APPROVED:

Pu-Shih Daniel Chen, Committee Chair

Ronald Newsom, Committee Member

Gwenn Pasco, Committee Member

Janice Holden, Chair of the Department of

Counseling and Higher Education

Jerry Thomas, Dean of College of Education

Mark Wardell, Dean of the Toulouse

Graduate School

LISTENING TO THE FRESHMAN VO ICE: FIRST-YEAR SELF-EFFICACY

AND COLLEGE EXPECTATIONS BASED ON HIGH SCHOOL TYPES

Paul B. May, B.S., M.Ed., M.S.

Dissertation Prepared for the Degree of

DOCTOR OF PHILOSOPHY

UNIVERSITY OF NORTH TEXAS

May 2013

May, Paul B., Listening to the Freshman Voice: First-Year Self-Efficacy and

College Expectations Based on High School Types. Doctor of Philosophy (Higher

Education), May 2013, 117 pp., 11 tables, references, 236 titles.

This quantitative study used Astin’s I-E-O theory to explore the relationship

between a college freshman’s high school background and academic self-efficacy. The

Beginning College Survey of Student Engagement was used to measure academic self-

efficacy across four types of high schools. Student gender and precollege experiences

(dual-credit and communication assertiveness) were used as control. A total of 15,400

first-year students were included in this study. An ANOVA was used to examine the

differences between groups, and ordinary least-square analysis was used to study the

factors that affect academic self-efficacy. Results showed statistically significant

difference in academic self-efficacy between public and private religious high school

graduates. Specifically, graduates of public high schools had statistically higher academic

self-efficacy than graduates of private religious high schools (p < .001). Additionally,

females and participants of dual-credit courses also tended to have higher academic self-

efficacy. Finally, analysis revealed that a first-year student’s communication confidence

is highly correlated to their academic self-efficacy. Results confirm in-coming first-year

students perceive higher education engagement differently based on traits attributed to

their precollege experiences. Results point to criteria colleges may be able to use in

identifying freshmen at risk for low academic self-efficacy and, therefore, for problems in

retention and degree completion.

ii

Copyright 2013

by

Paul B. May

iii

ACKNOWLEDGMENTS

My committee composed of Dr. Pu-Shih Daniel Chen, Dr. Ron Newsom, and Dr. Gwenn

Pasco

The-late Dr. John Gossett, University of North Texas--Communication Studies

Dr. Stephen G. Katsinas

Colleagues and encouraging students at Paris Junior College, Paris, Texas

Jim Cole and the Beginning College Survey of Student Engagement staff

My “A” Team (J, K, B, D, and “man’s best friend”) for the company and support you

provided

Bob Perry

Erma Dean Burkhead May: mother, inspiring educator, and wonderful mentor. You left

this world for a better place. I miss you, Mom.

Philippians 4:13

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TABLE OF CONTENTS

Page

ACKNOWLEDGMENTS ............................................................................................................. iii  

LIST OF TABLES ........................................................................................................................ vii  

CHAPTER I INTRODUCTION ..................................................................................................... 1  

Background of the Study .................................................................................................... 2  Post High School Psychosocial Behavior ............................................................... 2  Academic Self-Efficacy .......................................................................................... 4  High School Classification ..................................................................................... 4  Gender ..................................................................................................................... 5  Confident Communication ...................................................................................... 5  Concurrent Enrollment in High School and College Classes ................................. 6  

Statement of the Problem .................................................................................................... 6  Purpose of the Study ........................................................................................................... 7  Research Questions and Related Hypotheses ..................................................................... 7  Research Hypothesis ........................................................................................................... 8  Significance of the Study .................................................................................................... 8  Conceptual Framework ....................................................................................................... 9  

Astin’s Theory ........................................................................................................ 9  Albert Bandura’s Self-Efficacy Theory ................................................................ 11  

Definition of Terms ........................................................................................................... 15  Limitations ........................................................................................................................ 18  Delimitations ..................................................................................................................... 18  Assumptions ...................................................................................................................... 19  Organization of the Remainder of the Study .................................................................... 19  

CHAPTER II LITERATURE REVIEW ...................................................................................... 20  

Educational Transition from High School to College ....................................................... 20  The High School Graduate ................................................................................................ 22  Transition and Engagement .............................................................................................. 22  Trends of Change .............................................................................................................. 24  New Directions in Research on Students .......................................................................... 26  Kuh’s Theory of Expectations and Perceptions ................................................................ 27  Acquiring College Knowledge: Transition-Ready (or Not) ............................................. 28  Academic Self-Efficacy .................................................................................................... 29  Self-Efficacy in Survey Instruments ................................................................................. 32  

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Independent Variables ...................................................................................................... 32  The Historical Transition to College and Four High School Types ..................... 32  The Lingering Effects of High School on the First Years of College .................. 34  Public School ........................................................................................................ 36  Private School ....................................................................................................... 37  Religious School ................................................................................................... 38  Home School ......................................................................................................... 39  Types of Schools Related to This Study ............................................................... 40  

Student Characteristics—Independent Variables ............................................................. 42  Dual Credit ............................................................................................................ 42  Dual Credit Related to this Study ......................................................................... 43  Gender ................................................................................................................... 44  

Gender Related to This Study ........................................................................................... 45  Communication ................................................................................................................. 47  

Communication Confidence ................................................................................. 47  Communication Confidence, Self-Efficacy, and High School Students .............. 48  Communication as it Relates to This Study .......................................................... 49  

Summary and Conclusions ............................................................................................... 50  

CHAPTER III METHOD ............................................................................................................. 52  

Research Design ................................................................................................................ 52  Nature of the Study ........................................................................................................... 52  Population and Sample Description .................................................................................. 53  Sample ............................................................................................................................... 53  Confidentiality .................................................................................................................. 54  Instrumentation ................................................................................................................. 54  Data Preparation ................................................................................................................ 56  Data Analysis Procedures ................................................................................................. 57  

Research Question 1 ............................................................................................. 57  Research Question 2 ............................................................................................. 58  Research Question 3 ............................................................................................. 59  

CHAPTER IV RESULTS ............................................................................................................. 60  

Descriptive Statistics ......................................................................................................... 60  High School Type ................................................................................................. 60  Gender ................................................................................................................... 61  Dual Credit ............................................................................................................ 62  

Research Question 1 ......................................................................................................... 62  Research Question 2 ............................................................................................. 64  A Second Model of Prediction .............................................................................. 66  Research Question 3 ............................................................................................. 67  

Summary of Findings ........................................................................................................ 67  

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CHAPTER V DISCUSSION ........................................................................................................ 69  

Summary of Data, Methods, and Results .......................................................................... 69  Results of the Research Questions .................................................................................... 70  

Gender ................................................................................................................... 73  Precollege Experiences Involving Dual Credit Coursework ................................ 74  

Conclusions ....................................................................................................................... 77  Implications for Practice ....................................................................................... 78  Implications for Research ..................................................................................... 81  

The Final Word ................................................................................................................. 83  

APPENDIX A 2009 BEGINNING COLLEGE SURVEY OF STUDENT ENGAGEMENT BENCHMARKS ....................................................................................................... 85  

APPENDIX B PERCENTAGES WITHIN BCSSE 2009 FACTORS RELATED TO THIS STUDY ...................................................................................................................... 87  

APPENDIX C DUMMY CODING FOR MULTIPLE REGRESSION ANALYSIS .................. 89  

APPENDIX D IRB APPROVAL ................................................................................................. 91  

REFERENCES ............................................................................................................................. 93  

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LIST OF TABLES

Page

Table 1 Flow Chart of Theorists’ Typologies and Descriptors of Precollege Academic

Settings .................................................................................................................................. 25  

Table 2 Institutional Type Breakdown of Participants, BCSSE, 2009 ......................................... 53  

Table 3 Composite of BCSSE Test Items and the Research Domain to be Measured ................. 58  

Table 4 Frequency Table for Type of School ............................................................................... 61  

Table 5 Frequency Table for Gender ............................................................................................ 61  

Table 6 Frequency Table for Participation in Dual Credit Opportunities .................................... 62  

Table 7 Descriptive Statistics for Academic Self-Efficacy by Type of School ............................ 63  

Table 8 One-factor ANOVA results for academic self-efficacy .................................................. 63  

Table 9 Post-Hoc Tukey test results for Academic Self-Efficacy ................................................ 64  

Table 10 Multiple Regression Results—Initial Model ................................................................. 65  

Table 11 Multiple Regression Results—Final Model .................................................................. 66  

1

CHAPTER I

INTRODUCTION

How sad to think that the exhilaration about starting college has been muted by a tendency to portray the first year as a gauntlet to survive or a tragedy waiting to happen.

—R. Bonfiglio

Thousands of students make the transition from high school to college every year. In

1994, the National Center for Education Statistics (NCES) counted 2.14 million college students

enrolled for the first year of courses. By 2000 that number grew to 2.4 million, and in 2008 the

number surpassed 3 million (NCES, 2008). Understanding high school graduates’ expectations,

attitudes, and perceptions provides college administrators with a picture of the high school

experience and assists them in promoting college success (McCarthy & Kuh, 2005; Schneider &

Ward, 2003; Tinto, 1993, 2012). Aside from contributing to students’ expectations of college

learning, high schools are expected to prepare all students for success in college and the work

force, fulfilling a public expectation that all high school graduates can go to college (Bushaw,

2011; Palmer, 2000). However, some students manage the transition from high school to the first

year of college differently and more easily than others (M. Ishler, 2005; Kuh, 2005; Richmond,

2011; Seidman, 2005).

Aspirations for higher education are climbing faster today than in the last century

(Education Week, 2009; Kuh, Kinzie, Schuh, & Whitt, 2005). Along with access, students have

an expectation for change from the regimens of compulsory education and desire an environment

and experience beyond just new knowledge (Mayhew, Stipeck, & Dorow, 2011; Toutkoushian &

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Smart, 2001). This quantitative study explored the effect of precollege experiences on the

academic self-efficacy of college freshmen. Results from the 2009 Beginning College Student

Survey of Expectations (BCSSE) administered by the Indiana University Center for

Postsecondary Research were used to identify the strength of academic self-efficacy and patterns

of precollege experiences across four types of high school environments (public, private,

religious, home school). Based on data from the BCSSE, the variables studied were gender,

confident communication, and dual credit enrollment in high school and college classes.

Background of the Study

The desire for new experiences creates differences in the manner in which new college

students manage the transition from compulsory education to education driven only by free will

(H. Adelman & Taylor, 2002; Greene, 1989). C. Adelman (2006) argued that early exposure to

college life through discussions at home, concurrent coursework in high school and college, and

peer interactions eases the transition. The effect of pre-college experiences of high school

graduates who come from different types of high schools is often overlooked when the student

arrives on campus (Boyer, 1987; Upcraft, Ishler, & Swing, 2005; Wen & Cole, 2009). Because

high school plays an important role in readying students for college, first-year students from

different types of high schools may inherit unique social and academic self-efficacy traits

(Coleman & Hoffer, 1988; Duggan, 2010) leading to differences in their psychosocial behavior

and ultimately, success.

