
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Research Questions
This study analyzed specific academic and psychosocial characteristics of 4,379
freshmen at a mid-size regional public university in Texas to answer the following
questions:
1. Does high school class rank, college entrance exam scores, or psychosocial
skills best predict student performance in the students’ first year of college
among freshman students in a selected Texas public university?
2. Does high school class rank, college entrance exam scores, or psychosocial
skills best predict student persistence to the second year of college among
freshman students in a selected Texas public university?
Significance of the Study
The significance of this study is three-fold: First, it is aligned with current
demands that more students graduate from high school ready for college by examining
academic and psychosocial skills believed to be accurate predictors of post-secondary
success. Second, it will provide university leaders with data that will show correlations
between traditional indicators of academic achievement and selected psychosocial skills
and academic performance and persistence at the college level. Finally, using this data,
university leaders will be able to:
1. More accurately identify and recruit incoming freshmen who are most likely to
demonstrate success and persistence in their coursework
2. Design effective support systems addressing specific psychosocial needs for
everyone else
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Delimitations and Limitations
A delimitation of this study is that I examined existing data. Greater control over
the collection of data could be retained were the inventory to be administered by the
researcher as part of this study. Another delimitation is that the study only includes
students at one Texas university. The collection of data at more than one university
would not only increase the sample size, but would also provide important results with
direct applicability to students at other universities where the admissions processes
and the capacity for academic support might be different. Despite these delimitations
however, it is important to note that the sample included in this study surpasses the
requirements for generalizability because of its size and heterogeneity, and it is, in fact,
significantly larger than the sample sizes included in other related studies (Allen, 2009;
Gore, 2006).
One limitation of this study is that I had no direct control over the administration
of the Engage. While the conclusions based on students’ responses on this instrument
are presumed to be valid because there is an extensive research base supporting the
use of the Engage (see Chapter 4), one must still recognize the fact that conclusions of
correlation are ultimately dependent on the accurate administration of the instrument,
which is one part of the research design that is beyond the control of the researcher.
Assumptions
An assumption of mine is that the participants in the study answered the Engage
questions truthfully and accurately. More specifically, it is assumed that the participants
had a thorough understanding of the evaluation instrument and the capability to
accurately self-evaluate the degree to which they exhibit specific psychosocial
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characteristics. Furthermore, it is assumed that the Engage was administered according
to its validated protocol. A final assumption of this study is that once the factors that
might limit students’ success or persistence with college level work have been identified,
a successful support plan can also be developed that will counteract those limiting
factors.
Definition of Terms
Many terms that are part of this study require a common understanding between
the reader and me. Those terms are listed below and have been taken from the Engage
(ACT, 2006).
• Academic discipline: The amount of effort students put into their schoolwork
and the degree to which they see themselves as hardworking and
conscientious
• Academic self-confidence: The extent to which students are confident they
can perform well in school
• Commitment to college: The extent to which students appreciate the values of
education and are committed to staying in college and attaining a degree
• Communication skills: The extent to which students are attentive to others’
feelings and flexible in resolving conflicts with others
• General determination: The extent to which students strive to follow through
on commitments and obligations
• Goal striving: The strength of students’ efforts to set and achieve important
goals
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• Social activity: The extent to which students are comfortable meeting and
interacting with other people
• Social connection: The extent to which students feel connected to and
involved with the college/school community.
• Steadiness: The measure of how students handle strong feelings and keep
emotions from negatively impacting other activities
• Study skills: The extent to which students believe they know how to assess
an academic problem, organize a solution, and successfully complete
academic assignments
Additional terms referenced in the study that may need clarification include:
• College readiness: The attainment of academic and psychosocial skill
proficiency to the degree that a student may enroll and succeed in, without
remediation, credit bearing core courses at the university level
• Academic success: Completing credit bearing core courses at the college
level and earning at least a 2.5 GPA in those courses
• Persistence: Advancing toward the goal of earning a degree by enrolling in
the second year of college after completing courses in the freshman year
Understanding these terms and the context within which they are used provides the
reader with a clearer understanding of the scope of the study.
15
CHAPTER 2
REVIEW OF LITERATURE
Introduction
Understanding which indicators are most predictive of a student’s success in
college provides useful information to a number of stakeholders in the high school-to-
college matriculation process. Parents and K-12 school leaders can know where to
place their energy when modeling and teaching attributes linked to college success.
University leaders can know which students are motivated to progress with little need
for help and which will need more assistance. College admissions directors can make
better placement decisions, and assistance counselors and professors can quickly
provide struggling students with appropriate guidance. Most importantly, students can
gain insight into their existing psychosocial habits in order to make changes and
positively impact their likelihood of personal and professional success. Because of the
significance of this topic, the review of literature regarding indicators of college
readiness and persistence includes an analysis of:
1. The evolution of changes in state and national policies designed to
emphasize high school graduates’ readiness for college
2. The academic research focused on the predictive nature of traditional and
non-traditional indicators of college readiness
3. The ACT Engage as a measure of psychosocial skill development
Educational Policy Reform at the State and National Levels
Calls for reforms to our educational system are not new; in fact, they continue to
increase in number and intensity (Carnoy, 1999). “The body of educational change
16
knowledge that forms the technical foundation of reforms underway in practically all
education systems has significantly expanded during the last three decades” (Sahlberg,
2006). Such reforms have occurred for many reasons, chief among them the desire to
improve outcomes for the nation’s K-12 educational systems. The call for reform
however, has not garnered unanimous support. Some researchers believe reform is
unnecessary and that calls for education change have resulted from myths perpetuated
on the American people (Berliner & Biddle, 1995). “School-bashing has been a popular
indoor sport in America for years, and White House critics of the schools would not have
gotten away with the lies and distortions of evidence they promoted, had Americans not
also been worried about unresolved problems in our society and its public schools, and
had their efforts not been supported by industrial pronouncements and media
irresponsibility” (Berliner & Biddle, 1996, p. 4).
Despite gaining some traction as an opposing view, Berliner and Biddle’s
assertions remain a minority voice in the reform debate. Evidence continues to indicate
that high school academic experiences do not lead to high levels of readiness for, nor
persistence in, college level work. In surveys administered by Achieve, Inc. (2009), a
non-partisan think tank established by the nation’s governors, 39% of the respondents
who attended college after graduation said there were gaps in their high school
preparation compared to the expectations actually experienced in college. Moreover,
even among those who reported feeling extremely well prepared for college, 31% took
at least one remedial college course. Additionally, among college professors responding
to the same survey, a similarly damaging assessment emerged: Instructors estimated
half of all students who arrived at their schools were inadequately prepared for college-
17
level math and college-level writing. In addition, large percentages of instructors felt the
public high schools were failing to adequately develop students’ abilities to do such
things as read and comprehend complex materials (70%), think analytically (66%), and
do research (59%) (Achieve, Inc., 2009). Further, ACT researchers determined that
across the United States, even when controlled for gender, race/ethnicity, and family
income, the inconsistencies in the types of courses that students were allowed to select
to fulfill high school graduation requirements continued to result in readiness and
persistence-related consequences (ACT, 2008a):
1. Students who do not take a core curriculum in high school are more
likely to need remediation in English or math than students who do
2. Students who do not take higher level English courses and a foreign
language are more likely to need remediation than those who do
3. Students who do not take higher level math or science courses in
high school are more likely to not be successful in first-year subjects
in college
It is clear that rigorous college preparatory course sequences in English, math
and science are critical to preparing students for post-secondary work (ACT, 2005).
How to achieve this goal and who is specifically responsible for leading the charge has
been a focus of political leaders for the past 30 years.
Policy Reform Phase I: Increased High School Graduation Requirements
Since 1983 with the publication of A Nation at Risk, the federal government has
approved legislation designed to improve high school graduation rates and students’
18
level of preparation for college level courses (see Table 2). Many national, state, and
independent research efforts have focused on the, “…widespread public perception that
something is seriously remiss in our educational system." (National Commission on
Excellence in Education, 1983). Criticisms of the K-12 education system leveled in this
seminal report included the following:
1. High school curricula (have) no central purpose and can be described as
"cafeteria-style," where "appetizers and desserts can easily be mistaken for
the main courses"
2. Few students take challenging courses
3. Expectations for students, as expressed by state requirements for
graduation, are uniformly low
4. One-fifth of public 4-year colleges have to accept every high school graduate
in their home state regardless of grades or program taken
A Nation at Risk called for many different academic reforms including a
significant increase to the number of course credits needed to graduate and a
requirement that all students complete four years of English and three each of math,
science, and social studies. As a result, between 1982 and 2012, the percentage of high
school graduates meeting ever increasing academic requirements continued to rise.
However, increases in college level achievement or persistence were not realized. In
2001, the nation’s high school graduation rate measured 71.7%, while the percentage of
college ready graduates ranged regionally between 29% and 41% (Greene & Forster,
September, 2003). In 2010, the nation’s overall high school graduation rate had risen to
78.2%, according to the annual Building a Grad Nation report. However, college ready
19
percentages remained unchanged with nearly 60% of admitted freshmen unable to
enroll in college level courses (National Center for Public Policy and Higher Education,
2010). Although high school graduation rates have risen, producing students who are
ready to enroll in college level coursework continues to be a challenge for the nation’s
high schools.
Table 2 Summary of Federal Legislation Related to Enhancing College Readiness of Public School Students in the United States, 1999-2002
Federal Legislation
Year Passed
Summary of Key Points
PL 101-589 1999 The Excellence in Mathematics, Science and Engineering Education Act of 1990 was intended to promote excellence in American mathematics, science, and engineering education by creating a national mathematics and science clearinghouse, and creating several other mathematics, science, and engineering education programs.
PL 103-227 1994 The Goals 2000: Educate America Act established a new federal partnership through a system of grants to states and local communities to reform the nation’s education system. The Act established the National Education Goals Panel. It also created a National Education Standards and Improvement Council (NESIC) to provide voluntary national certification of state and local education standards and assessments and established the National Skill Standards Board to develop voluntary national skill standards.
PL 107-110 2001 The No Child Left Behind Act of 2001 provided for the comprehensive reauthorization of the Elementary and Secondary Education Act of 1965, incorporating specific proposals in such areas as testing, accountability, parental choice, and early reading.
Source: United States Department of Education. Retrieved from: http://www2.ed.gov/policy/gen/leg/edpicks.jhtml Policy Reform Phase II: Focus on International Comparisons
Just three years after A Nation at Risk recommended sweeping changes to
graduation requirements and college preparation, another report, A Time for Results,
20
raised academic performance standards by establishing the international stage as the
preferred benchmark for the nation’s academic achievement. This shift in comparing
American students’ academic progress with that of students in other countries continues
to influence educational reform efforts today (Bugas, Kalbas, Rotman, Troute, & Vang,
2012). International comparisons of student achievement caused United States
governors to meet twice in the late 1980s and early 1990s to set national education
goals in an effort to create more accomplished high school graduates and better
prepared college students. Each of these meetings resulted in publication of documents
intended to influence public policy and educational practice. Emphasis was placed on
improving the academic challenge of the coursework required for a high school diploma,
increasing high school graduation rates, and improving instruction in math and science
courses so that United States’ students would score first in international assessments.
(Vinovskis, 1999). Driven by the understanding that academic intensity and the quality
of one’s high school curriculum best predict college graduation (Adelman, 2006), the
governors’ work continued in two more national education summits held later in the
1990s. Emphasis on reforms designed to increase international competitiveness has not
produced the intended results either, however. According to a recent report from the
College Board, when compared to other industrialized nations, the United States has
fallen from first to twelfth in the share of adults’ ages 25 to 34 with postsecondary
degrees (Lee & Rawls, 2010), and nearly half of all college students do not complete their
degrees within six years (Symonds, Schwartz, & Ferguson, 2011).