Post High School Psychosocial Behavior

Astin (1993), and Pascarella and Terenzini (1991, 2005) concluded that the college

learning setting makes a significant difference in the development of individuals after high

school. The psychosocial development does not happen in a vacuum because of the lingering

3

influence of high school experiences that predispose students to a particular way of behaving

(Kuh & Whitt, 1988). However, current practice in higher education is to treat incoming first-

year college students as a homogenous cohort (Duggan, 2010; Kuh, 2003b; Tinto, 2003). This

practice is problematic because students from various types of secondary schools may have

different needs with which to become educationally engaged in college coursework (Boyer,

1987; T. Jenkins, 1998; Ruban & McCoach, 2005).

Astin and Lee (2003) contended that institutions must engage students at the intersection

of the transition into the freshman year. In institutions where first-year college students are

assigned to a unique course for college success and retention, the practice largely disregards the

precollege environment and incoming educational expectations. This disregard for the

uniqueness of first-year college students results in problems when students are adjusting to the

college environment (Bonfiglio, 2006; Boyer, 1987); thus, this study addressed a need for a more

comprehensive understanding of the differences among entering freshmen cohorts.

Studies had shown that as adolescents age, their disengagement with school increases,

while their disaffection with specific subjects increases (Eccles, Wigfield, & Schiefele, 1998;

Haladyna & Thomas, 1979; Hoffmann & Haussler, 2002). Students’ disengaged attitudes toward

education in general spawns academic difficulties and hinders high academic achievement in

particular (Fordham, 1999; Mickelson, 1990; Ogbu, 19816; Ogbu & Simmons, 1998). Olsen and

Maio (2003) argued that past attitudes can influence the formation of present attitudes, which can

make change difficult. Bempechat (1998) characterized this condition as a “lack of persistence, a

preference for easy tasks over challenging tasks, or a tendency to fall apart at the first sign of

difficulty” (p. 37), which has a negative effect on student achievement..

4

Academic Self-Efficacy

A student’s academic self-efficacy affects both work habits and the relationship between

success and failure. Covington (1998) stated, “One’s self-worth often comes to depend on the

ability to achieve competitively” (p. 78). Thomas (2000) associated self-efficacy with attitude

about learning. Thomas argued that attitude about learning is academic self-efficacy. Using grade

point average (GPA) as a measure of achievement, Thomas found “indirectly, motivation and

positive attitudes about mathematical ability tend to be linked to achievement through

participation in academic activities” (p. 165). Thus, a matriculating student’s engagement in past

meaningful educational activities is reflected in his or her perceptions of academic self-efficacy.

Since 2000 an emphasis on understanding first-year students has emerged at many

colleges (Zychowski, 2007). Zychowski examined empirical data about first-year students and

found that academic self-efficacy emerged as a significant predictor of student engagement and

institutional attachment. Similarly, Pascarella and Terenzini (2005), and Chickering, Chickering,

and Lindholm (2010) reported that college aspirations, engagement, and persistence related back

to the environment and “cultural capital” of the student as early as the eighth grade.

High School Classification

Researchers have undertaken to understand, recruit, and orient high school graduates

from different types of high schools (Duggan, 2010; Sutton & Galloway, 2000). Within widely

established databases, high schools are largely classified into four types: public high school,

private college-prep, private-religious, and home school . Each of these high school types operate

with slightly different educational goals.

The following three sections summarize the relationship of the study variables to

academic self-efficacy. A more detailed discussion of the variables is in Chapter II.

5

Gender

The first variable tested in the present study was gender. The study of gender in the

context of higher education has produced conclusions related to classroom teaching, the career

decision-making process, as well as the policymaking convictions of student-affairs

professionals for many years (NCES, 2004b). The NCES presented data that females aspire to

advanced degrees in greater numbers than men. The finding is consistent with prior findings

from Bayer, Drew, Astin, Boruch, and Creager (1970) who reported higher attendance of

females and higher GPAs of degree-seeking females. Regarding the database used in this study,

the actual numbers of students taking the BCSSE (59% women, 41% men) reflect the saturation

of females (Beginning College Survey of Student Engagement [BCSSE], 2009).

Confident Communication

The second variable tested in the present study was confident communication. Confident

communication is a foundational piece of emotional intelligence and aids in the transition

process (Bates, 2009). Roueche and Mink (1976) found that students adjusting to college are

expected to possess the necessary verbal skills to succeed in a lecture-based classroom. Roueche

and Mink (1976) theorized that outward communication skills are a by-product of an internal

locus of control, which in turn has the power to affect change in a current situation; thus, past

experiences create an internal locus of control that affects changes in a student’s situation and

affects verbal and nonverbal communication traits. Roueche and Mink recommended

implementation of educational practices that foster assertive communicative. Clearly, past

interpersonal experiences create a judgment of abilities that affects changes in a student’s

situation and affects verbal and nonverbal communication traits.

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Concurrent Enrollment in High School and College Classes

The third variable in the present study is concurrent enrollment in high school and college

classes, which is also referred to as dual credit. For the purposes of the present study, the term

dual enrollment is used. Citing from the results of the 2009 BCSSE, two thirds of respondents

stated they had participated in college coursework prior to high school graduation. The results of

a 2009 study concluded that students with prior concurrent coursework had statistically

significant higher rates of postsecondary degree completion and took less time to complete a

Bachelor’s degree (Westcott, 2009). Kim (2006) found that concurrent enrollment provided a

positive impact on college readiness, most significantly in mathematics.

Dual-credit programs and classes are thought of favorably, but may encounter problems

in several ways. First, the request to transfer coursework to a higher education institution may

not result in automatic acceptance (Westcott, 2009). Another area of current concern is the

standardization of the college-level material (Zimmerman, 1995) due to a wide variation of

college classroom experiences for students in dual credit settings. In order to fix these problems,

higher education institutions should work together and encourage early college experiences that

allow first-year college students to enter college with at least 6 college credits (Adelman, 2006).

Statement of the Problem

Academic self-efficacy is related to high school type (Cole, 2010), and the high school

factors that account for the differences in academic self-efficacy are yet to be determined. A

review of the literature revealed an unbalanced and incomplete body of knowledge about the

factors that contribute to academic self-efficacy in students from different types of high school

environments, which may affect perceptions (Kersh & Masztal, 1998) and specifically may

affect academic self-efficacy. This quantitative study explored the effect of high school

7

experiences on beginning college freshmen’s academic self-efficacy. Cole and McCormick

(2009) asserted that school environments should be examined for their influence on the

perceptions of college-motivated students as college administrators often fail to pay attention to

academic self-efficacy and the unique markers that create academic self-efficacy levels in

graduates from different types of high schools.

Purpose of the Study

Graduates from different types of high schools have different levels of academic self-

efficacy as measured by three indicators on the BCSSE, (a) perceived academic preparation, (b)

expected academic difficulty, and (c) expected academic persistence (Cole & McCormick, 2009).

Results from the 2009 BCSSE administered by the Indiana University Center for Postsecondary

Research were used to identify the strength of academic self-efficacy and patterns of precollege

experiences across four types of high school environments (public, private, religious, home

school). Three variables based on the BCSSE data were explored: gender, confident

communication, and dual credit (past enrollment in high school and college classes). The

purpose of the study was to investigate the effects of a college freshmen’s prior high school type

on perceived academic self-efficacy and college-experience expectations. This study also

provided an opportunity to look at the impact of gender, confident communication and dual

enrollment in high school and college classes on academic self-efficacy, and which types of high

schools are graduating students with the highest levels of academic self-efficacy.

Research Questions and Related Hypotheses

Based on the discussion in the previous sections, the following research questions and

related hypotheses guided the study:

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RQ1. Do first-year college students from different high school types (public, private

religious, private college-prep, home school) differ in their academic self-efficacy?

RQ2. To what extent are gender, dual credit coursework, and type of high school

attended contributors to a first-year college student’s academic self-efficacy?

RQ3. Is there a relationship between measures of academic self-efficacy and perceived

communication confidence?

Research Hypothesis

1. Hypothesis: A student’s perception of preparation for beginning the freshman year

will be different according to the type of high school attended.

2. Hypothesis: Gender, dual credit coursework, and/or type of high school will increase

the level of a first-year college student’s academic self-efficacy.

3. Hypothesis: There is a relationship between measures of academic self-efficacy and

perceived communication confidence .

Significance of the Study

The results of the current study are beneficial to both college administrators and high

school counselors. Results are informative to college administrators and faculty using better

practices regarding the treatment of incoming first-year students. High school counselors will

find data that indicates a need for improving academic self-efficacy among their college-bound

students. By capturing the students’ expectations in the first days of arriving on college

campuses, high school administrators and college faculty can adjust college-readiness

assessments and shape successful degree-completion attitudes in the minds of beginning college

students (Chemers, Hu, & Garcia, 2001). Results of the study inform policy makers and high

school teachers and counselors of possible potential issues in the transition from high school to

9

college regarding gender, confident communication, and concurrent enrollment in high school

and college classes. Results answer questions in the unique nature of the first-year college

student (Boyer, 1992; Kirst & Bracco, 2004; Upcraft, Gardner, & Barefoot, 2005) and inform

educators, policy makers, and administrators about how to better assist students to succeed in

college (Hill, 2012).

Conceptual Framework

Two theories guided this study: Alexander Astin’s Input-Environment-Output model, and

Bandura’s self-efficacy theory. Both are derived from the larger domain of psychosocial change

(E. H. Erikson, 1959; Stevens, 1983).

Astin’s Theory

Astin’s theory-based input-environment-output (I-E-O) model was the framework for an

extraordinary volume of research. Pascarella and Terenzini (2005) noted that the application of I-

E-O is widespread. Astin has been cited in numerous studies involving effects of college on

students. Astin’s I-E-O model (1970) first raised the prospect that differences exist in types of

high school environments. Weidman (1989), citing Chickering (1967) and Astin (1970),

hypothesized that college students bring important background characteristics and pressures from

parents and school into the college experience. These key and other characteristics shape

individual forces and predispose students toward choices in college settings (W. L. Smith &

Zhang, 2010). Based on Astin’s theoretical model, inputs are the characteristics that describe past

environmental influences on entering first-year students. This descriptor is among the

characteristics broadly known as precollege experiences in similar research domains (Braxton,

2000; Kuh, 2003a; Pascarella & Terenzini, 2005; Tinto, 1993).

10

Astin (1993) included a pre-college input variable, “From what type of high school did

you graduate?,” in the Cooperative Institutional Research Program (CIRP, 2008) Freshman

Survey. Over the years, Astin utilized CIRP to study 146 other entering variables of which 86

were directly related to past educational occurrences. The variables in the body of Astin’s work

relate directly to this study as ‘prior learning experiences,’ specifically high school environments.

Environment is the second component of the I-E-O model (Astin, 1970) and is related to

the first-year student with the campus and educational activities. For example, research has

shown that student-faculty interaction increases satisfaction and decreases attrition (Astin, 1993;

Braxton, 2000; Tinto, 1993). Astin (1993) noted that for some first-year students, the college-

going experience will be “the first intensive encounter with persons who have markedly different

beliefs” (p. 8). These interactions with the college environment produce changes in student

aspirations, values, and beliefs.