The inability of United States students to keep pace with the academic
performance of students from other countries continued the call for education reform
21
and resulted in increased scrutiny of prior legislation. “Given its scope and detail, the
No Child Left Behind Act (NCLB) was the source of considerable controversy in the
education community. As the law’s effects began to be felt, some educators and
policymakers questioned the feasibility and fairness of its goals and time frames”
(Education Week, 2011). Farkas, Johnson and Duffet (2003) report that nearly half of
the school principals and superintendents surveyed viewed the federal legislation as
either politically motivated or aimed at undermining public schools. Further, a 2011
study published by the RAND Corporation suggests that, because of its limited focus on
a small subset of school outcomes (primarily reading and math achievement), NCLB
measurements may not reveal a true and complete picture of a school’s effectiveness
(Schwartz, Hamilton, Stecher, & Steele, 2011).
Despite the continued legislative action and the bipartisan reauthorization of the
Elementary and Secondary Education Act in 1991 and 2001, academic reforms at the
secondary level have yet to produce students who are significantly better prepared or
who persist in their studies through graduation from college (National Center for Public
Policy and Higher Education, 2010). The disconnection between increased academic
standards and high school students’ levels of performance continues to have
ramifications at the K-12 and college levels. According to Cohen, Lingenfelter, Meredith,
and Ward (2006), despite the instruction, testing, and accountability systems that currently
drive instruction in US elementary and high schools, there still exists the reality that in every
state today, students can demonstrate the proficiencies required and graduate non-college
ready. Some researchers attribute this phenomenon to the fact that throughout the last 30
years and despite increased graduation requirements, state and national reforms have
22
remained focused on building a strong foundation for learning in the early grades rather
than on guarantying that high school graduates are exposed to a college preparatory
education (Achieve, Inc., 2009; Barone, 2013). “One of the most unrelenting challenges
(still) facing higher education is the large number of students in need of remediation –
the formal coursework in reading, writing, and mathematics, and the academic support
services provided to students who need help in meeting academic requirements”
(Greene as reported in Mason, 2009).
Policy Reform Phase III: Alignment of K-12 and College Standards
Increases in the numbers of high school students adequately prepared for
college level work cannot accurately be predicted by the courses chosen in high school,
nor influenced by challenges presented by comparisons to student performance in other
countries. Multiple sources indicate that the alignment between K-12 and higher
education curricula is an influence, however. Active partnerships between high school
and university educators are necessary for the development of the common
understandings and expectations that lead to increased student achievement: “It is clear
that college readiness partnerships create opportunities for secondary and post-
secondary institutions to leverage each other’s services…aligning programming to
maximize gains for students” (Barnett, Corrin, Nakanishi, Bork, Mitchell, & Sepanik,
2012). Increased collaboration between K-16 educators also improves everyone’s
awareness of curricular standards and the types of the assessments used at each level,
increasing the likelihood that high school students are prepared for college and
decreasing the need for remedial courses at the college level (US Department of
Education, 2006).
23
Recognizing the importance of increased collaboration and improved high
school-college alignment, many states began to enact legislation in the early 2000s
requiring the development of more challenging and better aligned high school courses.
Partnerships between public school and university leaders were also emphasized. For
example, in Texas, the 79th legislature passed House Bill 1 (HB1), directing the Texas
Higher Education Coordinating Board and the Texas Education Agency to appoint
vertical teams of public school and higher education leaders with the charge to:
1. Recommend college readiness standards
2. Evaluate the college preparatory nature of existing high school curricular
requirements
3. Recommend steps for aligning college readiness standards and public school
curricular requirements in each of the core content areas
Under the same legislation, Texas public school districts and higher education
institutions were also required to create college credit programs to allow high school
students to earn at least 12 college credits as further evidence of students’ increased
readiness for full time enrollment.
Since the early 2000s, the Texas legislature passed a number of other bills
designed to reinforce the importance of public education and university partnerships
and provide a framework for statewide policy development supporting increased levels
of college readiness, (see Table 3). HB 3, enacted by the 81st legislature in 2009, called
for an increase in the rigor and relevance of state instructional standards and
assessments, and created new college and career readiness standards as well.
Additionally, HB 3 established, “one of the most aggressive, and important, education
24
goals for the state - by the 2019–2020 school year, Texas (will) become one of the top
10 states for graduating college-ready students” (Texas Education Agency, 2012, ¶ 7).
SB 286 established the state P-16 Council as an advisory group for coordinating the
goals of five state agencies with the daily work of education professionals, business
members and community leaders. Charged with, “developing and strengthening
partnerships and relationships among public education, higher education, and the civic
and business communities” (Texas Education Agency, 2012, ¶ 1), state and regional P-
16 councils promote a college going culture within the public schools, conduct research
and evaluate instructional and intervention efforts, and reinforce increased high school
and college level instructional alignment through grass roots efforts.
Table 3
Summary of State of Texas Legislation Related to Enhancing College Readiness of Public School Students in Texas
Texas Legislation
Year Passed
Summary of Key Points
HB400 2001 Planned to increase enrollment in the state’s institutions of higher education, HB400 requires school districts with one or more high schools ranked among the bottom 10% in percentage of college-bound graduates for two consecutive years in a preceding five-year period and the colleges or universities nearest to those districts to develop plans to increase college enrollment among the graduates in those districts.
SB286 2003 Established the state P-16 council as an advisory group for coordinating the work of five state agencies with the daily work of education professionals, business members and community leaders. P-16 councils were established at the state and regional levels for the purpose of strengthening and supporting partnerships between the state’s secondary schools and colleges.
HB1 2006 Established a wide-ranging foundation for addressing college readiness through higher standards, assessments, curriculum, professional development, and accountability. This bill required vertical teams of high school and college faculty, appointed by the Commissioners of Education and Higher Education, to develop college-readiness content standards for English language arts, mathematics, science, and social studies.
table continues
25
Table 3 continued. Texas
Legislation
Year Passed
Summary of Key Points
SB282 2007 Amended the Texas education code to require each school district annually to notify the parent of each district student in grade nine or above of the availability of programs in the district that allow a student to earn college credit, including advanced placement, dual credit, joint high school and college credit, and international baccalaureate programs.
HB2237 2007 Provided the basis for increased funding for dropout prevention and college- and career-readiness programs and authorized a number of new initiatives designed to connect students who have traditionally been under-represented in higher education, at-risk students, and previous dropouts.
HB2237 SB1031
2007 Authorized the creation of 12th-grade transitional courses for students
HB3826 2007 Amended the Texas education code to require an applicant for admission to a public college or university to have completed the recommended or advanced high school program at a public high school or to have met the applicable ACT’s College Readiness Benchmark on the ACT or earned a score of at least 1,500 on the SAT or its equivalent.
HB3 2009 Extended and revised earlier college-readiness legislation to include the following:
1. Development of end-of-course exams that embed the college-readiness content standards;
2. Creation of a link between college-readiness cut scores on Algebra II and English III and advanced cut scores in earlier grades to indicate individual students’ progress toward college readiness; and
3. Established a statewide school accountability system that measures school progress in improving the extent to which students are meeting the college-readiness standards by the 11th grade.
Source: Southern Regional Education Board (2014). Retrieved from: http://www.sreb.org/page/1516/college_and_career_readiness_in_texas.html
Policy Reform Phase IV: Establishing National Standards
As a result of the focus placed on the importance of college readiness by state
leaders and local groups such as the P-16 councils in Texas, policy leaders at the
federal level have also sought to identify solutions to the nation’s college readiness and
persistence challenges. A growing consensus among political and business leaders has
emerged, calling for the establishment of national education standards in an effort to
produce improvements in high school achievement and college readiness. Many state
governments joined together, and in 2010, the National Governors Association Center
26
for Best Practice (NGA Center) and the Council of Chief State School Officers (CSSO)
released a set of education standards known as the Common Core State Standards
(CCSS), designed to strengthen individual states’ efforts to better prepare students for
college by increasing the level of academic rigor required in high school courses
(Pascopella, 2010). As of 2012, 45 states, the District of Columbia, four U. S. territories,
and the Department of Defense Activity have adopted the CCSS. Although the state of
Texas, the location of the university included in this study, has not joined the CCSS
movement, there is evidence that Texas’ standards in English/language arts and
mathematics are similar in scope and cognitive complexity to the national standards
(Conley, Drummond, de Gonzales, Seburn, Stout, & Rooseboom, 2011). The Common
Core Curriculum, whose potential to raise the quality and intensity of academic
standards across the nation is yet unknown, is the most recent result of the reformers’
work to improve students’ academic readiness for college level work. \
Indicators of College Readiness
College admissions officers often depend on evaluations of students’ college
entrance exams, high school coursework, and high school class rank, as objective data
sources to determine whether a student is college ready. A review of research indicates
the value of these indicators is mixed, however, and while they may be useful, they do
not provide the comprehensive level of information necessary for university leaders to
make the most informed decisions. Non-traditional indicators of students’ psychosocial
skill development however, do provide value-added information about a student’s
likelihood of succeeding and persisting toward college graduation, and this information
cannot be measured by high school coursework, GPA, or nationally standardized
27
achievement tests.
Traditional Indicators of College Readiness
College readiness has traditionally been defined by concrete evidence of
academic achievement such as the titles of high school courses taken, scores in high
school courses as reflected in students’ class rank, and high levels of achievement on
high school exit exams and college entrance exams. There are many difficulties
inherent in using these traditional criteria as the sole indicators of college readiness,
however. First, using course titles and types of courses taken in high school to
determine readiness for college level work assumes there is some degree of correlation
between the skills needed to succeed in a high school course and in a college course.
Wagner (2006) asserts that the only conclusion that can really be drawn from course
title analyses is that there is a “…(mis)alignment between what is required to get into
college and what is needed to stay in college and succeed as an adult,” (Wagner, 2006,
¶ 10). Second, despite some research findings that indicate the high school class rank
is consistently the best predictor of first year college achievement, persistence, and
overall college performance (Larson and Scontrino, 1976; McDonald & Gawkowski,
1976; Ting 2000; Geiser & Santelices, 2007), there is additional evidence showing that
unreliability in the use of high school grade point averages exists because of a lack of
national standardization around the meaning of grade point average (GPA). For
example, the use of the high school GPA and class rank can be called into question
when the highest ranking high school graduates enroll in college and need remedial
courses (Conley, 2010). Additionally, the predictive ability of high school GPA is
28
compromised by the many different methods used for weighting individual courses.
Many schools adhere to weighted GPA scales that reach as high as 5, 6, or 10 and
offer extra grade points for more rigorous courses, while others do not offer any
additional numerical credit for such courses. The National Assessment of Educational
Progress (Conley, 2007; National Statistics for Educational Statistics (NCES, 2007)
conducted a high school transcript study in 2005, analyzing course titles and student
GPAs, and found students to be more prepared for college in 2005 than in 1990, but
cautioned that the findings could be limited because of grade inflation and the
variations in grading standards across schools. Because of the lack of a national
standard and the disparity that exists among high schools across the United States,
colleges that set a specific GPA for determining students’ readiness run the risk of
admitting students who may not be ready while turning away more successful and
better prepared students. Third, while high stakes tests mandated by the NCLB Act
may be perfect indicators of mastery of specific knowledge and skills required by high
school courses, they are not reliable indicators of readiness because there is no
correlation between mastery scores on these tests and an acquisition of the skills and
knowledge required for college level success (Conley, 2003). Therefore, large numbers
of students may be left with a false sense of preparedness based on their high stakes
test results, and some colleges may accept students based on their official high school
transcripts, only to find after the first semester or year of college that the students are
not actually prepared for post-secondary success (National Center for Public Policy and
Higher Education, 2010). SAT/ACT scores maintain the highest level of predictability of
a student’s college GPA (Willingham, 2013). In their meta-analysis of hundreds of
29
studies and 241 data sets published between 1997 and 2010, Richardson, Abraham, &
Bond (2012) found the SAT/ACT scores to be among the strongest predictors of
college GPA with an r value of .40.
Non-Traditional Indicators of College Readiness
Precollege academic preparation and standardized test scores provide an
incomplete understanding of one’s degree of readiness for college level work. Every
year, thousands of high school students continue to matriculate into American colleges,
not only unable to perform academically, but also unclear about the time, energy, and
degree of self-direction that is required for success (McCabe, 2000). If traditional
indicators cannot be relied on to be the most accurate and comprehensive predictors of
college success, what should be used in their place? Literature findings suggest that
non-academic factors strongly contribute to a student’s academic achievement and
persistence. (Tinto & Pusser, 2006; Pascarella & Terenzini, 2005). Recently, when
identifying attributes of students who were college ready, university instructors began
placing greater emphasis on key cognitive strategies, specific types of content
knowledge, contextual knowledge, and behavioral attributes that are commonly found in
successful college students (Conley, 2007).
An agreement on the definition of college readiness is not easily reached,
although it is critical to understanding the power of non-traditional indicators like
psychosocial skills. “The ability to do credit-bearing work in the most accessible higher
education institutions on the day you enroll…” is the definition for college readiness
advocated by Patrick Callan from the National Center for Public Policy and Higher
30
Education (Callan, as reported by Olson, 2006, ¶ 38). Meanwhile, the definition
espoused by Mary Catherine Swanson, founder of Advancement via Individual
Determination (AVID) includes the, “study and resiliency skills necessary to succeed”
(Swanson, as reported by Olson, 2006, ¶ 40). Many researchers refer to college
readiness as the mastery of “the knowledge and skills necessary to succeed, without
the need for remediation, in entry-level college courses offered at a post-secondary
institution,” (Achieve Inc., 2009; ACT, 2009; Bill & Melinda Gates Foundation (BMGF),
2009; College Board, 2008; Texas Higher Education Coordinating Board (THECB),
2008; Texas Education Agency (TEA), 2007). David Conley, founder of the Educational
Policy Improvement Center (EPIC) uses both empirical evidence and practical
experience to deepen this understanding by keeping it multi-dimensional, inclusive of
multiple data, and indicative of students’ mastery of both academic content and
psychosocial skills. His definition deemphasizes indices or “cut scores” that use a single
score alone or in combination with another element, such as high school grade point
average, to predict college success (Conley, 2012). Conley’s definition requires
individualization of assessments and evaluates students’ knowledge and skills as well
as their aspirations and motivation; actions that cannot be accomplished through one
standardized measurement. Conley establishes “college ready” as the ability to, “qualify
for and succeed in entry-level, credit bearing college courses leading to a
baccalaureate, without the need for remedial or developmental coursework” (Conley,
2010, p. 27).
According to Conley (2012) and as shown in Figure 4, measuring a student’s
degree of college readiness relies on determining his or her level of mastery of four
31
keys to learning:
1. Cognitive strategies – the ways of thinking that are necessary for college
success. They include formulating hypotheses and developing problem
solving strategies, analyzing and evaluating findings or conflicting viewpoints,
and monitoring the accuracy and precision of all work produced.
2. Content knowledge – the important foundational content and big ideas from
core subjects that all students must know well and an understanding of the
structure of knowledge in core subject areas. Also included are the technical
knowledge and skills associated with career aspirations, the perceived value
of lesson content, and the effort (students) are willing to expend to master the
content.
3. Transition knowledge and skills – describe one’s understanding of, and ability
to, navigate the unwritten rules of college: knowing which high school courses
to take in preparation for college, understanding college-level norms and
expectations, and learning how to be a self-advocate within the policies and
procedures of a college environment.
4. Learning skills and techniques – broadly include student ownership of
learning and learning techniques that enable mastery of learning, and
specifically include goal setting, persistence, self-efficacy, motivation, time
management, study skills, and strategic reading.
32
Figure 4. Four keys to college and career readiness.
Note. From Conley, D. (2012). College and career readiness: equipping students with the four keys. Educational Policy Improvement Center. Retrieved from: http://epiconline.org/Issues/college-career-readiness/the-colution/
Conley’s learning skills and techniques include, “acquiring and effectively
applying the knowledge, attitudes and skills, to understand and manage emotions, set
and achieve positive goals, feel and show empathy for others, establish and maintain
positive relationships, and make responsible decisions” (Weissberg & Cascarino,
2013a, 2013b). These behaviors are critical to developing a positive mindset, believing
in one’s ability to set and tackle new and challenging goals such as attending college,
and one’s degree of hope for the future, a positive predictor of future success (Dweck,
2006; Lopez, 2013). Additional skills like self-management, social awareness, the
combination of communication, cooperation and negotiation abilities, and ethical
behavior that leads to responsible decision making are also components of the 21st
century skills framework necessary for success in today’s world (Partnership for 21st
Century Skills, 2011). Although critically important to post-secondary success, these
33
skills are often thought of as soft, and are not explicitly taught to students. Instead of
minimizing the importance of these skills, school leaders should actively seek
opportunities to teach students to develop and self-monitor them to their maximum
potential. The ACT Engage holds potential as a tool for both K-12 educators and
university leaders in understanding the relationship between psychosocial skills and
college readiness and persistence.
ACT Engage
Designed as a measure of psychosocial factors that are indicative of academic
success and persistence, the ACT Engage, formerly known as the Student Readiness
Inventory or SRI, is composed of 108 items organized in 10 categories: academic
discipline, academic self-confidence, commitment to college, communication skills,
steadiness (emotional control), general determination, goal striving, social activity,
social connection, and study skills (ACT, 2008b). Table 4 provides sample test items for
each of the Engage categories.
Table 4
Engage Inventory Category Definitions and Sample Questions
Category Definition Sample Item
Academic Discipline
Reflects the amount of effort a student puts into schoolwork and the degree to which he sees himself or herself as hardworking and conscientious
“I turn in my assignments on time.”
Academic Self-Confidence
Reflects the extent to which a student believe he or she can perform well in college
“I am a fast learner.” Table continues
34
Table 4 continued.
Category Definition Sample Item
Commitment to College
Reflects a student’s commitment to staying in college and getting a degree
“I am motivated to get a college degree.”
Communication Skills
Reflects how attentive a student is to others’ feelings and how flexible he or she is in resolving conflicts with others
“In reaching an agreement, I consider the needs of others as well as my own.”
Steadiness Reflects how a student responds to strong feelings and how he or she manages those feelings
“I’m a patient person.”
General Determination
Reflects the extent to which a student strives to follow through on commitments and obligations
“When I make plans, I follow through with them.”
Goal Striving Reflects the strength of a student’s effort to achieve objectives and end goals
“Once I set a goal, I do my best to achieve it.”
Social Activity Reflects how comfortable a student feels meeting and interacting with other people
“I find it hard to talk to people I don’t know well.”
Social Connection Reflects a student’s feelings of connection and involvement with the college or school community
“I have a sense of belonging while I’m on campus.”
Study Skills Reflects the extent to which a student believes he or she knows how to assess an academic problem, organize a solution, and successfully complete academic assignments
“I highlight key points when I read assigned materials.”
Note. From Le, Casillas, Robbins, & Langley, 2005; ACT, 2006
The Engage was created as a result of the analysis of research indicating the
existence of psychosocial factors that may influence college readiness and success
(Pascarella & Terenzini, 1991; Tinto, 1975, 1993, Robbins, Lauver, Le, Davis, Langley,
& Carlstrom, 2004), and the fact that prior work resulted in a diversity of constructs and
lack of an integrative framework, (limiting) the development of a multidimensional
35
inventory with strong psychometric and conceptual underpinnings (Le, Casillas,
Robbins, & Langley, 2005).
The Engage, originally developed as the Student Readiness Inventory, resulted
from a meta-analysis of 109 existing educational and psychological studies and initially
categorized psychosocial and study skill factors into nine broad constructs related to the
identification of at risk students. In this study, Tinto’s student integration theory (Tinto,
1975, 1993), and Bean’s student attrition model (Bean, 1985) provided the theoretical
framework related to persistence. Reviews of motivational literature by Covington
(2000) and Eccles and Wigfield (2002), indicated the importance of the theories of self-
regulation and expectancy values to the concept of motivation: “the quality of student
learning as well as the will to continue learning depends closely on the interaction
between the kinds of social and academic goals students bring to the classroom, the
motivating properties of these goals, and prevailing classroom reward structures”
(Covington, 2000, p. 171). The Engage measures motivation principally through the
scale of Academic Discipline. Because of the strong link in the literature between
motivation and students’ likelihood of achieving academically and persisting to the
following year of study, measures of academic discipline would be expected to provide
insight into the likelihood of students achieving and persisting. “Perhaps more than any
other trait, Academic Discipline is essential for both academic performance and
retention. Students demonstrating high levels of Academic Discipline place great value
on their schoolwork and will make academic tasks and assignments a high priority. In
contrast, low scoring students (who lack motivation) may avoid their schoolwork, cut
classes, and view other elements of their lives as more important than the completion of
36
school-related tasks” (ACT, 2008b).
Building on the meta-analysis of existing literature conducted by Robbins et al.
(2004), ACT researchers led by Le added to the knowledge base by examining existing
and emerging personality and industrial-psychology literature. From their additional
work, Le et al. (2005) identified three content domains and an additional construct that
would provide the conceptual framework for the SRI development: motivation
(conscientiousness, goal focus, and academic self-efficacy), academic related skills
(academic skills, problem solving skills, communication skills, and emotional control
skills), and social engagement (sociability, social correction, and teamwork) (Le et al.,
2005). Teams of applied psychologists and writers then worked together and
independently to create an initial pool of 320 test items. This pool of items was
administered to a small group of high school seniors for clarity and understanding,
revised, and again rated by education and communication experts for further analysis
and revision. After further editing, the final pool of test items was narrowed to 305.
Next, an item selection study was conducted involving 5,970 high school seniors
and first year students from 2-year and 4-year colleges and universities across the
United States, but primarily located in the Midwest, South, Southeast and Southwest.
ACT researchers conducted both exploratory and confirmatory factor analyses and
narrowed the test item bank to approximately 100 items, with 10 questions measuring
each of the 10 selected constructs (Le et al., 2005). Scale validation and reliability were
calculated using SRI results from both the development (N = 5,970) and validity (N =
14,464) samples. ACT recruited 14,464 incoming freshmen from 2-year and 4-year
universities representative of a variety of geographic, demographic, and selectivity
37
factors to participate in this study. Results indicate that the scales demonstrated,
“…moderate to high internal consistency reliabilities (with a Cronbach’s coefficient)
alpha range = .80 to .87” (ACT, 2006).
Summary
High school class rank and scores on standardized admission tests have long
been used as key gatekeepers when considering students’ applications to college. Such
indicators have been adequate for predicting success at the college level as long as our
understanding of college readiness remained one-dimensional and focused only on the
attainment of academic skills. However, because the definition of college readiness now
includes both academic and psychosocial aptitude, university leaders must expand the
criteria used for selecting students and must seek ways to use this broader definition to
support students throughout their university experiences. Traditional indicators of
college readiness provide a limited understanding of students’ strengths and offer
virtually no indication of students’ motivation or likelihood of persistence when
navigating the challenges of a university education. Measuring students’
psychosocial skills and understanding the predictive nature of those skills are key
components of the new process for identifying college ready students (Le et al., 2005).
While there is an abundance of research examining the predictive ability of students’
high school courses, high school class rank, and standardized test scores on their
likelihood of year first success at the college level, few studies examine the predictive
nature of psychosocial skills and their relationship to first year college success and
persistence toward degree completion. Further, “little work has been devoted to the
development of a model of student persistence that would provide guidelines to
38
institutions for creating policies, practices, and programs to enhance student
success….a significant gap remains between what researchers know about the nature
of student retention and what practitioners need to know to enhance student retention”
(Tinto, as reported in Seidman, 2005). Therefore, the purpose of this study is to apply
Vroom’s theoretical framework to determine if high school students’ level of college
readiness can be better predicted by evaluating the same students’ high school class
rank, ACT/SAT scores, or their psychosocial skills. Results of this study are intended to
provide university leaders with important knowledge related to the selection and support
of students who will achieve success in and graduate from college.