The third and final component of Astin’s (1970) I-E-O model was outcomes. Astin

described outcome as growth or change after the college experience concludes. In studies

reviewed by Pascarella and Terenzini (2005), it was found that the lingering effects of high

school environmental inputs existed throughout the first year and disappeared by the fourth year

of college. Although challenging students to perform at optimum levels is tricky and complex,

higher education institutions should take student’s academic background seriously in the success

equation (Mayhew, Seifert, & Pascarella, 2012).

The present study and its results focus on the first two components of Astin’s I-E-O

theory: inputs, and environment. The impact of high school experience on first year students’

transition into college was explored. The Foundations of Excellence’s Current Practices

Inventory (2010) called for studies that would (a) reveal aspects of differing academic

11

backgrounds, and (b) examine the intersection of first-year structures and procedures on a

specific sub-population of students. Astin noted in 1993 that experiencing higher education in an

environment oriented toward student development would show positive effects on attitudes and

bachelor’s degree completion.

W. L. Smith and Zhang (2010) utilized Astin’s input and environment domains to

examine the effect of college-going attitudes among first- and second-generation students in a

quantitative research design. W. L. Smith and Zhang noted high correlations between high

school staff and perceptions of what the college experience is like. Their findings revealed

important initial perceptions of college are built and swayed primarily by a student’s

conversations with parents, counselors, and college-orientation personnel. Controlling for initial

experiences in college, W. L. Smith and Zhang found that first-generation students received the

least amount of parental support, and yet, held academic notions on a par with second-generation

students.

Similarly, Kuh, Kinzie, Schuh, and Whitt (2005) found that “challenging students to

perform at optimal levels is tricky and complex” (p. 301). Kuh et al. asserted there is a distinct

need to accommodate students from a variety of backgrounds to “diversify the gene pool in

higher education” (p. 308). As a result of longitudinal studies of 20 highly effective colleges,

Kuh et al. recommended an alignment of policies, practices, and new programs designed to

assess first-year student’s academic preparation prior to other considerations.

Albert Bandura’s Self-Efficacy Theory

Albert Bandura was the pioneer of the self-efficacy construct based on social learning

theory, but he was not the first to examine the role of human agency. Determinism, or one’s

sense of control over future events, has existed for much of human history (Gecas, 1989).

12

However, Bandura’s semantic play in coining self-efficacy, its explanations, and applications has

produced a relatively new field of research in the past 30 years. With his seminal work Self-

efficacy Theory: Toward a Unifying Theory of Behavioral Change in 1977, Bandura’s research

posited the concept that one’s prior experiences predetermine a course of action for future events.

Those with strong self-efficacy beliefs are found to be more confident in their capacity to

execute needed behaviors in new contexts (Caprara, Alessandri, & Eisenberg, 2012), thus, the

nature of self-fulfilling prophesies in academic self-efficacy plays a predictive role at the

beginning of college as students face stress and uncertainty (Schunk & Pajares, 2001;

Zimmerman, 1995. “The construct of self-efficacy … is relevant to postsecondary academic

success as it is thought to influence the amount of effort put into performance of a task”

(National Survey of Student Engagement, 2007, p. 10).

Bandura (1977) stated that the source of academic self-efficacy originates in four

domains of one’s environment: vicarious events, communication from others, performance

accomplishments, and emotional arousal. Of these original concepts, two of Bandura’s

originating sources are central to academic self-efficacy in this study: a performance

accomplishment is represented in the variable “dual credit experiences” of students, and

communication is represented by the variable “communication confidence.” Cole (2010)

determined that high school type has a significant effect on first-year college expectations. Kuh

et al. (2005) found that precollege experiences impact student engagement practices, student

satisfaction, and success in degree programs. C. Adelman (2006) used longitudinal data to argue

that college students who complete the degree often maintain a healthy self-efficacy via college

savvy thought processes and the acquisition of college knowledge early, particularly before the

sophomore year of high school. C. Adelman in 1996 confirmed Boyer’s and Tinto’s basic

13

finding that the intensity and quality of a high school curriculum counts most in a self-

efficacious approach to degree completion.

Academic self-efficacy. Beliefs about one’s ability to move easily to the next challenge

are developed through major sources in life’s events. Individuals will evaluate their

competencies by way of successful experiences or performances. The effects of their actions

arrive by way of major and minor experiences (Pajares, 2002). Bandura (1997) stressed the

importance of school environment and that good schooling fosters psychological growth.

Through the environment “education should equip students with intellectual tools, interest in

education, and efficacy beliefs” (Bandura, 1997, p. 214). According to self-monitoring theories,

quantifying academic self-efficacy relies on the ability of the student to be self-observant, which

enables the individual to gauge the effects of actions (Pajares, 2002; Pajares & Schunk, 2001).

Self-monitoring alters behaviors by gaining the attention of the holder via internal belief systems

(Zimmerman, 1995). Yet another study indicated that self-efficacy can predict college-going

behaviors more than other traditional predictors, such as aptitude tests (Robbins, Allen, Casillas,

Peterson, & Le, 2006). In sum, self-efficacy can predict multiple academic outcomes (Bandura,

1977).

Expectancy constructs. Problems with self-efficacy research are related to attributes of

other expectancy constructs such as self-confidence (Pajares & Urdan, 1996). Chapter II of this

study will include a discussion of the differences and uses of self-efficacy and self-confidence.

Researchers have gone beyond the self-efficacy of students and have added theoretical

understandings of emotional intelligence (Astin & Oseguera, 2005; D. Nelson, Low, & Hammett,

2011) and interpersonal skills (Ando, 2011; Pike, 2006; Reason, Terenzini, & Domingo, 2007)

on academic self-efficacy and motivation. While acknowledging these expanded contributions,

14

this study focused only on the academic self-efficacy of first-time first-year college students

from the perception of past, present, and future actions. Self-efficacy remains high in the

predictive power of academic outcomes. This is a common theme regarding first experiences:

when middle-aged research subjects were asked to recall a significant memory from college,

25% related a memory from the first 3 months of the freshmen year (Pillamer, Goldsmith et

al.,1988).

Major transitions raise awareness of one’s abilities to abate threat (Chemers et al., 2001;

E. H. Erikson, 1959; Pritchard, Wilson, & Yamnitz, 2007) and the beginning of college is one

time that threat drives people to ‘read themselves’ or self-monitor (Zimmerman, 1995). Gecas

(1989) found that one’s self-efficacy changes over the course of a lifetime and has consequences

for successfully maneuvering many of life’s stressful events. Borkowski and Thorpe (1994)

noted “individuals who have high efficacy beliefs appear to have motivational patterns, self-

regulated capacities, and optimistic selves that will engender lasting achievement” (p. 66).

Finally, Bandura (1986) addressed self-efficacy during life changes and stressful transitions

when he posited “Students who develop a strong sense of self-efficacy are well-equipped to

educate themselves when they have to rely on their own initiative” (p. 417). In effect, students’

beliefs about their capabilities affect how they approach the future.

Self-observation and self-regulation of learning environments has become an area of

specialized research. Stress was found to also relate to both academic and nonacademic

endeavors in the pressures that college brings (B. Erikson, Peters, & Strommer, 2006). First-year

students need to adjust effectively and properly and demonstrate how experiences in high school

have contributed to college readiness (Swing & Upcraft, 2005).

15

Academic self-efficacy is strongly connected to environmental influences, hence the link

to high school types. Longitudinal studies have collected this data for years noting in reports the

difference that high school types (i.e., Public/Catholic/Other private) contribute to the overall

long-term success of persons moving through the education system (NCES, 2008). Although it is

true that students do not know what they do not know (Tinto, 1997), first-year college students

do not arrive on campus as empty vessels. A host of prior experiences, current perceptions, and

future expectations shape their engagement in higher education (Ahern, 2005; Cole &

McCormick, 2009; Kuh, 2005). Quilter (1995) and Tinto (2009) found that high educational

expectations and motivation are present in all students regardless of at-risk or normal status.

Chapter II of this study will present an overview of the literature related to academic self-

efficacy.

Definition of Terms

The following terms are presented for clarification in succeeding sections and are

operationally defined for the purpose of the study. The general subject of the present study is the

strength of academic self-efficacy and its presence within four types of high school environments

(public, private, religious, home school). The specific topic closes the gap in the knowledge

represented by the research questions about gender, confident communication, and dual

enrollment in high school and college classes.

• Academic self-efficacy. Academic self-efficacy is described as an individual’s

perceived capability in performing necessary tasks to achieve goals (Cruce, Kinzie, Williams,

Morelon, & Yu, 2005). For the purpose of this study, academic efficacy is measured by a

student’s perceived academic preparation, expected academic difficulty, and expected academic

16

perseverance as studied by the Indiana 2009 BCSSE surveys administered by the Indiana

University Center for Postsecondary Research.

• Communication confidence. Communication confidence is the perceived ability to

use interpersonal communication to achieve a level of self-satisfaction in a new setting (Rubin,

Martin, Bruning, & Powers, 1993). It is comprised of elements of assertive communication,

perceived efficacious traits of competent communication, and verbal displays of confidence. For

the purpose of this study, perceived communication confidence is the combined score of past and

present activities and present perceptions of efficacy in communication activities.

• Dual credit. Dual credit is enrollment in courses counting directly toward college

credit during the high school years, typically offered after the 10th grade year. For the purpose of

this study, Dual Credit is declared via an answer choice on the survey.

• First-year college student. A first-year college student is a high school graduate

attending college for the first time. For the purpose of this study, surveys administered during

freshmen orientation and include individuals from many backgrounds who are on campus for the

first time since high school graduation self-identified in response to administration of the BCSSE.

• Precollege experiences. Precollege experiences expose high school students to the

literacy, arts, concepts, careers, and cultural identity of American higher education (Biggs,

Schomberg, & Brown, 1977). Due to such exposure, a high school student’s perceived abilities

in educational activities develops via other individuals and experiences, and predispose him/her

to certain outcomes and future educational engagement (Hurtado, Engberg, Ponjuan, &

Landreman, 2002). For the purpose of this study, precollege experiences refer to the combination

of college choice, academic preparation, past patterns of motivation and well-being, and college

aptitude (Kuh et al., 2005).

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• Types of high schools.

• Home school. Home school is an alternative form of education in which parents

or guardians bypass the public school system and teach their children at home. In some states,

home schools are considered private schools (Education Commission of the States, 2011b). For

the purpose of this study, a home-schooled person is one that self-identified as a high school

graduate from a home school environment in response to administration of the BCSSE.

• Private, college preparatory (non-sectarian) high school. Private, college

preparatory (non-sectarian) high schools are institutions that are controlled by an individual or

agency other than a state, a subdivision of the state, or the federal government (which is usually

supported primarily by other than public funds) and the operation of whose program rests with

other than publicly elected or appointed officials. Private schools and institutions include both

not-for-profit and for-profit institutions (NCES, 2007c). For the purpose of this study, students

were asked to self-identify if they had graduated from a private-non-sectarian high school

program in response to administration of the BCSSE.