39
CHAPTER 3
METHODOLOGY
Introduction
Understanding the relationship between college readiness predictor variables
and students’ actual results, as measured by their first year GPA and rate of enrollment
in the second year of courses, is vital for those involved in preparing, selecting, and
teaching college level students. The review of existing literature reveals the predictive
power of traditional academic indicators such as an ACT/SAT score and high school
class rank. However, the literature also supports further study regarding the predictive
power of psychosocial indicators. There is an increased emphasis in current literature
on the belief that college readiness is not simply a function of academic knowledge
acquisition, but rather includes the mastery of academic knowledge and psychosocial
skills such as perseverance, motivation and self-efficacy.
Research Design
This quasi experimental study utilized linear and logistic regression models to
examine the effect of traditional college readiness predictors such as high school class
rank (HS Rank) and college admission exam scores (ACT and SAT), and psychosocial
factors measured by the ACT Engage, on participants’ first semester college GPA and
persistence to the second year of college. The Engage, developed by American College
Testing (ACT), measures psychosocial and study skill factors in three broad categories:
motivation, academic related skills, and social engagement.
40
Participants
The participants in the current study included 4,379 first-year freshman students
in a regional Texas public university. The university selected for this study is one of two
universities in the state that administers the Engage to each of its incoming freshmen
during annual orientation activities. Table 5 shows the ethnicity and gender distribution
for the study sample. Among the participants, the majority were female (2,388 or 54%)
while 46% were male. The ethnic distribution included 633 participants (14.5%) self-
identifying themselves as African American, 64 (1.5%) as American Indian, 376 (8.6%)
as Asian/Pacific Islander, 1038 (23.7%) as Hispanic, and 2,185 (49.9%) as White.
Thirty-four (.8%) were identified as Other, while 49 (1.1%) provided no response.
Table 5
Ethnicity and Gender Distribution of Study Participants
Variable Frequency Percent Cumulative Percent
African American 633 14.5 14.5 American Indian 64 1.5 15.9 Asian/Pacific Islander 376 8.6 24.5 Hispanic 1,038 23.7 48.2 White 2,185 49.9 98.1 Other 34 .8 98.9 No Response 49 1.1 100.0 Female 2,388 54.5 54.5 Male 1,991 45.5 100.0
Table 6 displays the descriptive measures regarding participants’ age, ACT/SAT
scores, class rank, and class size. The descriptive measures included the percentage,
41
minimum, maximum, and mean values for each variable. Participants’ ages ranged from
14 to 54 years with a mean of 17.99 and a standard deviation of .941. The results
indicate that 95.6% of study participants were between the ages of 16 and 19 years old
at the time of their initial enrollment at the selected university. Participants’ SAT scores
ranged from a low of 650 to a high of 1,600 (perfect score) with a mean score of
1,105.55 (SD = 146.83). Note the mean score for study participants was 94.45 points
higher than the mean for all college-bound SAT test takers from the high school class of
2012 across the nation. In addition, ACT scores ranged from 15.3 to 36 (perfect score)
with an overall mean value of 23.75 (SD = 3.61). The mean ACT value among the study
participants was 2.65 points higher than the national average for all college-bound ACT
test takers in the high school class of 2012. Regarding class size, study participants
graduated from high schools with senior classes ranging in size from 9 to 1,517 with a
mean value of 457.22 (SD = 266.94). The percentage class rank for study participants
ranged from 2 to 100 with a mean of 72.76 (SD = 17.39), indicating that most study
participants graduated in the top third of their respective high school classes. There is a
difference in the number of study participants in regards to class rank because some
participants were home schooled and some schools have enacted policies against
ranking their graduates. The data were not provided for 262 participants. Because of the
overall large size of the sample and the small number of participants for which data
were not reported, these differences did not significantly impact the results of this study.
42
Table 6
Descriptive Statistics for Study Participants - Age, Highest Composite SAT and ACT Scores, Class Rank, and Class Size
Variable N Minimum Maximum Mean Standard Deviation
Age 4,379 14 54 17.99 .941
ACT 1,392 15.3 36.0 23.755 3.6143
SAT 2,953 650 1600 1105.55 146.831
HS Rank 4,104 2 100 72.76 17.386 Class Size 3,803 9 1517 457.22 266.940
Pell grant eligibility and Texas Success Initiative college readiness status are
shown in Table 7. A review of the Pell grant eligibility status for study participants
indicated that approximately one-third of the freshman class qualified for federal
financial assistance with 37.9% (n = 1658) qualifying and 62.1% (n = 2721) not
qualifying. The majority of the study participants (93.9%, n = 4111) met the state
requirements for attending a state public university by earning a college ready status
through the Texas Success Initiative (TSI). In comparison, only 6.1% (n = 268) of the
study participants did not submit a score sufficient to meet the requirements of the TSI.
Participants who did not meet the TSI requirements attempted an approved TSI
assessment and failed one or more portions of the test. These students, while not
meeting TSI requirements, may still be admitted to a public university in Texas.
However, state law requires that students not meeting TSI admission requirements
enroll in approved developmental education for any failed testing area.
43
Table 7
Descriptive Statistics for Study Participants - Pell Grant Eligibility, and Texas Success Initiative (TSI) College Readiness Status
Variable Frequency Percent Valid Percent Cumulative Percent
Pell Eligible Yes 1,658 37.9 37.9 100.0
Pell Eligible No 2,721 62.1 62.1 62.1 TSI Yes 4,111 93.9 93.9 93.9 TSI No 268 6.1 6.1 100.0
Variables Examined
Dependent Variables
1. Current GPA – The first semester college grade point average (Current GPA)
was calculated by assigning each grade earned in a course a predetermined
point value. Specifically, a grade of A was assigned 4 points, B assigned 3
points, C awarded 2 points, D given 1 point, and F received 0 points. The
current GPA was calculated by dividing the sum of the values assigned to the
corresponding alphabetical grade earned in all courses attempted, by the
number of semester hours of credit associated with each grade. Current GPA
was measured as a continuous variable on a 4 point scale.
2. Persistence in college (Persistence) - Persistence is defined as the
continuous enrollment after the first year of college of a student with the
intention of completing the selected program of studies and earning a degree.
Persistence in College was measured as a categorical variable with
persistence coded 1 and non-persistence coded 0.
44
Independent Variables
1. Gender (Gender) – The Gender of each study participant was identified as
male or female. Gender was measured as a categorical variable with males
coded 1 and females coded 0.
2. Ethnicity (Ethnicity) - Ethnicity categorizes people according to biological or
genetic traits. Ethnicity was measured as a categorical variable with African-
American coded 1, Asian coded 2, Hispanic coded 3, Native American coded
4, Other coded 5, and White coded 6.
3. Socio-economic status (SES) (Pell Eligibility) - SES is a measure of an
individual’s or family’s economic and social position based on income. SES
was measured by a student’s eligibility for a Federal Pell Grant and was
measured as a categorical variable. Pell Grant eligibility was coded 1, and
non-Pell Grant eligibility was coded 0.
4. High school class rank (HS Rank) – Percentage Class Rank in high school
class is a continuous variable ranging between 1 and 100. One-hundred was
the upper limit for this variable because it represents the highest percentage
rank a student could achieve out of the entire class of students.
5. SAT composite scale score (SAT) – Raw scores were calculated for the math
and verbal sections based on the number of questions on the SAT answered
correctly or incorrectly, or omitted. The scaled score is determined from the
raw score by a statistical process called equating and ranges from 200 to
800. This process ensures that the different forms of the test or the level of
ability of the group of students testing did not impact an individual’s score.
45
The SAT score is the composite of a student’s highest scaled scored on the
math and verbal tests and is the score used by the university in the admission
decision. The SAT Composite Scale Score was measured as a continuous
variable.
6. ACT composite score (ACT) - The ACT raw score for each test section
(English, Math, Reading, and Science) was calculated by determining the
number of questions answered correctly. One point is awarded for each
correct answer and no points are deducted for incorrect or omitted responses.
Raw scores for each test section were converted to scaled scores which
range between 1 and 36. The ACT Composite Score was the average of the
student’s scaled scores for the four multiple-choice test sections. The
reported ACT composite score was the student’s highest scaled scored on
each of the ACT test sections and is used by the university in the admission
decision. The ACT Composite Scale Score was measured as a continuous
variable.
7. TSI complete (TSI Complete) – The Texas Success Initiative (TSI) requires
that all students entering a Texas public institution of higher education must
meet certain standards of college readiness before enrolling in credit bearing
courses. In order to meet this requirement, students must meet one of the
following conditions:
1. Earn a composite ACT score of at least 23 with a minimum score on the
math and/or verbal section of 19. ACT Inc. has determined this is the
minimum ACT score students would need to earn in order to have a 50%
46
likelihood of getting a B or better in an introductory college class and a
75% likelihood of getting a C or better.
2. Earn a composite SAT score of at least 1,070 with a minimum math and/or
verbal score of 500. The College Board has determined that this is the
minimum SAT score students would need to earn in order to have a 65%
likelihood of achieving at least a B-minus average (2.67 GPA) during the
first year of college
3. Demonstrate college readiness through successful military service,
completion of college level coursework at a private or out-of-state
university, or through enrollment in a certificate program at a community
college or technical school.
4. Meet the college ready benchmark standard on the 11th grade Texas
Assessment of Knowledge and Skills (TAKS) high school exit exam.
5. Meet the college readiness standard on the following state-approved
college placement exams: ASSET, COMPASS, THEA, and
ACCUPLACER.
Students who do not meet the TSI standard are required to enroll in
approved developmental education for any subject for which a passing
score was not achieved.The TSI Complete benchmark was measured as
a categorical variable with students meeting the standard coded 1 and
students not meeting the standard coded 0.
6. ACT Engage – The Engage is a statistically validated questionnaire
measuring psychosocial factors that are indicative of college students’
47
academic readiness and persistence toward graduation. The questions
measuring psychosocial factors were grouped into themes and scores for
each theme were measured as continuous variables.
Instrumentation
History of the ACT Engage
The Engage was developed after a comprehensive review of existing literature
by Robbins et al. (2004). Specifically, using educational persistence and motivational
theory models as a framework (Bean, 1980; Tinto, 1975, 1993; Dweck, 1999, and
Eccles & Wigfield, 2002), Robbins et al. (2004) and his team analyzed 109 studies and
examined the relationship between psychosocial and study skill factors and college
outcomes that included achievement and persistence.
Tinto’s Integration Theory included measurement of students’ contextual
influences, such as the quality of faculty-student interactions, integration into the school,
perceptions of social support, social involvement, and institutional commitment.
Similarly, Bean’s Attrition Theory linked organizational variables such as informal
contact with faculty members, membership in campus organizations, and the
helpfulness of an advisor to college success outcomes. Covington (2000), and Eccles
and Wigfield (2002) identified three factors as the best predictors of college
achievement outcomes: motivation to achieve, self-expectancy, and values. Students’
ability to self-regulate their own learning was identified as a predictor of achievement
outcomes by Schunk and Zimmerman (2003), Zimmerman (1986), and Zimmerman and
Martinez-Pons (1986). Finally, research by Pintrich, Smith, Garcia and McKeachie
(1993) identified test anxiety as another important predictor of college students’
48
academic performance. As a result of the meta-analysis, nine broad constructs were
created to categorize the psychosocial factors and study skills identified in the literature
as having predictive validity regarding college students’ achievement and persistence.
These constructs include: achievement motivation, academic goals, institutional
commitment, perceived social support, social involvement, academic self-efficacy,
general self-concept, academic-related skills, and contextual influences. Finally, the
nine broad constructs were then combined into three higher order constructs:
motivation, academic-related skills, and social engagement, forming the foundation for
the inventory as a method for predicting college achievement and persistence.
Psychometric Properties of the ACT Engage
In order to create assessment questions that would be understood by
participants and would yield valid and reliable results, researches followed a carefully
designed process described in Chapter 2. Questions were created, evaluated, and
revised through a sampling process including more than 20,000 participants. Education,
advising/counseling, and personality psychology professionals assisted ACT
researchers in generating an initial pool of 320 items which were then evaluated for
comprehensibility by a small sample of high school students. An item selection study
involving more than 5,000 students was conducted and, after exploratory and
confirmatory factor analysis, 10 items were selected to measure each of the 10 Engage
scales.