• Private religiously affiliated high school. A private religiously-affiliated high

school is an educational entity affiliated with the local community religious affiliations in

promoting the social capital of a church (Coleman & Hoffer, 1988). For the purpose of this study,

a high school graduate from a religiously-oriented high school self-identified in response to

administration of the BCSSE.

• Public high school. A public high school is an institution controlled and operated

by publicly elected or appointed officials and deriving its primary support from public funds

(NCES, 2007c). For the purpose of this study, students were asked to self-identify if they had

graduated from a public high school in response to administration of the BCSSE.

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Limitations

This study was subject to two major limitations. First, this research was based upon the

2009 administration of the BCSSE survey conducted by the Indiana University Center for

Postsecondary Research. Some researchers have criticized BCSSE for its sampling method. For

example, Cole, Kennedy, and Ben-Avie (2009) contended that BCSSE institutions were not

randomly selected. These colleges and universities elected to participate in the BCSSE project.

Generalizations from these findings thus rested on an assumption that the BCSSE sample was

representative of the wider population of four-year colleges and universities. Another limitation

is that those taking the BCSSE had already arrived on a college campus having passed through

the admissions process and might have perceived admission as proof of academic self-efficacy.

This type of self-fulfilling prophecy or self-selection bias might be present in the minds of the

first-year college students taking the BCSSE.

Delimitations

For the purpose of this study, GED completers were not included in the analysis of high

school graduate data. This is consistent with other databases like CIRP, CSEQ, and CCSSE that

examine the impact of high school environments. GED completers are outside the mainstream of

the concept of “school,” and being different from traditional students, may not have developed

academic self-efficacy from the years of schooling that they received. The study was confined to

the results of the BCSSE as administered by the Indiana University Center for Postsecondary

Research in 2009. Results of the 2009 BCSSE were delimited to only 20% of the population of

the BCSSE study by a limitation imposed by the Indiana University Center for Postsecondary

Research.

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Assumptions

It is assumed that BCSSE participants had previously considered their expectations for

the college experience and could accurately articulate them on the BCSSE survey. It is also

assumed that respondents provided, to the best of their ability, honest responses to the BCSSE

survey. The last assumption is that conditions during college orientation were similar and that

respondents answered to the best of their ability, regardless of web- or paper-based survey

administration.

Organization of the Remainder of the Study

This dissertation consists of five chapters. Chapter I is the introductory chapter that

includes the problem statement, purpose of the study, research questions, definition of terms,

limitations, delimitations, and assumptions. Chapter II contains a review of literature related to

the study. Chapter III presents the research methods. The findings from the data are presented in

Chapter IV. Chapter V concludes with implications and a discussion of the findings.

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CHAPTER II

LITERATURE REVIEW

The purpose of this study was to investigate how first-year college students from four

different high school types (public, private, religious, and home school) differ in their academic

self-efficacy. Factors comprising self-efficacy include perceived academic preparation, perceived

academic difficulty, and expected academic perseverance, as described in the 2009 BCSSE. The

investigation was also designed to determine what student characteristics may affect a first-year

college student’s perceived academic self-efficacy. The characteristics examined included the

following student variables: gender, prior college experience, and type of high school system.

Finally, the study was an effort to examine whether there is a relationship between measures of

academic self-efficacy and perceived communication confidence.

The following review of literature is a summary of literature pertaining to the systematic,

thematic, and theoretical backgrounds presented by other researchers on the topic of self-efficacy

regarding college-going expectations. In addition, advantages and disadvantages in the literature

related to concepts of students’ self-efficacy will be discussed. The review of literature concludes

with a discussion of the variables being investigated and a critique of past studies using similar

variables.

Educational Transition from High School to College

Viewing education as a set of systems aids in understanding the context in which

environments and social factors may influence an individual’s behavior (Alderfer, 1977;

Mayhew et al., 2011). Schools function as subsystems in larger systems of community and

21

society. School systems can be understood in social, economic, and political contexts. Generally

speaking, there are five functions of schooling (Macionis, 2002). The first, socialization, and the

second, cultural innovation, place education at a point of discovery that changes every life. The

third function of schooling, social integration, and the fourth function, social placement, unify

society and reward talent, regardless of background. Finally, the last function notes that colleges

and universities bring together people of diverse backgrounds and create networks for career

resources. Though the education system can be summarized as a change-worthy discovery

process unifying and rewarding blindly for employment and a fulfilling life, an organic system

such as education is changed entirely when one small area is changed. In a similar opinion to

Macionis, Goodlad (2003) forwarded public expectations as one of the purposes of schooling

systems. Goodlad was concerned about the need to shift focus. “The transfer of learning across

contexts (‘systems’) is quite limited. Even good students at universities do not transfer the

principles they learn to other contexts. Education may not be perfect” (p. 1), Goodlad noted, yet

the systematic relationship between education and democracy is essential.

Pascarella and Terenzini (2005) advanced a microsystem approach to higher education’s

place in this larger system. They focused on higher education’s four primary objectives: (a)

promoting self-understanding, (b) expanding personal, cultural, and social interests, (c)

confronting closed-mindedness and prejudice, and (d) developing ethical standards. As a result

of their meta-analysis of research in higher education, they argued that change is inevitable in

students during their college years as they develop social competencies and self-worth. The crux

of these changes is “away from authoritarian, dogmatic, and ethnocentric thinking” (Pascarella &

Terenzini, 2005, p. 214).

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The High School Graduate

The high school years contribute greatly in preparing students for college (McCarthy &

Kuh, 2005). Though standards in different types of schools are widely acknowledged in the

literature as a barrier to collaborative efforts, colleges and schools still face the challenge of

“understanding the relationship between the student experience in high school and subsequent

success in college” (Palmer, 2000, p. 100). High school grades are considered a large contributor

to college-going perceptions (C. Adelman, 2006; Education Week, 2009), and Astin and

Oseguera (2005) argued that high school grades are more reliable than standardized test results

(e.g., the ACT and SAT) at predicting success; however, high school outcomes (grade-point

average [GPA], ranking, awards, curriculum, etc.) do not guarantee a smooth transition to the

first year of college from secondary education institutions (H. Adelman & Taylor, 2002).

Understanding high school graduates’ expectations, attitudes, and perceptions gives

college administrators a more accurate picture of the high school experience (Richmond, 2011)

and assists them in promoting college readiness (McCarthy & Kuh, 2005; Schneider & Ward,

2003; Tinto, 1993). Aside from contributing to students’ expectations of college learning, high

schools are expected to prepare all students for success in college and the work force fulfilling a

public expectation that all high school graduates can go to college (Bushaw, 2011; Palmer, 2000;

Wilson & Adelson, 2012). Palmer (2000) suggested that colleges’ continued efforts to monitor

student movement from high school to college strengthen public confidence in higher education.

Transition and Engagement

The vast and varied literature on college-student pathways (initiation to completion) is

multifaceted. The typology of studies falls into specializations such as demographic indicators,

campus environments, social affiliations, faculty nuances, recruitment practices, and selectivity,

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to name a few. Tinto (1993) and Upcraft, Ishler, et al. (2005) asserted that important paths need

to guide researchers to seriously examine the in-flow, retention, and departure patterns of

students. They asserted that closely-examined research and literature reviews need to add

meaningful understanding of, and intentional focus on, the individual (vs. the aggregate group),

the organizational character of engagement (vs. the multiplex of all institutions), longitudinal

processes (vs. mere descriptions of associative behaviors), and relevance to policy (vs. academic

interest). This literature review meets the criteria as set forth by Tinto and Upcraft through an

examination of types of high school graduates’ perceived self-efficacy and how this is affected

by prior schooling and by administrators at all levels.

The present study was informed by Tinto’s (1993, 2009) theoretical components of

student integration. Tinto (2009) advocated “anticipatory socialization” in that successful

“transition hinges on the degree to which individuals have already begun the process of transition

prior to formal entry,” and the “desire to fit in moves [first-time college students] to emulate the

life of the institution well in advance of entry” (p. 97). The idea that a student brings to college

the student’s academic experiences as part of their many assets is further argued by Kuh and

Whitt (1988), Seidman (2005), and Bourdieu (1973). Bean (1980) supported the empirical tenets

of Tinto’s work, but deviated from it to stress that students’ beliefs shape attitudes, effect

interaction, and evolve into organizational involvement after college. Tinto (2009) maintained

that isolating beginning students in a college-success course to solve all of their freshmen issues

fragments the broad institutional approach to student engagement. When placed against the

characteristics of Bandura’s (1995) academic self-efficacy, it becomes clear that students’

attributes (traits) need facilitation to reach a level of engagement in the campus community that

fosters meaningful resolve and persistence (C. Adelman, 1999).

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Astin supported Tinto’s holistic model (see also Pascarella & Terenzini, 1991),

advancing “predictive outcomes” to gauge the time, chances, and capacity that it takes beginning

college students to complete a degree (Astin & Oseguera, 2005). Kirst, Venezia, and Antonio

(2004), Siegel (2011), and Boyer (1986) concurred, advancing the holistic framework of student

retention to the signals of success laid by high school professionals. “If students receive

conflicting signals or no signals at all about what is required for college admission and

placement, they are less likely to be prepared” (p. 16).

Clear signals will have a positive impact on motivation and are one mechanism for leveling the playing field. Since many postsecondary institutions are minimally selective, students need to be motivated to meet a preparation standard rather than beat the competition. This enhances motivation [to matriculate] because it is attainable. (Kirst & Bracco, 2004, p. 20)

Kuh and others (2004) found that individuals move into, through, and out of the college years by

willful acts of engagement. Stated another way, the first year of college is the start of students’

retention and satisfaction framed in postsecondary expectations.

Trends of Change

Though some would argue that there is a downward trend in student effort during the

high school senior year (C. Adelman, 2006; Boyer, 1987; Education Week, 2009), Astin’s policy

center at the University of California at Los Angeles (UCLA) concluded: “students are entering

college with less inclination to study but with higher academic expectations” (CIRP, 2002). “We

should not be surprised that this generation expects to get good grades for less effort” (Kuh, 2005,

p. 88). Nonetheless, experiences with prior transitions in schooling and learning patterns

established in elementary and high school persist through the college years. Cole and

McCormick (2009) reported that (a) perceptions are situationally dependent regardless of

acquired knowledge, and (b) all situations one encounters are affected by expectations; an

anticipated future event is impacted by past experiences. Differences in precollege experiences

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and prior transitions account for marked variance in student expectations (Noyes, Gordon, &

Ludlum, 2009). For example, the large body of literature regarding differences between first- and

second-generation students cites the contributions of the student’s experience in their precollege

environment (“subculture”), though both first- and second-generation students expect success in

college (Pike & Kuh, 2005a). Table 1 shows a comparison of the precollege terminology

employed by major researchers in this domain.

Table 1

Flow Chart of Theorists’ Typologies and Descriptors of Precollege Academic Settings

Astin I-E-O Tinto—interactionist theory

High school type Student’s entry characteristics; prior schooling; high school academic achievement

Kuh—theory of expectations/NSSE Traits + environment + academic characteristics = first-year college engagement

Department of Education/IPEDS School Types

Public/Catholic/other private

Note. I-E-O = input–environment–output; NSSE = National Survey of Student Engagement; IPEDS = Integrated Postsecondary Education Data System.

In summary, many studies have been conducted to analyze properties of and integrate

policies through Astin’s (1970) I-E-O theoretical framework. The I-E-O model has been used to

explain the impact of learning environments and group differences on students’ first-year college

experiences and learning outcomes (Pike & Kuh, 2005b). What still remains to be studied

pertains to the actual precollege dispositions of first-year college students “which can be shaped

into educational advantage through an institution’s programmatic or policy concerns” (Upcraft,

Ishler, et al., 2005, p. 497).

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New Directions in Research on Students

Researchers since the year 2000 have focused on the examination of college-going

dispositions (Tidwell & Sias, 2005). Dispositions are also called traits in the research pertaining

to communication theory and communication patterns during large life changes. Adjustments

into the first weeks of college are often based on self-fulfilling prophecies operating on

perceptions of competence (Pajares, 1996). In a large body of research, the disposition of

optimism is associated with arriving on campus. S. Hinkle (2004) noted, “an optimistic

perspective seems to enhance student adjustment to the transition and disillusionment could not

necessarily hinder adjustment. This optimism was tempered by a complexity of expectations” (p.

228). In contrast, in 2009, Noyes et al. examined survey responses from a sample of freshmen

and fourth-year students. Their conclusions contained the following observation:

The fact that high school behaviors and traits can influence student “engagement,” even late in the college career, is perhaps more worthy of comment. That the persistence of these influences over time is evidenced in the NSSE data supports what many institutions instinctively know when they select which students should be invited to attend their school—that for students to be successful there should be a good match between the personality of the student and the personality of the institution. (Noyes et al., 2009, p. 13)

The challenge for higher education institutions is to discover these reasons for first-year

engagement, either internal (dispositions) or external factors (self-efficacy), and make

environmental adjustments to promote academic self-efficacy and degree completion (Collins,

2006).

This section has been a summary of influences and characteristics of the first-year college

student’s adaptation and adjustment to college, understood through the work of Tinto (1975,

1993, 2004, 2009), Astin (1968, 1970, 1985, 1993), Astin and Lee (2003), Astin and Oseguera

(2005), and others. The next section addresses the effect of closely-held perceptions.

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Kuh’s Theory of Expectations and Perceptions

Kuh (2003b) conceptualized and organized a system to define, measure, and interpret

dimensions of college-student engagement. Kuh (2005) found that expectations organize a filter

to determine a way for individuals to assess effort necessary for a task, and influence behavior in

the psychosocial realms of self-efficacy and motivation (Greeno, Collins, & Resnick, 1996; Kuh

et al., 2005). High student expectations are generally satisfied where institutional environments

are perceived as inclusive and affirming, and learning environments are collaborative,

communicative, inquiry-based, and reflective of social significance (Kuh et al., 2005). For the

beginning college student, this includes both in-class engagement and out-of-class engagement

with which to gain self-awareness, social competence, altruism, and autonomy (Irungu, 2010).

To this end, expectations and perceptions intermingle so a first-year student’s choices are parallel

to prior experiences (Cole & Qi, 2009).

From Kuh’s (2003a, 2004, 2005) work has come the NSSE, BCSSE (considered a pretest

to the NSSE), the College Student Expectations Questionnaire (CSEQ), and input on myriad

other constructed instruments (Gonyea, 2001). In 2000, the NSSE was pilot tested, and the

BCSSE was tested in 2006. Ideally, entering college students take the BCSSE at the start of the

freshmen year and the NSSE at the end of the fourth year. With precollege and postcollege data

at hand, patterns and practices emerge to understand, direct, implement, and evaluate the

“environment” portion of Astin’s I-E-O theory (Kim, 2006; NSSE, 2007). Kuh’s development of

instruments for improving practice places priority on expected changes. Change must take place

with students remaining engaged and motivated to increase their knowledge and skills.

Students are transitioning to college, and colleges are adjusting to meet expectations

(Wilson & Adelson, 2012). According to Kuh, students expect to change by learning more and

28

maturing the way they think and act. Although the college experience is supposed to change

people, the rates at which individuals change or grow are highly variable (E. H. Erikson, 1959;

Hong, Shull, & Haefner, 2012; Kuh, 2003a; Multon, Brown, & Lent, 1991).

This section has discussed Kuh’s theory of expectations related to the large body of

literature on anticipated change in college. The next section continues the discussion of a first-

year student’s anticipated changes and perceptions of college readiness.

Acquiring College Knowledge: Transition-Ready (or Not)

The Bill and Melinda Gates Foundation funded research that concluded: “Because

college is truly different from high school, college readiness is fundamentally different than high

school competence” (Conley, 2007, p. 6). A variety of problems begin to emerge when high

school graduates enroll in college. By the end of the first year, academic difficulties, poor

institutional fit, financial concerns, and family obligations are exposed (C. Adelman, 1999;

Mayhew et al., 2011). Having taken a myriad of high school exit and public admission tests,

students are confused about what they really need to know to succeed. It is also argued that high

school is focused more on students in high school (providing opportunities for them to graduate)

than what they should know to be able to succeed in postsecondary education (Kirst & Bracco,

2004). Historically, there has been little correlation among reforms across educational levels and

there are few incentives (Conley, 2007).

Several researchers have indicated a need to examine the nature of relationships between

what students do in high school, what they know about college, and their post-high school

aspirations (Kirst et al., 2004; Upcraft, Gardner, et al., 2005). Kirst and Bracco (2004) noted,

“high school teachers and college professors differ in their views of what students should know

in order to enter postsecondary education” (p. 15). Pascarella and Terenzini (2005) summarized,

29

in a meta-analysis on the acquisition of college knowledge, that change is a function of factors

attributed to the first-year student’s academic background, interactions with major agents of

change, and efforts to engage in learning environments. These are shaping forces and

predisposing forces affecting the first-year students (Mayhew et al., 2011; Pratt & Skaggs, 1989).

This section was a summary of the effect of perceptions on college readiness and the

transition away from high school to the college environment. The next section concerns the

review to first-year students’ self-efficacy and ways in which Bandura’s work can successfully

be addressed through item analysis.

Academic Self-Efficacy

Academic self-efficacy is the belief one has regarding educational abilities to produce

desired outcomes in future situations. Bandura (1986) noted, “students’ beliefs about their

capabilities affect how they approach the future. Students who develop a strong sense of self-

efficacy are well-equipped to educate themselves when they have to rely on their own initiative”

(p. 417). Wood (1994), Yakaboski (2011), and DeWitz and Walsh (2002) took the position that

not enough has been done to understand the relationship between individual characteristics and

self-efficacy beliefs. DeWitz and Walsh tested the hypothesis that the college context, with its

many facets, produces levels of satisfaction. A sample of undergraduate participants produced a

significant association between self-efficacy and satisfaction, confirming the older work of

Multon, Brown, and Lent (1991) that found self-efficacy is a by-product of satisfied educational

outcomes. Hong et al. (2012) likewise found significant correlations between the intent to stay in

college and satisfaction with the college environment’s responsiveness to students.

Academic self-efficacy is not related to satisfaction alone (Bandura, 1977; Pajares,

1996b; Stevens, 1983). It is also reflected in the general outcomes predicted and performed

30

during the college years. Gore (2006) found that validity studies were needed to determine the

relationship between college success and measures of self-efficacy beyond standardized test

scores. Results from Gore and Wilson and Adelson (2012) suggest that academic self-efficacy

predicts general college outcomes, but intervening conditions matter in academic self-efficacy;

conditions such as the types of efficacy beliefs measured, how the questions are worded, and

when these academic-efficacy beliefs are measured. In creating test-response items to gauge

academic self-efficacy, Bandura’s (1995) research concurred, noting that perceived self-efficacy

is a factor in establishing intention. Bandura cautioned that care should be applied when using

terms of “can do” (a judgment of capability) rather than “will do” (a statement of intention).

Several key constructs arise in the literature regarding academic self-efficacy. The first

concerns its definition. Bandura (1995) and Pajares (1996a) posited that self-efficacy should be

removed from understanding other student characteristics such as self-esteem and self-worth and

behaviors based on self-fulfilling prophecies. The confusion with locus of control was also

expressed by Bandura (1995), but other researchers state the two are quite similar in one’s ability

to control outcomes by actions and will (Hong et al., 2012). Bandura clearly argued for self-

efficacy’s unique phenomenon of perceived capability and well-being; a high locus of control

does not include these two characteristics (Bandura & Barbaranelli, 1996).

Second, measurements of perceived efficacy should differentiate levels of task demands

that represent impediments to successful performance. Schunk (1991) and Lee and Bryk (1989)

found that variables such as perceived control, outcome expectations, perceived value of goals,

and self-concept are cues to individual’s efficacy beliefs. Self-efficacy appraisals reflect the level

of difficulty individuals believe they can surmount. If there are no obstacles to overcome, the

activity is easily performable and everyone is highly efficacious. Pajares (1996a) argued that

31

research using self-efficacy needs to differentiate between “I am capable” (confidence) and “I

will be capable” (self-efficacy); this study met that standard for validity.

The following points summarize the extensive literature on academic self-efficacy. In

summary, academic self-efficacy

1. Is a “set of beliefs about capabilities to produce designated levels of performance that

exercise influence over events that affect [students’] lives” (Bandura, 2002 p. 71).

2. Involves context-specific judgments of capabilities held in arrays of dispositions

(Zimmerman, 1995).

3. Is psychosocial trait for optimistically determining outcomes of human agency

(Bandura, 1995; Pajares, 1996a; Pascarella & Terenzini, 2005).

4. Is not self-concept, self-esteem, or confidence. It is a prediction of actions and locus

of control with self-fulfilling prophesies (Pajares, 1996b).

5. Is validly measured by scales (Bandura, 2006).

6. Concerns or encompasses communication (Weidman, 1989), emotional intelligence

(D. Nelson et al., 2011), student backgrounds (Kuh et al., 2005), and gender (Ruban & McCoach,

2005).

7. Is a mediating influence in studies focusing on learning disabilities, minorities, first-

year, and first-generation college students (S. Hinkle, 2004; Pike & Kuh, 2005a), social

integration (Strayhorn, 2010), and spirituality (Chickering et al., 2010).

8. Is a scaled subscore in the NSSE instrument for fourth-year college students (NSSE,

2007): NSSE’s benchmark “academic self-efficacy” is measured using responses from three

domains—perceived academic preparation, perceived difficulty, and academic perseverance;

9. Is present in items found in the BCSSE instrument.

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Self-Efficacy in Survey Instruments

BCSSE’s three scales—academic preparation, perceived difficulty, and academic

perseverance—meet Bandura’s measure of academic self-efficacy (Bandura, 1997; NSSE, 2007).