Reliability estimates were calculated for each of the 10 scales and Table 8 shows
that the scales demonstrate moderate to high internal consistency reliabilities using
49
Cronbach’s alpha (alpha range = .80 -.87 and median = .84).
Table 8
Internal Consistency Reliability of the Engage Scales
Scale # of Items Score Range Alpha
Academic Discipline 10 10-60 .83 Academic Self-Confidence 12 12-72 .83 Commitment to College 10 10-60 .85 Communication Skills 10 10-60 .82 General Determination 11 11-66 .87 Goal Striving 10 10-60 .84 Social Activity 10 10-60 .84 Social Connection 11 11-66 .80 Steadiness 12 12-72 .84 Study Skills 12 12-72 .86 Note. Source: ACT. (2008b). Student readiness inventory (Engage) user’s guide. Retrieved from: http://www.act.org/sri/pdf/UserGuide.pdf
To validate the Engage, 23 two-year and 25 four-year postsecondary institutions
representing a variety of geographic locations, selectivity levels, and demographic
characteristics of students participated in the preliminary analysis. A total of 14,464
incoming first year students from these schools completed the Engage. Institution type
and selectivity, demographic characteristics, and prior academic achievement were
controlled so the validity of the Engage themes as predictors of students’ performance
and persistence could be examined. The effectiveness of the Engage scores in
predicting performance and persistence was measured by the percentage of students
correctly identified as having academic difficulty (first semester GPA < 2.0) or dropping
out after the first semester. The predictive accuracy of the Engage was compared to
results achieved through a random selection of students, use of ACT scores, and the
combination of ACT and Engage scores. Table 9 shows the percentages of participants
50
in the sample who were correctly identified by each of these methods. It also shows that
the Engage is not only a stronger predictor of performance than the ACT alone, but that
when combined with the ACT it provides the greatest likelihood of accurate identification
of students unlikely to be successful in school.
Table 9
Percent of 4-Year College Students Accurately Identified as At-Risk Per 100 Students
Selection Method Drop-Out Academic Difficulty
Random Selection 10% 20% ACT Composite Score Only 16% 44% Engage Only 24% 46% ACT Composite Score + Engage 25% 51%
Note. ACT. (2008b). Student readiness inventory user’s guide. Retrieved from: http://www.act.org/sri/pdf/UserGuide.pdf Procedure and Data Analysis
Initially, data was obtained from Engage surveys administered to 4,379 freshmen
during the fall semester orientation of the 2012-2013 school year at the selected
university participating in this study. Next the data was entered into my database and
screened for erroneous entries. Data was then reviewed for completeness in order to
meet the requirements of statistical analysis. Descriptive statistics (i.e. mean and
standard deviation for continuous variables and frequencies and percentages for
categorical variables) were calculated to examine the distribution and shape of each
variable included in the study. The rationale for examining the shape and distribution
was to determine if any transformation of the dependent variable was needed in order to
conduct statistical analyses. After determining that no transformations were necessary, I
51
proceeded with the statistical analysis. Descriptive measures were calculated for each
variable in the current study. Then, bivariate correlations (i.e. Pearson product moment
correlations) were calculated to examine the bivariate relationships between each of the
independent and dependent variables. Note: Correlations range from -1 to 1. Regarding
the magnitude of the absolute value of the correlation coefficient, a small or slight
correlation ranges from 0 to .30, a moderate correlation ranges from .31 to .50, while a
strong correlation ranges from .51 to 1.0 (Cohen, 1988). Next, multiple regression was
conducted whereby the independent variables were regressed upon the outcome or
dependent variable (current GPA) while controlling for selected demographic variables.
Then, logistic regression was conducted using the same independent variables and
persistence as the dependent variable. These results of multiple and logistic regression
analyses allowed me to determine the unique effects of traditional and non-traditional
indicators of college readiness on the first semester college GPA and persistence to the
second year of college. The effect size and 95% confidence intervals were reported
where necessary to place the results of each analysis into proper context. SPSS™
(www.ibm.com version 22.0 was used for all analyses.
Summary
This study was designed to address the gap in research that exists regarding the
predictability of traditional academic and non-traditional psychosocial skills in relation to
college students’ performance and persistence. Data from participants’ high school
percentage rank and ACT/SAT college admission exams were selected as predictor
variables because they are traditionally used in the college admission process. In
addition, data from the ACT Engage were selected as the measure of participants’
52
psychosocial skills based on prior research confirming the validity of the assessment
and because, although supported by a rich literature base, psychosocial skills have
traditionally not been utilized in the college admission process.
Knowing which factors most strongly correlate to college performance and
persistence can provide significant benefit to K-12 educators, university professors and
administrators, and most importantly to individual students. While existing research
shows a correlation between traditional academic indicators like high school class rank
and college admission test scores (SAT/ACT) and academic success in college, the
predictive power of students’ psychosocial skills has been examined under much more
limited circumstances. Furthermore, despite a strong literature base that indicates the
importance of psychosocial skills to students’ post K-12 success, most universities still
rely on the traditional indicators of college success when selecting students.
Understanding the predictive power of students’ psychosocial skills could help university
leaders not only answer demands by hiring managers that students increase their
mastery of 21st century skills, but also effectively respond to the growing political and
economic pressure to graduate more students within four years. The findings from this
study are intended to lead to greater reliance by university leaders on non-traditional
indicators of college readiness, and ultimately result in increased levels of achievement
and persistence among future classes of university freshmen.
53
CHAPTER 4
RESULTS
Introduction
This study analyzed the predictive power of traditional and non-traditional
indicators of college readiness on measures of college academic performance and
persistence. Traditional indicators of college readiness included high school class rank,
composite Scholastic Aptitude Test (SAT) or American College Test (ACT) scores and
college readiness status, as measured by participants’ Texas Success Initiative (TSI)
data. Non-traditional indicators of college readiness included results from the ACT
Engage, which measured participants’ level of psychosocial skill development according
to ten different themes. Measures of college performance and persistence included
participants’ first semester college GPA and their enrollment status in the second year
of college. The sample included 4,379 students who met the enrollment criteria and first
attended classes at the selected participating university in the fall of 2012. The research
questions guiding this study sought to determine which traditional and non-traditional
indicators of college readiness were better predictors of college success and
persistence. Specifically, the research questions included:
1. Does high school class rank, college entrance exam scores, or psychosocial
skills best predict student performance in the students’ first year of college
among freshman students in a selected Texas public university?
2. Does high school class rank, college entrance exam scores, or psychosocial
skills best predict student persistence to the second year of college among
freshman students in a selected Texas public university?
54
To effectively answer the research questions in this study, a predictive model identifying
the relationship between the selected dependent and independent variables was
constructed. Descriptive statistics, bivariate correlations, and multiple regression and
binary logistic regression models were calculated to analyze the data. The findings are
displayed in 6 tables.
Descriptive Statistics
Table 10 displays the range, mean, and standard deviation values for each of the
ten themes measured by the Engage instrument. The mean values among the theme
ranged from 50.15 (SD = 29.73) to 60.75 (SD = 31.16). Among study participants in the
2012 freshmen class, Commitment to College, Study Skills, and Academic Self-
Confidence exhibited the largest mean among psychosocial skills compared to Social
Activity, Social Connection, and Communication Skills. Note: Commitment to College
returned the greatest variance in responses with a standard deviation of 29.57.
Table 10
Descriptive Statistics for Study Participants – Engage Inventory Mean Results Variable N Minimum Maximum Mean Standard
Deviation Academic Discipline 3533 1 99 56.01 28.074 Academic Self-Confidence 3524 1 99 58.02 27.890 Commitment to College 3536 1 99 60.75 31.162 Communication Skills 3528 1 99 54.74 28.805 General Determination 3529 1 99 56.88 29.568 Goal Striving 3524 1 99 55.33 29.462 Social Activity 3530 1 99 50.15 29.731 Social Connection 3529 1 99 52.56 27.583 Steadiness 3531 1 99 57.62 28.867 Study Skills 3528 1 99 58.28 27.649 The Impact of Academic and Psychosocial Factors on College Performance
55
Research Question 1
Does high school class rank, college entrance exam scores, or psychosocial
skills best predict student performance in the students’ first year of college among
freshman students in a selected Texas public university?
The results of multiple regression analysis provide insight into Resear
Question 1 by determining the strength of the relationship between traditional and non-
traditional measures on college performance (first-year GPA). Table 11 displays the
correlation between gender, age, ethnicity, Pell Grant eligibility, TSI Complete, HS
Rank, ACT, SAT, the ACT Engage themes and college performance measured by the
students’ first semester college GPA. Independent variables with negligible correlation (r
< .10) to the dependent variable included age and non-traditional variables,
Commitment to College, Communication Skills, General Determination, Goal Striving,
Social Activity, Social Connection, and Study Skills. Further, gender, ethnicity, Pell
eligibility, TSI Complete, Academic Discipline, and Academic Self-Confidence were
slightly correlated (r =.10 -.30) with the dependent variable. The non-traditional Engage
factor, Academic Discipline, accounted for the most variance in the current GPA (r2 =
6.25%). Regarding traditional variables with the strongest positive correlation to Current
GPA, HS Rank exhibited the strongest correlation (r = .378) with similar results noted for
college admission exams that included the SAT (r = .315) and ACT assessments (r =
.327). When converted to r2, these predictors accounted for 14.28%, 9.92%, and
10.69% of the variance in first semester college GPA, respectively.
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Table 11 Correlation Between Gender, Age, Ethnicity, Pell Grant Eligibility, TSI College Readiness Indicator, High School Class Rank, ACT Scores, SAT scores, ACT Engage Psychosocial Factors and Academic Performance in College
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
CURRENT GPA (1) 1.00 GENDER (2) .150 1.00 AGE (3) -.096 -.037 1.00 ETHNICITY (4) .109 -.031 .157 1.00 PELL ELIGIBILITY (5) .130 -.023 -.074 .288 1.00 TSI COMPLETE (6) -.140 -.014 .105 -.056 -.058 1.00 HS RANK (7) .378 .173 -.073 .022 -.054 -.119 1.00 ACT (8) .327 -.141 -.079 .359 .236 -.295 .244 1.00 SAT (9) .315 -.138 -.356 .175 .273 -.251 .187 1.00 ACADEMIC DISCIPLINE (10) .250 .217 -.036 -.023 -.027 -.008 .270 -.039 -.129 1.00 ACADEMIC SELF-CONFIDENCE (11) .111 -.117 -.050 .056 .013 -.147 .234 .371 .311 .390 1.00 COMMITMENT TO COLLEGE (12) .076 .141 -.028 -.087 -.035 .007 .076 -.030 -.096 .474 .315 1.00 COMMUNICATION SKILLS (13) .044 .095 -.037 -.026 -.010 -.007 -.014 -.038 -.071 .421 .215 .402 1.00 GENERAL DETERMINATION (14) .084 .090 -.029 -.075 -.064 .013 .098 -.109 -.164 .716 .384 .539 .592 1.00 GOAL STRIVING (15) .029 -.007 -.024 -.107 -.063 .008 .041 -.085 -.149 .616 .493 .540 .542 .794 1.00 SOCIAL ACTIVITY (16) -.087 -.010 -.034 -.002 .027 .015 -.113 -.076 -.107 .228 .300 .296 .338 .328 .497 1.00 SOCIAL CONNECTION (17) -.039 .031 -.049 -.021 .025 .022 -.060 -.086 -.150 .328 .195 .388 .545 .434 .532 .580 1.00 STEADINESS (18) -.005 -.110 -.015 -.051 -.043 -.005 -.012 -.023 -.005 .373 .357 .282 .405 .417 .472 .345 .237 1.00 STUDY SKILLS (19) .059 .057 -.003 -.099 -.066 .016 .041 -.072 -.089 .534 .326 .370 .536 .628 .625 .252 .374 .370 1.00
57
Initially, multiple regression models were constructed to predict first semester
college GPA from the statistically significant independent variables reported in Table 11.