Scoring academic self-efficacy using BCSSE required a combination of conceptually related

factors that measure prior academic performance and perceived adjustment.

1. PAP in the BCSSE has been used to explain the role of academic confidence in first-

year students’ engagement patterns (Kinzie & Matveev, 2008; Wolf-Wendel, Ward, & Kinzie,

2009). Academic self-efficacy constructs require more than hindsight.

2. “Self-perceived coping ability” equates to BCSSE’s expected academic difficulty

(EAD). Chemers et al. (2001) found academic self-efficacy produced optimism and overall

satisfaction. The research was based on first-year student self-reports half way through the Fall

2000 semester.

3. EAP in the BCSSE gauges one’s expected academic perseverance. As Bandura

(1995) described it, academic self-efficacy requires the context to be more of a doorway to, past

experiences predisposing students to predict how difficult/easy it will be to move through the

changes ahead—”a prediction of outcomes” (p. 8). This is the perceived ability to adjust.

In Chapter III contains a further explanation of specific clustering using BCSSE items regarding

these elements of academic self-efficacy.

Independent Variables

The Historical Transition to College and Four High School Types

Policy and societal changes have brought high school completion and college attendance

within reach of almost all American students (Boyer, 1987; Katsinas, 2004). In the January 25,

2011, State of the Union address, the President of the United States called on all Americans to

33

accept one year of college as a normal education (Obama, 2011), and the Chronicle of Higher

Education responded, calling it “the perfect storm” (Benton, 2011). The increasingly high level

of unprepared students graduating high school is appalling, the article noted. Coordinating this

complex of opportunity, preparation, and building expectations for movement up the academic

hierarchy is a change from 1920 when Henry Ford saw a need, established his own trade school,

and taught unskilled workers with a sixth-grade education the rudiments of production (Simonds,

1943). At the end of World War II, colleges and universities were being established by mandate

across the nation via the 1947 President’s Commission on Education federal report (Berger &

Lyon, 2005; Gilbert & Heller, 2010).

After A Nation at Risk (National Commission on Excellence in Education, 1983) was

published in the 1980s, as other world powers escalated superior educational opportunities of

their own (Bell, 1988), research detected disparities between social classes and choices in high

school course delivery (at home, at church, and on the gymnastics floor). At the same time, new

efforts to bring an accountable postsecondary education to the masses included recommended

high school curriculum tracks for college preparation. High school performance became a

bellwether of academic capabilities in the transition to college (Mayhew et al., 2011; Pascarella

& Terenzini, 1991), also during this time period.

The emergence of specialized study in the freshmen year began when colleges searched

to optimize learning across the college years, and valid, reliable constructs of the many

constituencies on campus could provide initiatives and experiences toward desired gains (Swing,

2004). J. Ishler and Upcraft (2005) noted, “If institutions are to challenge and support first-year

students in their academic success, they must focus on the characteristics and experiences of

their students prior to college” (p. 31).

34

The Lingering Effects of High School on the First Years of College

With regard to prior academic achievement, there is substantial evidence that the most

powerful predictor of persistence into the sophomore year is the first-year students’ prior

academic achievement, including high school grades. Pancer, Hunsberger, Pratt, and Alisat

(2000) and Kuh (2005) cited research and advanced the argument that noticeable secondary-

school trends persist through the college years.

The NCES (2007a) reported more students attend college immediately after high school

now compared to fewer than half in 1972. Academic preparation affects their readiness for first-

year classes to a much higher degree (B. Erikson & Strommer, 2005; Hong et al., 2012)). The

U.S. government (NCES, 2008) reported larger numbers of nonpublic high school graduates,

particularly home school students, are attending college than in years prior to 2003. T. Jenkins

(1998) found significantly higher GPAs for home school students who attended community

colleges in three states. In the end, Berger and Lyon (2005) cited the “socio-cultural contexts of

American society that have shaped who has been served and in what ways they have been served”

(p. 4).

The lingering effects of high school settings are also impacted by choices made. Godwin

and Kemerer (2002) and others have produced the foundation for understanding school choice.

Kemmerer also explored the behavioral outcomes of secondary-school choice and “selection bias”

associated with higher educational aspirations. Goodwin and Kemerer found that selective

colleges have a higher number of nonpublic high school graduates. They also found that students

from a particular background have more commitment, fewer withdrawals (particularly at

Catholic high schools), and go to college in larger numbers than public high school students who

attended their attendance-zone school. As a contribution to the theoretical view of school type,

35

Godwin and Kemerer created a learning framework with school attributes as a subset of

characteristics; public or private? is listed as their first significant factor of the school

environment.

Research examining the inherent uniqueness of different high school environments on

academic self-efficacy is minimal. Sutton (2000) found there is no difference in college success

among high school graduates from public, nonpublic, and home school environments. Reason et

al. (2007) used NSSE data to construct an analysis of first-year competence and found that

academic competence is attributable to what happened to students during the first year of college,

rather than to characteristics they brought with them to college. The study examined only 30

institutions and researchers acknowledged that various campus environments may exist that

caused the study to underestimate the impact of certain conditions in the development of

beginning students’ competencies.

Duggan (2010) drew college-going attitudes from three types of high school

environments: traditional public school college preparation, home schooled, and private schooled.

When asked to perceive how they differed from their peers and other schools, public school

students cited their strengths in computers and writing; private school students cited their study

skills and habits, and home school students said they excelled in academics, mathematics, and

reading. Duggan concluded that college-transition research needs to include students from

private schools and home schools. Duggan also encouraged future research to replicate the

research on high school graduates from various types of environments with a larger response set

for generalizability.

In this section, important points in 80 years of educational changes have been noted. The

school-choice debate was critiques from several facets and the impact of “choice” on lingering

36

perceptions of education. In the following section, there is a summary of the function of each

type of school as it applies to the experience of transitioning to a new environment.

Public School

Public school systems started as a place to educate non-religious “pauper” children for a

better democracy. The Massachusetts laws of 1642 and 1647 ordered a minimum of home

instruction or apprenticeships for all children in a township, noting that, “the universal education

of youth is essential to the well-being of the State” (Barlow, 1967). Compulsory education

through the 12th grade began at the turn of the century following the Civil War as an industrial

wave was emerging across America. States eventually assumed control of educational systems

and their curriculum. In 1910, morality became an instructional component based largely on the

following dictum:

The school must take upon itself new duties in teaching math, promoting healthful sports, training in manly and womanly ways, inculcating thrift, teaching the principals underlying the conservation of our human and material national resources, and preparing the rising generation for a more intelligent use of their leisure time. (Cubberly, 1919, p. 501)

Polls taken by Gallup in 2000 showed expectations for public schools are (a) to prepare

people to become citizens; (b) to help people become economically self-sufficient; (c) to

promote cultural unity; and (d) to improve social conditions (Rose & Gallop, 2000). Gallup

found in 2002 (Rose & Gallup, 2002) that half of parents of public school students are likely to

be satisfied with schooling. This is in contrast to a 75% satisfaction rating of parents of

religiously oriented schools, home schools, or private/nonreligious schools. As charter schools

have emerged in the last 10 years, more satisfaction is found among parents of public school

students. Astin’s CIRP (2008) survey of freshmen categorized three types of public schools and

asked high school graduates from public schools to also identify “magnet” and “charter” if

37

applicable. This study used the BCSSE constructs of public/private-religious/private-

nonreligious/home school (see the 2009 BCSSE website).

More than a century of public education has produced many reformation efforts and

among those is an effort to prepare students for college. In 2009, 3 million diplomas were

awarded in public high schools in the U.S. (NCES, 2011a). Currently, the U.S. Department of

Education reports findings on different types of public and private schools in the annual

Condition of Education report. In 2011, the report tracked 18 million undergraduates in the Fall

of 2009 and reported 76% attended public colleges and 24 % attended private colleges.

Private School

The majority of the founding fathers of America were tutored in academies run by

Harvard and Yale where Latin and Greek were the core classes in the curriculum (Brubacher &

Rudy, 2004). Colonizing the New World also meant cultural transplantation in regards to private

schooling (Urban & Wagoner, 1999). The Puritans founded Harvard College, modeled after

Cambridge University (Brubacher & Rudy, 2004), based on two cardinal principals of English

Puritanism that most affected the social development of the United States: a learned clergy and a

lettered people (Rudolph, 1962). From the mid-1800s forward, it was understood that a learned,

college-educated citizenry would prevent a society run by the laws of dishonorable “mechanics,

cobblers, tailors, and the like” (Rudolph, 1962, p. 6).

Regarding the state of private education today, Deal (1991) concluded public schools are

more tightly controlled through authoritative command and rule, and private schools are more

closely knit through implicit mechanisms of social control. In the private schools Deal reviewed,

several common foundations were a widely shared myth or saga, a visionary leader, a loyal cadre

of followers, distinctive practices, and a loyal group of students and alumni. People were highly

38

committed to these organizations because they believed in what they stood for and found

meaning in their membership.

Though initiated in the Northeast, the location of private schools in the U.S. has moved

South. The 2009–2010 Private School Universe Survey (NCES, 2011b) reports 56% of schools

were located in the Midwest and South; the remainder is split between the Northeast (23%) and

West coast (20%). In 2009-2-10, the highest concentration of the 4.7 million private school

students reside seven states: California, Florida, Illinois, New York, Ohio, Pennsylvania, and

Texas. Each of these states recorded 200,000 or more private students. BCSSE drew its 2009

data from a similar regional population of first-year students spread around the U.S. (South and

Midwest institutions = 54%; BCSSE, 2009). With regard to the issue of self-efficacy, this

research does not look for correlation regionally. It is possibly imprecise since the student might

not attend an institution in the same region as high school graduation and BCSSE does not

delineate exact parameters for geographic boundaries. Another body of higher education

literature examines the matriculation patterns of students to colleges based on selectivity; this

research focuses on the type of high school and does not look for correlation in patterns of

matriculation (public or private high school students entering private or public colleges).

Religious School

Religious schools in America have roots in European Presbyterian and Anglican roots.

Lutheran schooling migrated to America and is assumed to have easily become part of many of

the original communities in the original colonies (Ornstein & Levine, 1984).

With regards to schooling policy, Massachusetts enacted the first compulsory (necessary,

sometimes forced) school attendance laws in 1852. The state of New York did the same in 1853.

By 1918, all states had passed laws requiring children to attend at least elementary school.

39

However, Catholic families who opposed common schooling created their own private schools.

This decision by the Catholic Church to provide for the mandatory education of children was

supported by the 1925 Supreme Court rule in Pierce v. Society of Sisters; states could not

compel children to attend public schools, and children could choose private schools.

In 2009–2010, the NCES (2011b) reported 77% of the 324,114 students in twelfth grade

private schools attended Catholic schools (47%) or Christian/other religious schools (30%). After

high school graduation, 86% of Catholic graduates and 70% of Christian school graduates

attended a 4-year college in the fall.

Tinto’s (1993) construct of social integration paved the way for research to probe the

religiously affiliated school choice. Results of a study found that worldview factors (“fit”)

contribute to high levels of student satisfaction and low levels of attrition (Morris, 2007).

Home School

Home schooling is the oldest form of education since the trades were handed down in

families (Holt, 1999). During the 1980s, home schooling experienced rapid growth and scrutiny

as parents pulled children from the influences of society found in public schools. By 2010, the

home-school movement had expanded to include 3 million students. The U.S. Department of

Education reported parents pulled students from traditional education paths for religious or moral

reasons (36%) and for dissatisfaction with school environments and instruction (38%) (NCES,

2007b). Boschee and Boschee (2011) undertook a quantitative examination of home schooling in

South Dakota and found that parents overwhelmingly stated the desire for strong familial

relations as the reason for the practice. Moving home schooled students into college raises

questions, leading Duggan (2010) to examine home school students’ preparation for college.

40

Duggan found similar outcomes and college GPA performance among home school completers

as students graduating from public high schools.

T. Jenkins (1998) noted that home schooling was still for people with unconventional

lifestyles in the 1990s and was not publicly widespread. As such, homeschooling was not an

easily understood concept. T. Jenkins formed findings from a dual-prong project that examined

the classroom performance of home schooled students in community colleges and the knowledge

that advisors had of the unique characteristics and needs of home schooled students on a college

campus. Across three states (Oregon, Michigan, and Texas), entering home-schooled college

students’ transcripts were analyzed and academic advisors were interviewed. Findings similar to

Duggan (2010) showed insignificant differences between college performance of the different

high school preparation. Based on the equality of preparation and no known advising model for

college administrators, T. Jenkins concluded that home schooled people are largely self-

supporting in the first year of college.

Types of Schools Related to This Study

The current study focused on impacting and guiding the research regarding a more

diverse precollege background group and on specific types of students on college campuses

(Berger & Lyon, 2005). Prior research has explored similar precollege backgrounds in

preparation, not environment (S. Hinkle, 2004). Astin (1993) and Pike and Kuh (2005b) found a

limited relationship between the demographics of first-year college students and student

engagement. Given that high school graduates emerge from four types of environments, differing

psychosocial backgrounds beyond demographic labels will likely result in changes in, and

expectations for, the first year of college (Wilson & Adelson, 2012).

41

Lee and Bryk (1989) compared high performing schools without regard for public or

private organization. Using data from the longitudinal database kept by the U.S. Department of

Education, they concluded that orderly schools are higher performing than other types of schools

and that Catholic schools are the most orderly. Citing research that “Catholic schools more

closely resemble the ideal of ‘the common school’ than do their contemporary counterparts”

(p. 172), they found that high-performing students are in schools with smaller class sizes, where

curriculum provides less choice of courses in mathematics, and where fair and effective

discipline permeates the environment (Lee & Bryk, 1989). This finding supports the premise by

Deal (1991) and Kemmerer (2002) that independent schools and Catholic schools are effective

not because they are “independent” or Catholic, but because they are organized. As Boyer (1992)

argued, perhaps the expectations of beginning college students relates more to the condition of

high-aspiration high school cultures described by Lee and Bryk’s three factors above rather than

the taxes or tuition (public or private).

Cole and Qi (2009) noted that important predictors of first-year academic confidence are

in one’s high school coursework and experiences. Prior school experiences accounted for some

first-year expectations and attitudes. The high school years influence college perception to the

extent that beginning college students act in a certain way to fulfill the perceived notions of how

the new learning environment (college) is supposed to be (Konings, Brand-Gruwel, &

Merrienboer, 2005; Mills, 2010).

Other than gender, the present research did not examine the interaction of high school

types and other student demographics. The next section will describe in depth the rationale for

using identifying variables of high school graduates from four types of high schools.

42

Student Characteristics—Independent Variables

Dual Credit

The numbers of students accessing dual-credit programs are increasing (Education

Commission of the States, 2011a). Demographers predict an increase in the generation Tidal

Wave II (children of the Baby Boomers) to access dual-credit programs mainly across the West

and South (Boswell, 2000). Dual-credit programs offer an alternative to a lackluster senior year

(C. Adelman, 2006; Boswell, 2000; K. Swanson, 2003) and provide an opportunity to experience

college-level work (Education Commission of the States, 2011a).

Kellum (2009) researched the effects of the 2006 Mississippi Education Reform Act.

This act established the authority of local colleges over dual-credit programs offered in

secondary schools. The goals of the programs in Mississippi are to increase high school

completion and raise postsecondary enrollment and completion. Kellum enumerated the benefits

of dual credit: (a) increase rigor of high school coursework, (b) promote efficient use of the

state’s educational funding, (c) increase access to higher education, and (d) enhance admission to

postsecondary education.

The results of a 2009 study concluded that students with prior dual-enrollment

coursework had statistically significant higher rates of postsecondary degree completion and

took less time to complete a Bachelor’s degree (Westcott, 2009). C. Adelman’s (2006)

recommendations are forceful, presenting an urgent need for all high school students to acquire

college credit whenever possible. Dual-credit programs are thought of favorably, but encounter

problems regarding long-term benefits. For example, some students completing dual credit in

Florida high schools could not get regular admission into the state universities and had to repeat

the exact course to receive credit. The literature on academic self-efficacy notes a large variation

43

of beneficial outcomes, especially in contexts of learning mathematics (Kim, 2006; Zimmerman,

1995). Results from Kim (2006) found that dual credit provided a positive impact on college

readiness, most significantly in mathematics. A qualitative study by Richmond (2011) found the

opposite—that standard Advanced Placement coursework outweighed dual credit in the equation

of students’ on-going college success. However, one’s internal self-efficacy was not a

component of Richmond’s study and differs from college acceptance based on a high school

GPA. The potential that self-efficacy is correlated to attending college classes before graduation

was not examined.

As previously reported, dual credit exposes students to a college environment before

arriving on the college campus. K. Swanson (2003) found that non-public high school students

access college dual credit in larger numbers and at younger ages, thus developing an early

understanding of what college learning is and what to expect. Swanson found that the academic

performance of former dual-credit students in regular college classes exceeded the GPAs of a

comparison group of students without dual-credit coursework prior to college.

Dual Credit Related to this Study

On the 2009 BCSSE, two thirds of respondents stated that they had participated in

college coursework prior to high school graduation (See Appendix B). This study looked at the

impact of dual credit on academic self-efficacy, and which types of high schools were accessing

this mode of education. Because C. Adelman (2006) directed students to enter college with at

least six college credits, college credit during high school has risen in prominence. This study

intended to address questions about which types of high schools are using dual credit to push

students forward, and if dual credit correlates with academic self-efficacy.

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Gender

According to results of a 2004 report from the NCES, researchers presented data that

females aspire to advanced degrees in greater numbers than men (NCES, 2004b). This is

consistent with prior findings from Bayer et al. (1970) pointing to the higher attendance of

females and higher GPAs of degree-seeking females. Astin (1968) contrasted characteristics of

public universities with teachers’ colleges where femininity and better behavior led to less harsh

instructor behaviors. The actual numbers of students taking the BCSSE (59% women, 41% men)

and the NSSE (55% women and 45% men) reflect the saturation of females in the research

(BCSSE, 2009).

In larger terms, the literature on gender in higher education has shifted two ways. First,

researchers examined gender and tasks of learning. Second, researchers studied subgroups of

students. Task-oriented gender studies have emerged in the literature on assertive communication.

Christie and Segrin (1998) set out to examine self-efficacy and the performance of tasks related

to higher education outcomes. Using path-model quantitative analysis, they found that men and

women excelled at different pieces of a task’s completion. Sex was not a significant predictor of

task completion, but masculinity contributed significantly higher self-efficacy scores. Findings

confirmed work by Bandura (1995) and Pajares (1996) in that self-efficacy is related to tasks and

not gender. Christie and Segrin (1998) used the target tasks of giving a speech and completing a

complex mathematics problem. This may have skewed the results of the study and applications

of its findings to masculine characteristics of construction and deconstruction; small-group

dynamics or patient worries faced by medical professionals might have produced different results

due to the emotive nature involved. The application of the research findings need to be taken in

45

the narrow focus of the task designated for the study, and not assumed to be true of all tasks

faced in and out of the classroom.

The second arena of emerging study for gender is the study of subgroup populations and

gender-related correlations. Goldrick and Han (2011) and Strayhorn (2010) found significant

differences in minority students entering college. These studies found (a) males are more likely

to interrupt the flow of educational progress, and (b) minority males are more likely to

emphasize the extent of their “social capital” upon arrival. Both studies arrived at a similar

conclusion: minority males of lower socioeconomic status have lower grades and more

difficulties than their peers from high socioeconomic-status backgrounds. This is consistent with

Yakaboski (2011) who found “for women and minorities, being a minority meant the need to

prove their merit through greater effort and determination” (p. 573). The studies emphasized the

changing nature of sociocultural inputs. An emphasis on extensive educational advising for

patterns of difficulty in these college-going subgroups’ is lacking from the findings of the studies.

Finally, Mayhew et al. (2011) explored gender for its impact on orientation programs of

new students transitioning to a new institution. They found that gender was less significant than

race on planned student engagement, but confirmed prior research that found differing social

integration expectations were based on gender (Krallman & Holcomb, 1997).

Gender Related to This Study

Upcraft, Gardner, et al. (2005) contended gender is a largely underused control variable

that is easily accessible to institutional leaders, and gender should be included in studies of

outcomes. In this study, transitions and adjustments through efficacious behaviors were

examined in first-year college students in the first days of college. Gender creates culture

(Schunk & Pajares, 2001; Strayhorn, 2010) and, therefore, this study uniquely captured the

46

possible influence of gender in the aftermath of high school and before the impact of college

classes. In a study conducted in Ireland, Simmons (2008) examined first-year college students

attending a number of institutions in Dublin. Simmons also examined females’ adaptation and

adjustment, facilitated by emotional intelligence or academic self-efficacy. Females reported

significantly lower levels of “fear of attachment” than their male counterparts. Simmons’ study

gives light to quantitative methods seeking correlations between self-efficacy and gender.

Gender related to this research study in another way. One’s perceived academic self-

efficacy is a possible characteristic of males and females from different high school backgrounds.

For example, in the southwestern U.S., the following four situations are found: a large religious

high school requires one term of debate in 11th or 12th grade for graduation. A small public high

school meets speech-communication requirements through dual-credit “public speaking” at the

neighboring community college. A large urban public school has ninth grade students take one

semester of “speech.” Home schooled students are assigned a year of preparation for a youth

speaker’s tournament at an association of area churches. The gender of an individual might have

an impact on the perceived self-efficacy and performance outcomes in these four different

situated classes (C. Adelman, 2006; Pascarella & Terenzini, 2005; Schunk & Pajares, 2001).

McCroskey, Valencic, and Richmond (2004) described the concept of assertive speaking as the

clear, direct, and appropriate expression of personal opinions, feelings, and purposes without

undue anxiety and with respect for oneself and others. The body of literature on assertive-

communication styles applies to this study in two ways: as a communication goal for both

women and men in a time of major social change; and as an instructional disposition that

employs a variety of interpersonal communication traits (Bate, 1976; Ruban & McCoach, 2005).