In order to account for the fact that data on study participants included either an ACT or
SAT score, but not both, two separate models were constructed for analysis. The first
model, shown in Table 12, included ACT scores as an additional independent variable,
while the second model, shown in Table 13, included SAT as the additional independent
variable. Current GPA remained the dependent variable in both models.
The multiple regression model including ACT scores (see Table 12), returned an
R- Square value of .303, indicating that the overall model explained approximately 30%
of the variance in college GPA, which was a moderate effect size (Cohen, 1988). The
model was statistically significant (F = 30.31, df = 1202, p < .001). The results of Model
1 displayed in Table 12, indicate that gender, Pell eligibility, HS rank, ACT, Academic
Discipline, Academic Self Confidence, and Social Activity were statistically significant
predictors of Current GPA, (p < .05). The variables producing the highest degree of
predictability of Current GPA based on the standardized beta coefficients included
Academic Discipline, ACT, and HS rank. Thus, results regarding Research Question 1
suggest that among students taking the ACT, Academic Discipline was a stronger
predictor of college performance than ACT scores or high school class rank. Note while
ethnicity was statistically significant, the model was not designed to treat each ethnic
group as a distinct independent variable.
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Table 12 Regression of Students’ Gender, Age, Ethnicity, Pell Grant Eligibility, TSI College Readiness Indicator, High School Class Rank, ACT Scores, and ACT Engage Psychosocial Factors on Academic Performance in College
Variable
Unstandardized Coefficients
Standardized Coefficients t Sig.
95.0% Confidence Interval for B
B Std. Error Beta Lower Bound Upper Bound (Constant) .507 1.264 .401 .688 -1.972 2.987 Gender .123 .055 .060 2.239 .025 .015 .231 Age -.069 .067 -.026 -1.031 .303 -.201 .062 Ethnicity .055 .014 .106 3.887 .010 .027 .082 PELL Eligibility .134 .053 .066 2.545 .011 .031 .238 TSI Complete -.062 .110 -.014 -.566 .571 -.277 .153 HS Rank .016 .002 .272 9.798 .010 .012 .019 ACT .073 .009 .266 8.326 .010 .056 .090 Academic Discipline .010 .002 .283 6.738 .010 .007 .013 Academic Self-confidence -.004 .001 -.114 -3.329 .001 -.006 -.002 Commitment to College -.001 .001 -.023 -.772 .440 -.003 .001 Communication Skills -.001 .001 -.020 -.564 .573 -.003 .002 General Determination -.002 .002 -.065 -1.295 .195 -.006 .001 Goal Striving .003 .002 .077 1.535 .125 -.001 .006 Social Activity -.002 .001 -.070 -2.099 .036 -.005 .000 Social Connection -.001 .001 -.020 -.578 .563 -.003 .002 Steadiness -.002 .001 -.045 -1.485 .138 -.004 .001 Study Skills -.001 .001 -.020 -.585 .558 -.003 .002
59
The multiple regression results including the SAT scores displayed in Table 13
produced an R-Square value of .246, indicating that the overall model explained
approximately 25% of the variance in college GPA. The effect size, according to Cohen
(1988) was moderate. The model was statistically significant (F = 43.59, df = 2293, p <
.001). The results of Model 2, which are displayed in Table 13, suggest that Gender,
Pell eligibility, HS rank, SAT, Academic Discipline, Academic Self Confidence, and
Commitment to College were statistically significant predictors of college GPA (p < .05).
Similar to the results found in Model 1, Model 2 revealed that the variables producing
the highest degree of predictability of current GPA based on standardized beta
coefficients included the non-traditional predictor of Academic Discipline, while
traditional predictors included SAT and HS rank. The results suggest that among
participants taking the SAT, Academic Discipline was a stronger predictor of college
performance than either SAT scores or high school class rank.
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Table 13 Regression of Gender, Age, Ethnicity, Pell Grant Eligibility, TSI College Readiness Indicator, High School Class Rank, SAT scores, and ACT Engage Psychosocial Factors on Academic Performance in College
Variable Unstandardized
Coefficients Standardized Coefficients
t Sig.
95.0% Confidence Interval for B
B Std. Error Beta Lower Bound
Upper Bound
(Constant) -2.570 .925 -2.780 .005 -4.384 -.757 Gender .173 .043 .082 4.077 .000 .090 .257 Age .065 .049 .025 1.331 .183 -.031 .160 Ethnicity -.003 .011 -.005 -.229 .819 -.024 .019 PELL Eligibility .178 .043 .082 4.168 .010 .094 .262 TSI Complete -.122 .096 -.024 -1.277 .202 -.310 .065 HS Rank .015 .001 .243 11.779 .010 .013 .018 SAT .002 .000 .266 11.548 .010 .002 .002 Academic Discipline .010 .001 .274 9.647 .010 .008 .012 Academic Self-confidence -.004 .001 -.113 -4.499 .010 -.006 -.002 Commitment to College .002 .001 .046 1.985 .047 .000 .003 Communication Skills .002 .001 .045 1.713 .087 .000 .004 General Determination -.002 .001 -.062 -1.714 .087 -.005 .000 Goal Striving .000 .001 -.008 -.220 .826 -.003 .002 Social Activity -.001 .001 -.021 -.856 .392 -.002 .001 Social Connection -.002 .001 -.050 -1.910 .056 -.004 .000 Steadiness -.001 .001 -.015 -.663 .508 -.002 .001 Study Skills .001 .001 .015 .587 .557 -.001 .002
61
The Impact of Academic and Psychosocial Factors on College Persistence
Research Question 2
Does high school class rank, college entrance exam scores, or psychosocial
skills best predict student persistence to the second year of college among freshman
students in a selected Texas public university?
The results of the Pearson Product Moment correlations displayed in Table 14
revealed that ethnicity, Academic Self-Confidence, Goal Striving, and Steadiness, did
not meet the p < .05 threshold for statistical significance. Further, gender, age, Pell
eligibility, TSI Complete, Commitment to College, Communication Skills, General
Determination, Social Activity, Social Connection, and Study Skills each explained less
than 1% of the variance in persistence, with correlations ranging from r = -.084 to r =
.099. The only independent variables slightly correlated with Persistence included ACT
(r = - .121), SAT (r = -.122), Academic Discipline (r = -.123), and HS rank (r = -.160).
When converted to r2, the non-traditional indicator, Academic Discipline accounted for
1.51% of the variance in Persistence, while traditional indicators ACT, SAT, and HS
rank accounted for 1.46%, 1.48%, and 2.56% respectively
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Table 14 Correlation Between Gender, Age, Ethnicity, Pell Grant Eligibility, TSI College Readiness Indicator, High School Class Rank, ACT Scores, SAT scores, ACT Engage Psychosocial Factors and Academic Persistence in College
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
PERSISTENCE (1) 1.00 GENDER (2) -.099 1.00 AGE (3) .031 -.037 1.00 ETHNICITY (4) -.005 -.031 .157 1.00 PELL ELIGIBILITY (5) -.068 -.023 -.074 .288 1.00 TSI COMPLETE (6) .056 -.014 .105 -.056 -.058 1.00 HS RANK (7) -.160 .173 -.073 .022 -.054 -.119 1.00 ACT (8) -.121 -.141 -.079 .359 .236 -.295 .244 1.00 SAT (9) -.122 -.138 -.356 .175 .273 -.251 .187 1.00 ACADEMIC DISCIPLINE (10) -.123 .217 -.036 -.023 -.027 -.008 .270 -.039 -.129 1.00 ACADEMIC SELF-CONFIDENCE (11) -.031 -.117 -.050 .056 .013 -.147 .234 .371 .311 .390 1.00 COMMITMENT TO COLLEGE (12) -.084 .141 -.028 -.087 -.035 .007 .076 -.030 -.096 .474 .315 1.00 COMMUNICATION SKILLS (13) -.046 .095 -.037 -.026 -.010 -.007 -.014 -.038 -.071 .421 .215 .402 1.00 GENERAL DETERMINATION (14) -.045 .090 -.029 -.075 -.064 .013 .098 -.109 -.164 .716 .384 .539 .592 1.00 GOAL STRIVING (15) -.013 -.007 -.024 -.107 -.063 .008 .041 -.085 -.149 .616 .493 .540 .542 .794 1.00 SOCIAL ACTIVITY (16) .039 -.010 -.034 -.002 .027 .015 -.113 -.076 -.107 .228 .300 .296 .338 .328 .497 1.00 SOCIAL CONNECTION (17) -.033 .031 -.049 -.021 .025 .022 -.060 -.086 -.150 .328 .195 .388 .545 .434 .532 .580 1.00 STEADINESS (18) .006 -.110 -.015 -.051 -.043 -.005 -.012 -.023 -.005 .373 .357 .282 .405 .417 .472 .345 .237 1.00
STUDY SKILLS (19) -.037 .057 -.003 -.099 -.066 .016 .041 -.072 -.089 .534 .326 .370 .536 .628 .625 .252 .374 .370
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Binary logistic regression was employed to provide insight into Research
Question 2 and ascertain the effects of traditional and non-traditional predictors on the
likelihood that study participants would enroll in a second year of coursework. Binary
logistic regression was selected because the dependent variable, persistence, was
dichotomous rather than continuous. In the case of persistence, either students enrolled
in the second year of studies (coded 1) or they did not (coded 0). Further, binary logistic
regression is best suited to predict the probability of either of the two categories of
dependent variable occurring, given the characteristics of the independent variables in
the model.
Similar to the methodology used to answer Research Question 1, two separate
logistic regression models were constructed to answer Research Question 2. The first
model, shown in Table 15, included ACT as the independent variable. The second
model, shown in Table 16, included SAT as the independent variable. Two separate
models were necessary as participants took only the ACT or SAT, but not both.
Persistence remained the dependent variable in both models.
The initial binary logistic regression model (Model 1) examined data among the
participants who submitted ACT scores for admission consideration and can be used to
classify subjects at a .5 threshold with respect to the anticipated decision to persist in
college. This model explained 11.4% of the variance in persistence based on
Nagelkerke R2 value and correctly classified 78.9% of the cases, indicating the model is
reliable for prediction purposes. Sensitivity, or the percentage of occurrences with the
observed characteristic (e.g., “yes” for persistence) indicted that the model correctly
predicted 98.9% of the cases. Further, specificity, or the percentage of occurrences that
did not have the observed characteristic (e.g., “no” for persistence was 6.2%. Of the 17
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predictor variables, two non-traditional predictors measured by the Engage were
statistically significant. The results revealed that for each point participants’ scores on
Academic Discipline increased above the mean of 56.01, the odds of persistence were
increased by a factor of 1.01 (95% CI ranged from 1.005 to 1.123). Similarly, for each
point participants’ scores in Social Connection increased above the mean of 52.56, the
likelihood of persistence increased by a factor of 1.001 (95% CI ranged from 1.001 to
1.016).Note: while the variables were statistically significant, the likelihood of
persistence was slightly above chance alone (i.e., Exp (B) = 1.0 is a neutral value for
which both outcomes, persistence/non-persistence are equally likely). Three traditional
predictor variables, which were statistically significant, yielded negative results. More
specifically, participants classified as females exhibited a decrease in the log odds of
persisting to the second year of coursework by 29.1% (95% CI ranged from .516 to
.974) over male participants. Regarding Pell eligibility, participants who met the
requirements to receive federal financial assistance decreased the log odds of returning
for year two by 46.0% (95% CI ranged from .398 to .733) over participants who did not
receive financial assistance. Finally, for each point above the mean of 23.75 that
participants ACT scores increased, their odds of persistence increased by a factor of
1.10 (95% CI ranged from 1.051 to 1.170). The results from Model 1 suggest that
among study participants taking the ACT, those more likely to persist to the second year
of study were males, scored above the mean in Academic Discipline, Social
Connection, and on the ACT, and did not qualify for Pell Grant financial assistance.
Participants meeting this criteria had a probability of 96% of persisting to their second
year of coursework at the selected Texas University.
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Table 15 Logistic Regression Among Sex, Age, Ethnicity, Pell Grant Eligibility, TSI College Readiness Indicator, High School Class Rank, ACT scores, ACT Engage Psychosocial Factors and Academic Persistence in College
Variable B S.E. Wald df Sig. Exp(B)
95% C.I. for EXP(B)
Lower Upper
Gender -.344 .162 4.500 1 .034 .709 .516 .974 Age .171 .200 .732 1 .392 1.186 .802 1.755 Ethnicity -.065 .042 2.388 1 .122 .937 .863 1.018 PELL Eligibility -.616 .156 15.608 1 .010 .540 .398 .733 TSI Complete .358 .294 1.483 1 .223 1.430 .804 2.543 HS Rank .008 .005 3.401 1 .065 1.009 .999 1.018 ACT .103 .027 14.239 1 .010 1.109 .1.051 1.170 Academic Discipline .014 .005 9.458 1 .002 1.014 1.005 1.123 Academic Self-confidence -.005 .004 2.172 1 .141 .995 .998 1.002 Commitment to College .003 .003 1.410 1 .235 1.003 .998 1.009 Communication Skills -.001 .004 .023 1 .879 .999 .992 1.007 General Determination -.002 .005 .112 1 .738 .998 .988 1.008 Goal Striving -.004 .005 .551 1 .458 .996 .986 1.006 Social Activity -.005 .003 2.248 1 .134 .995 .998 1.002 Social Connection .008 .004 5.035 1 .025 1.009 1.001 1.016 Steadiness -.002 .003 .447 1 .504 .998 .992 1.004 Study Skills .002 .004 .304 1 .582 1.002 .995 1.009 Constant -5.006 3.785 1.834 1 .176 .007
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Model 2, which examined data among participants who submitted SAT scores for
admission consideration, was calculated to determine the utility of the model for
predicting persistence. Model 2 explained approximately 9.5% of the variance in
persistence based on Nagelkerke R2 and correctly classified 75.3% of the cases. The
model was reliable for prediction purposes based on sensitivity, which was 98.5% while
specificity was 5.5%. While determined to be a statistically significant predictor in Model
2, ethnicity was not interpretable because of the coding method utilized in this study. Of
the remaining 16 predictor variables, the variable returning the most significant effect on
persistence was gender; female participants decreased the log odds of persisting to the
second year of college by 21% (95% CI ranged from .635 to .979) over male
participants. In addition, five variables were statistically significant but showed little
predictive validity in determining participants’ persistence to their sophomore year. As
participants’ SAT scores increased above the mean of 1105.55, their log odds of
persisting increased by a factor of 1.001 (95% CI ranged from 1.002 to 1.004). Similarly,
for each point that participants’ scores increased above the mean in Commitment to
College (mean = 60.75), Academic Discipline (mean = 56.01), and high school rank
(mean = 72.76), their log odds of persisting to the second year of college also increased
by factors of 1.006 (95% CI ranged from 1.005 to 1.016), 1.011 (95% CI ranged from
1.002 to 1.010), and 1.019 (95% CI ranged from 1.013 to 1.026), respectively. Note:
While the variables were statistically significant, the likelihood of persistence was
slightly above chance alone (i.e., Exp (B) = 1.0 is a neutral value for which both
outcomes, persistence/non-persistence are equally likely). Interestingly, Academic Self-
Confidence (a non-traditional college readiness indicator), decreased the log odds of
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not persisting. For each point above the mean of 58.02 that participants’ scores
increased in Academic Self-Confidence, the log odds of returning decreased by a factor
of .005 (95% CI ranged from .990 to .999). The results from Model 2 suggest that
among study participants taking the SAT, male participants and those with higher high
school class ranks, SAT scores, and Academic Discipline scores were more likely to
persist in their college studies. The probability of participants persisting to the second
year of study meeting this criteria was 91%. On the other hand, study participants from
the SAT score subset who were less likely to persist to the second year of college were
those scoring above the mean on Academic Self-Confidence.
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Table 16 Logistic Regression Among Sex, Age, Ethnicity, Pell Grant Eligibility, TSI College Readiness Indicator, High School Class Rank, SAT scores, ACT Engage Psychosocial Factors and Academic Persistence in College
Variable B S.E. Wald df Sig. Exp(B)
95% C.I. for EXP(B)
Lower Upper Gender -.237 .110 4.629 1 .031 .789 .635 .979 Age -.046 .125 .136 1 .712 1.047 .820 1.337 Ethnicity .073 .029 6.311 1 .012 .930 .879 .984 PELL Eligibility -.143 .111 1.666 1 .197 .867 .698 1.077 TSI Complete -.080 .232 .119 1 .730 .923 .586 1.455 HS Rank .019 .003 34.532 1 .010 1.019 1.013 1.026 SAT .003 .001 26.333 1 .010 1.003 1.002 1.004 Academic Discipline .011 .003 15.526 1 .010 1.011 1.005 1.016 Academic Self-confidence -.005 .002 4.681 1 .030 .995 .990 .999 Commitment to College .006 .002 8.806 1 .003 1.006 1.002 1.010 Communication Skills .002 .002 .721 1 .396 1.002 .997 1.007 General Determination -.004 .003 1.327 1 .249 .996 .990 1.003 Goal Striving -.004 .003 1.190 1 .275 .996 .989 1.003 Social Activity -.003 .002 1.512 1 .219 .997 .993 1.002 Social Connection .004 .003 2.059 1 .151 1.004 .999 1.009 Steadiness -.001 .002 .237 1 .626 .999 .995 1.003 Study Skills .000 .003 .032 1 .859 1.000 .995 1.005 Constant -3.643 2.353 2.398 1 ..121 .026
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Conclusion
The purpose of this chapter was to provide results from statistical analyses
examining the degree of relationship between gender, age, ethnicity, socioeconomic
status, high school class rank, college admission test scores, selected psychosocial
factors, first semester college GPA and persistence to the second year of college
coursework. Correlation, linear regression, and logistic regression results were included
showing the relationships of the predictor variables to the variance in college GPA and
the probability that participants would persist to the second year of coursework. The
results of the study are summarized below.
1. High school rank, ACT and SAT college admission test scores, along with the
Engage social skill Academic Discipline offered the best explanation of the
variance in Performance, accounting for 14.28%, 10.69%, 9.92%, and
6.25%.of the variance in College GPA, respectively.
2. Logistic regression performed to ascertain the effects of traditional and non-
traditional indicators on the likelihood that participants would persist in college
explained 11.4% of the variance in persistence among ACT takers and 9.5%
of the variance in persistence among SAT takers.
3. Regarding persistence and among sample participants who submitted ACT
results for admission consideration, increasing Social Connection, Academic
Discipline and ACT scores above the mean were associated with increased
likelihood of persistence by factors of 1.0, 1.01 and1.02, respectively. Male
students were 29.1 times more likely to return, and those who were Pell Grant
eligible were 46 times less likely to return. Among the participants who
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submitted SAT results for admission consideration, increasing high school
rank, SAT, Academic Discipline, and Commitment to College scores were
associated with an increased likelihood of persistence by factors of 1.02%,
1.0, 1.0, and 1.0, respectively. Similar to ACT takers, male participants who
took the SAT were 21 times more likely to return after the first year of college.
Conversely, increased Academic Self-Confidence scores were associated
with an increase in non-persistence by a factor .005.
These findings are consistent with the literature that suggests academic factors
are the best predictors of college academic performance and persistence but that
consideration of psychosocial factors can add value as well. For example, Larose and
Roy (1991) found that high school GPA was the best predictor of academic
performance for the total student population. Additionally, Mathiasen (1985) concluded
from his meta-analysis of 60 studies that in addition to academic performance in high
school and on college entrance exams, skills related to motivation and achievement
(study skills, academic discipline) positively impact college success. Ting (2000) was
specifically interested in persistence and in his study of Asian American students, he
concluded that, “students who have a realistic self-appraisal system recognize the
social environment of the campus, understand ways to work through the existing system
(and are) more likely to remain on the same campus” (p. 447). Self-appraisal is related
to the Engage theme of Academic Discipline because it involves the ability to set goals
and navigate past potential obstacles that would impede persistence.
Ultimately, the findings provide useful information for university administrators
and K-12 educators by identifying attributes of students more likely to succeed in
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college and those who will need greater attention and support. Equipped with this
information, K-12 educators can better prepare students for college success by
addressing both their academic preparation and the motivational factors that influence
Academic Discipline. University leaders can better select students by analyzing both
traditional and non-traditional indicators of college success and they can support more
students toward college level success by adapting support programs to target the
unique academic, psychosocial, financial, and gender related needs of students.
Chapter 5 reviews the study’s purpose, methods, and findings, offers discussion of the
study’s results.
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CHAPTER 5
DISCUSSION
Introduction
This study considered prior research related to academic and psychosocial
factors that influence first-year college students’ academic performance and persistence
to the second year of study. The objective was to determine the predictive power of
specific academic and non-academic factors on the outcomes of college level
achievement and persistence so that, when armed with this knowledge, educators at all
levels could best prepare and support students toward their goals of college graduation.
In this chapter, the results are discussed regarding the relevancy of participants’ high
school class rank, ACT/SAT scores, and psychosocial factors identified by the ACT
Engage in predicting college achievement and persistence. An interpretation of the
study findings, applications for educators, and implications for further study are
presented.
Statement of the Problem
The purpose of this study was to determine how high school students can
become better prepared to achieve academically and to persist to graduation from
college, and how university leaders can better support students in this process. It is
clear that the attainment of a college degree holds great promise for individual citizens
and for our nation’s economy, which include the benefits of greater employment, greater
pay, and increased insulation against an economic recession (Greenstone & Looney,
2011; Leonhardt, 2010). It is also evident that high school students continue to struggle
with achievement and persistence at the university level (Greene & Forester, 2003;
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National Center for Education Statistics, 2010). This study was conducted due to the
conflicting findings of research recommending the prioritized use of academic predictors
of college achievement and persistence based on earlier work by Larson and Scontrino
(1976), McDonald & Gawkowski (1976), Ting (2000), Geiser & Santelices (2007),
Richardson, Abraham & Bond, (2012), Willingham (2013), and other findings indicating
that non-academic factors also play an important role in students’ preparation
(Pascarella & Terenzini, 2005; Tinto & Pusser, 2006; Conley, 2007; DeBerard et al.,
2004). This study was based on the expectancy theory developed by Victor Vroom
(1964) that links human behavior to individual characteristics such as personality, skills,
knowledge, and experience, and his belief that one’s motivation to achieve is a product
of the factors of expectancy, instrumentality, and valence. Two research questions were
investigated in order to provide clarity around the important issue of students’
preparation for, and persistence toward, college graduation.
Discussion of Results
Statistically significant findings related to the identified research questions have
resulted from this study. Specifically related to Vroom’s expectancy theory, results
indicated that students who have the skills to succeed academically are more motivated
to achieve and persist in college. This section provides interpretation of study findings
with reference to existing research, applications for educators and suggestions for
further study.
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Interpretation of the Findings
This study was designed to determine the relationship between traditional
(academic) and non-traditional (psychosocial) indicators of college readiness and
measures of college performance (first semester GPA) and persistence (enrollment in
the second year of courses). Variables were selected for inclusion in the study as a
result of the review of literature in Chapter 2. Specifically, the dependent variables were
selected for study because first-year college GPA is a comprehensive indicator of
academic achievement as it reflects the grades students earn in their courses. Further,
first-year grades in college, in particular, are correlated to continued academic
achievement and likelihood of persistence toward graduation (Driscoll, 2007). “Grades
have traditionally been viewed as the most important indicator of college performance
and have been used as a criterion in psychological literature for almost a century”
(Lounsbury, Fisher, Levy, & Welsh, 2009 as reported in Krumrei, Newton, Kim & Wilcox,
2013, p. 4). In addition, levels of attrition for existing students have become one of the
measures of effectiveness used by state and federal political leaders to justify increases
or decreases in university funding and the retention of students continues to be one of
the most challenging issues for university leaders (Berger & Lyon, 2005; Dougherty,
Natow, Bork, & Vega, 2010). Independent variables were carefully identified to align
with the current research base that indicates aptitude (Willingham, Lewis, Morgan, &
Ramist, 1990), demographic (Pascarella, Pierson, Wolniak, & Terenzini, 2004), and
psychosocial factors (Chemers, Hu, & Garcia, 2001) are useful in predicting college
success (Robbins et al., 2004).
Study results related to Research Question 1 identified both traditional and non-
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traditional predictors of college readiness relevant to participants’ academic
performance in college. Regression analysis indicated that high school class rank,
scores on national college admission exams such as the ACT and SAT, and the
psychosocial skill Academic Discipline were the strongest prediction of first-year college
academic performance.
Study results related to Research Question 2 were less definitive however.
Although both traditional and non-traditional predictors were found to be relevant to
academic persistence in college, results of the logistic regression model used for this
analysis indicated that few of the variable relationships were particularly strong.
Increases in Academic Discipline and ACT/SAT scores were all associated with
increases in persistence, while among that SAT takers, increases in high school class
rank, and Commitment to College were also associated with increases in persistence.
This finding is consistent with prior research showing a positive relationship between
high school academic performance, scores on college admission exams and Academic
Discipline and persistence in college. Geiser and Santelices (2007) conducted a
longitudinal analysis of student achievement and found that high school GPA was
consistently the best predictor of college grades, and Richardson et al. (2012)
determined that in addition to high school grades and ACT/SAT scores, effort regulation
(Academic Discipline) (r = .31) was statistically significantly correlated to college GPA.
Similarly, Robbins, Allen, Casillas, Peterson, & Le (2006) studied psychosocial factors
and their relationship to college outcomes, and concluded that Academic Discipline (r =
.28, r = .13) and Commitment to College (r = .12, r = .12) were statistically significantly
correlated to college performance and persistence, respectively.
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Relationship to Research
Chapter 2 identified important literature findings related to state and national
policies emphasizing high school graduates’ readiness for college, the predictive nature
of traditional and non-traditional indicators of college readiness, and the ACT Engage as
a measure of psychosocial skill development. This study compliments the findings of
prior research related to indicators of college level academic achievement, and
suggests opportunities for future research regarding factors that most influence
persistence.
In response to Research Question 1, study results regarding the predictive
nature of traditional indicators of college-level academic achievement aligned with the
results of prior research. In this study, prior academic performance, as measured by
high school class rank and ACT/SAT college admission exams, explained the greatest
amount of variance in students’ performance during the first semester of college. These
findings support prior research from the last 35 years regarding the validity of using high
school class rank and standardized tests to predict college outcomes. (Larson &
Scontrino, 1976; McDonald & Gawkowski, 1976; Ting, 2000; Geiser & Santelices, 2007;
Willingham, 2013; Richardson et al., 2012).
The measurement of non-academic factors is also supported in the literature and
was cited as relevant information that should be considered in addition to test scores
when making admission decisions (US Department of Education, Office of Civil Rights,
2000). Study results regarding the importance and predictive nature of non-traditional
indicators of academic achievement, most notably Academic Discipline, also aligned
with prior research (Robbins et al., 2004; Robbins et al., 2006). Academic Discipline
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was found to explain 6.25% of the variance in College GPA and, although it was not as
strong a predictor as high school rank or ACT/SAT scores, it nonetheless provides
important insight when evaluating students’ readiness for college-level work.
Considering nonacademic and academic factors can only strengthen the admission
review process.
In response to Research Question 2, study results regarding the predictive
nature of traditional indicators of college-level persistence aligned with the results of
prior research. In this study, prior academic performance, as measured by high school
class rank (r = -.16) and ACT/SAT college admission exams (r = -.12), explained the
greatest amount of variance in students’ persistence to the second year of university
study. These results are consistent with findings by DeBerard et al. (2004) where
logistic regression of traditional and non-traditional predictors of college success also
indicated the greatest (although slight) correlation existed between high school
academic performance and persistence (r = -.20). When examining the non-traditional
predictors of college readiness as related to Research Question 2, the only non-
traditional indicator of college readiness with a statistically significant relationship to
persistence was Academic Discipline (r = -.12). Although these results challenge the
findings of Gerdes and Mallinckrodt (1994) who determined that emotional and social
adjustment factors predicted (persistence) as well or better than academic factors, they
align closely with the work of DeBerard et al. (2004) and Robbins et al. (2006).
Despite these similarities in study findings however, the fact remains that there
are few statistically significant traditional or non-traditional predictors of persistence, and
those that are statistically significant all produced very low correlations. Study results
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were not significant for six of the seven non-academic Engage themes included for
analysis. Thus, this model supports the findings of Garton, Dyer and King (2000) who
determined that, “(traditional and non-traditional) criteria used for college admission of
students are a good predictor of academic performance, but (have) limited power and
value as a predictor of student (persistence)” (p. 52), “(Persistence) is a complicated
construct that (remains) difficult to predict,” (DeBerard et al., 2004, p. 66) the original
research question seeking to identify statistically relevant predictors of persistence
among university freshmen remains relevant for further study.
Application for K-16 Educators
The results of this study are aligned with those of prior studies and have strong
implications for K-16 educators dedicated to helping all students achieve the benefits of a
post-secondary education. Study results provide individual students, high school teachers
and university educators with two areas for application focus:
1. The positive correlation between high school class rank and ACT/SAT scores and
college success evidences the need for the preparation of all students for post-
secondary education through an academically challenging and strongly aligned
K-16 instructional program.
2. The positive correlation between the skills measured by the ACT Engage,
especially Academic Discipline, and college success evidences the need for
teaching students to be aware of and improve their psychosocial abilities, and for
the creation of support programs that address students’ Academic Discipline.
Efforts by educators at all levels to improve students’ academic knowledge and Academic
79
Discipline so that college level performance and persistence also improve, should consider
the following:
Actions Designed to Increase Students’ Academic Preparation
1. Improve students’ academic preparation through a tightly aligned academic
program that exceeds state, national, and international standards (Bangser,
2008; Conley, 2010; Savitz-Romer, Jager-Hyman & Coles, 2009; Texas
Education Agency, 2008),
2. Implement a graduated system of assignments and grading policies that evolve to
be more like that in college by the time students are seniors in high school.
Require increasingly more complex assignments that teach key cognitive
strategies (Conley, 2011),
3. Design policies that require high school students to select academically
challenging and individually engaging courses including Advanced Placement,
International Baccalaureate, and Dual Credit (Mattern, Xiong, & Shaw, 2009;
Conley & Ward, 2009; Dougherty, Mellor, & Jian, 2006; Hargrove, Godin, & Dodd,
2008).
Actions Designed to Increase or Support Students’ Application of Psychosocial Skills, Especially Academic Discipline
1. Promote opportunities for students to take more ownership of their learning as
they progress through high school and teach key academic behaviors such as
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organization, time management, and study skills consistently and systematically.
(Conley, 2011)
2. Provide students with opportunities to take on higher-order or long-term goals
that are “worthy” to the student—goals that are “optimally challenging” and
aligned with the students’ own interests, and provide a rigorous and supportive
environment for accomplishing their goals. Rigorous and supportive learning
environments should instill high expectations, a growth mindset, expectations for
challenge and early failure, cycles of constructive feedback and iteration, and a
sense of belonging, as well as support for strategies to plan, monitor, and stay on
track. (Shechtman, DeBarger, Dornsife, Rosier, & Yarnall, 2013),
3. Identify at-risk students as early as possible using multiple sources of information.
The ACT Engage is an essential tool for early identification and should be
administered at the middle school, high school and college levels to begin
developing students’ awareness of and competency in each of the psychosocial
skill areas that impacts college success. Interventions at each level should be
designed to support the “whole student” and outcomes should be tracked using a
crosswalk of support services aligned to the individual needs of students
(Casillas, 2010).
4. Create a data driven support system that addresses the psychosocial needs
of the incoming class of students. Such a system should include (Habley &
McClanahan, 2004):
• Short- and long-term goals for student retention, progression, and
completion
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• A clear referral system designed and widely understood so students
are matched with appropriate opportunities for programs and events
• Advising interventions with selected students populations
• An academic advising center with increased advising staff
• A comprehensive learning assistance center and supplemental
instruction
• A summer bridge program and freshman seminar
These recommendations align with the work currently being done in Texas through local
P-16 partnerships between school districts and university leaders and organized
through a statewide framework established by the Texas Higher Education Coordinating
Board (THECB). Now, more than ever, due to recent legislative changes outlined in
Texas’ House Bill 5 and passed in 2013 by the 83rd legislature, educators’ efforts must
focus on developing students’ academic and psychosocial skills through readiness and
support initiatives similar to those recommended above and enacted through these P-16
partnerships. Results from this study and others offer the support necessary for local
and state leaders to continue to promote these efforts.
Suggestions for Further Study
While this study confirmed that traditional measures used in the university
admission process (HS Rank, ACT/SAT scores) are statistically relevant predictors of
academic achievement, results also pointed to the value of considering non-traditional
predictors of academic performance, such as Academic Discipline as measured by the
ACT Engage, as well. Results related to persistence were not as definitive. Perhaps this
82
is because the variables selected for this study are measures of student’s academic and
interpersonal strengths prior to entering college. Once a student is in college, there are
myriad influences that impact persistence, namely the quality of instruction and the
support systems that are available. GPA also influences persistence (Cabrera,
Castaneda, Nora, & Hengstler, 1992; Mangold, Bean, Adams, Schwab, & Lynch, 2003;
O’Brien & Shedd, 2001). Ishitani and DesJardins (2002), for example, found that the
higher a student’s first-year GPA, the less likely that student was to drop out of college.
Knowing that academic and social expectations and influences change significantly
during the course of the first year of university study, further study is warranted to
determine other variables that might have more significant predictive power regarding
persistence. Additionally, since results of this study indicated a significant relationship
between gender and persistence, with female freshmen approximately 21% - 29% less
likely to return for a second year of study, and socio-economic status and persistence,
with ACT takers who were also Pell Grant eligible 46% less likely to return for their
second year of study, more analysis would be warranted here as well.
Conclusion
This chapter reviewed the results of this study regarding the predictive power of
traditional (HS Rank and ACT/SAT scores) and non-traditional (ACT Engage themes)
indicators of college readiness regarding college students’ performance and
persistence. This study was based on the understanding that the attainment of a college
education provides numerous benefits to individual graduates and to the collective
national economy as well. Namely, a college degree better prepares individuals for the
changing and increasingly more competitive jobs market and can lead exponentially
83
increased economic prosperity. As the number of citizens attaining a post-secondary
education increases, so does the number of people who are better able to meet the
creativity and technology demands of the 21st century economy. This in turn, leads to
increased economic prosperity and global competitiveness for the nation as a whole.
Further, because of the evolving understanding among K-16 educators regarding what
skills and knowledge are necessary for high school graduates to be sufficiently prepared
for the demands of a post-secondary education, and because of the increased pressure
being placed on university leaders to increase graduation rates and decrease the time
required to graduate, identifying the most accurate measures college performance and
persistence becomes even more important.
Although study results related to college persistence did not yield conclusive
evidence on the predictive power of traditional or non-traditional indicators of college
readiness, they did support prior research findings that traditional indicators of college
performance including high school class rank and college admission test scores on the
ACT or SAT are stronger predictors of students’ performance in college. This study also
determined that measuring psychosocial factors, especially Academic Discipline, can
provide university leaders with important additional information necessary for increasing
the number of students who matriculate successfully toward graduation. Suggestions
for applicability of the study results to the work of K-16 educators were provided in an
effort to increase the number of students who are academically and interpersonally
prepared for success in college.
84
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