47

Communication

Communication Confidence

Research involving human communication has been implemented to examine the process

through which meaning and social realities are created, and to a larger degree, how meanings are

managed (Rubin, Rubin, & Piele, 2000). The context in which communication takes place is

often interrelated with other realms of study, mediating past experiences with present difficulties

(Rubin, Martin, Bruning, & Powers, 1993). The current study raised the possibility that self-

efficacy and perceived academic preparation result in communication assertiveness. The present

study is an effort to investigate the multiple intersections of communication confidence of

incoming first-year college students.

Understanding communication behaviors began with early researchers examining the

theory of a relationship between perceptions, self, and communication. Historically, theorists

favored making a connection between self-perceptions and communication (Hansford & Hattie,

1982). Communication was viewed as a function of the social world and engagement with the

environment (Maruscsak, 2006). In recent years the emergence of an interactionist-self theory

has examined the social world from the concept of psychosocial change. More recently, current

theory linking communication confidence and self-perceptions as an integrated whole has been

documented (Glauser, 1984). Through communication, one may be perceived as self-confident,

but not necessarily socially competent, in the ability to communicate.

Researchers that seek links in the perceptions of self and communication typically

explore communication and behaviors (Maruscsak, 2006). Some experts have assumed that

individuals who are high in self-esteem are more competent communicators than those low in

self-esteem (Hansford & Hattie, 1984). To quantify these phenomena, NSSE used a measure

48

called interpersonal attentiveness. Emotional intelligence literature calls this characteristic

assertive communication (D. Nelson et al., 2011). This competency in the present study will be

termed Communication Confidence.

Assertive communication is a foundational piece of emotional intelligence and aids in the

transition process (Bate, 1976). Roueche and Mink (1976) found that students adjusting to

college are expected to possess the necessary verbal skills to accompany a lecture-based

classroom. Additionally, Roueche and Mink theorized that outward communication skills are a

by-product of an internal locus of control, which in turn has the power to affect change in the

current situation. To state it another way, past experiences create an internal locus of control that

affects changes in a student’s situation and impacts his or her verbal and nonverbal

communication traits. Researchers point to a need to implement an environmental atmosphere

that fosters assertive communicative on foundational levels similar to the locus of control.

The lack of complex verbal skills delays a student’s transition to and through the college

years. M. J. Smith (1975) determined that communication is foundational for building

relationships. Further, M. J. Smith found that “free information” about someone’s interests,

needs, and value choices make it easier for a robust communication environment to take place.

Anderson (1995) concluded that these interpersonal motives (personal characteristics explaining

why people communicate with others and how people communicate to satisfy interpersonal

needs) are stable in observed needs of experimental participants.

Communication Confidence, Self-Efficacy, and High School Students

Incoming first-year college students from different high school types maintain established

communicative patterns. These communication patterns are embedded in first-year college

students due to the desire for a student to have a solid relationship with others and themselves (E.

49

H. Erikson, 1959; Hong et al., 2012; Hurt, Scott, & McCroskey, 1978). The communication

environment of their high schools may enrich or impede their perceptions of college. As noted

previously in this study, perceived self-efficacy may create self-fulfilling prophecies and those

self-fulfilling actions pertain to active communication interaction.

An assertive communication style is perceived as more efficacious than are nonassertive

or aggressive styles (Mottet, Martin & Myers, 2004; Woolfolk & Dever, 1979). An assertive

communication style may be a biological trait or a generalized learned mechanism connecting

experiences with coping skills (Wahba, 2005). Hansford and Hattie (1982) explored

communicator style in high school students and uncovered the existence of the following

communication characteristics in high school graduates: relaxed, animated, dominant, image, and

apprehension. Further analyses found that these characteristics are dependent on contextual

dimensions (Hansford, 1984). One’s self-concept and masculinity/femininity were found to

correlate with one’s communicator style (Ando, 2011). In particular, high school students with a

high self-concept perceived themselves as being relaxed, attentive, low on situational

communication apprehension, and held a positive view of their communication image. Similarly,

Hopf and Colby (2009) concluded that increased anxiety in interpersonal communication is

correlated with low self-efficacy, suggesting first-year college students’ feelings of perceived

powerlessness results in negative, apprehensive communication patterns.

Communication as it Relates to This Study

New pathways for the flow of and the need for communication come at major life

changes. Chickering and Gamson (1991) cite communication intentions to be a part of good

practices in undergraduate education. “Exposure to post-secondary education significantly

enhances students’ oral communication skills” (Pascarella & Terenzini, 1991, p. 579). In

50

addition, understanding the intersection of perceived self-efficacy and communication patterns of

first-year students parallels national-survey benchmarks of engaged educational activities (Kuh,

2005).

The present study measured confident communication patterns using a new subscore in

the BCSSE: Communication Confidence, synonymous with and hybridized through competence

and assertiveness. On the 2009 BCSSE, students responded to five communication-oriented

survey questions: “I engaged” (past high school experiences = Question 9), “I will engage”

(predicted college behaviors = Question 14), and “I am an effective communicator” (overall

efficacy judgment = Question 17b). These items were analyzed together and create a self-

perceived efficacious communication environment that includes, but is not isolated from,

intrapersonal communication and interpersonal communication patterns. The measurable,

quantifiable construct is noted as communicative confidence. In Chapter III will be a discussion

of the methods used to reliably measure communication confidence using BCSSE’s measures of

student engagement.

Summary and Conclusions

Previous research has examined the many parts of precollege influences on first-year

college students’ expectations. Based on surveys and the examination of policies, entities have

differentiated and assembled the scholarly body of work that spans the work of the high school

counselor, the practices of enrollment management, and the beginning movement through the

college experience. Much of the literature is found in the context of student retention and

persistence. Few studies describe how student-affairs leaders perceive the variety of incoming

college freshmen leadings to an unbalanced and incomplete body of knowledge. Additionally,

few studies exist on how different types of high school environments predetermine concepts of

51

what to expect in college, an important time in human development. There is certainly an urgent

need for an empirical study on the ways that different types of high schools navigate or mitigate

the expectations of beginning college students.

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CHAPTER III

METHOD

Research Design

The purpose of this study was to investigate the relationship between academic self-

efficacy and students’ high school background. The study was guided by the following research

questions:

RQ1. Do first-year college students from different high school types (public, private

religious, private college-prep, home school) differ in their academic self-efficacy?

RQ2. To what extent are gender, dual credit coursework, and type of high school

attended contributors to a first-year college student’s academic self-efficacy?

RQ3. Is there a relationship between measures of academic self-efficacy and perceived

communication confidence?

In this chapter, details of the methods used in the study are specified. First, an overall

description of the population and the sample used is discussed. Next, a discussion of the test

instrument and its psychometric measures is presented. Also, steps to check and address data

abnormalities is explained. Finally, the chapter concludes with the data analysis procedures and

how the procedures are associated with the research questions they address.

Nature of the Study

Beginning College Student Survey of Expectations (BCSSE) measures entering first-year

students’ pre-college academic and co-curricular experiences as well as interest in and

expectations for participating in educationally purposeful activities during college (Cole et al.,

53

2009). The BCSSE survey originated in 2006 and was founded on the work of George Kuh

(2005) with a goal of measuring a student’s overall perception of the college-going experience.

The results of a study conducted by the Indiana University Center for Postsecondary Research in

2009 provided the foundational statistics with which to test the hypotheses, which are testable

predictions about the observed phenomenon and constitute the gap in the knowledge.

Population and Sample Description

The population for this study is first-year college students enrolled in all baccalaureate-

granting institutions in the United States. A random sample was drawn from the 2009

administration of the BCSSE, in which a total of 73,274 first-year students at 197 4-year

institutions participated in the administration of the BCSSE. These institutions self-selected to

participate in BCSSE, and many are using a companion survey, the National Student Survey of

Engagement, to assess first-year to senior-year growth and change. Institutional characteristics of

the 2009 BCSSE participating institutions can be found in Table 2.

Table 2

Institutional Type Breakdown of Participants, BCSSE, 2009

Doctoral granting: 26,091 Master’s granting: 32,783

Baccalaureate 4-year: 14,400

Private: 27,769

Public: 45,505 Note. Number of institutions: 197; total respondents: 73,274

Sample

The sample for this research came from the 2009 administration of the BCSSE. Only

20% of the whole BCSSE data (approximately 15,000 responses) is released by the

administrators of the BCSSE for this study. To ensure a proper comparison between different

54

types of high schools, this sample included at least 1,000 randomly selected students from the

public and the two private high school environments and all (n = 681) respondents from home

school environment. The BCSSE is administered to first-year students before the first day of

classes and assesses the student’s general perceptions and expected engagement across various

educational events. In 2009, 91% of responses were gathered from a random sample of students

attending orientation before classes started (BCSSE, 2009). See Appendix B for grand mean

results

Confidentiality

Due to the absence of student identifiers in the dataset provided by the Indiana

University’s Center for Postsecondary Research, personal identifications were not disclosed nor

traceable. Confidentiality is not an issue. Because of this, the University of North Texas’ IRB

approved this study on an expedited basis. See Appendix D.

Instrumentation

According to Cole and McCormick (2009), BCSSE measures entering first-year students’

pre-college academic and co-curricular experiences, as well as their interest in and expectations

for participating in educationally purposeful activities during college. The BCSSE instrument is

distributed to a random sample of entering students at institutions that subscribe to BCSSE’s

product. Responses to the survey items provide insight into a first-year student’s pre-college

engagement in academically-relevant activities. The survey originated in 2006 and is founded on

the work of Kuh (2005) with a goal of measuring a student’s overall perception of the college-

going experience. The BCSSE is administered by Indiana University’s Center for Postsecondary

Research and access to the database has been granted for this study.

55

The survey is constructed of 32 items that are arranged according to past experiences and

future predictions. Items 1 through 12 ask for a report of past high school experiences. Predicted

college experiences are measured in Items 13 through 23. Items 24 through 32 relay

demographic and institutional information. From these 32 items BCSSE administrators group the

expectations of first-year engagement into five benchmarks. The five benchmarks are (a) high

school engagement, (b) expected academic engagement, (c) expected academic perseverance, (d)

expected academic difficulty, and (e) perceived academic preparation. Appendix A shows the

five benchmarks and their associated survey items.

Reliability and validity measures conducted on the initial NSSE test administration

showed strong face and construct validity (Kuh, 2003a). The results are quite stable from one

year to the next. Threats to validity are controlled through questioning techniques about recent

activities and a time frame reference. Pike and Kuh (2006) noted that studies of self-report are

valid under five conditions:

1. Information requested is known to the respondents.

2. The questions are phrased clearly and unambiguously.

3. The questions refer to recent activities.

4. The respondents think the questions merit a serious and thoughtful response.

5. Answering the question does not threaten or embarrass the respondent.

In his overview of psychometric properties, Kuh (2003a) illustrated that the NSSE instrument,

BCSSE’s larger counterpart, has good reliability between administrations. Confirmation from

test-retest analysis found a Pearson correlation of .83.

BCSSE data from these five scales have shown to be normally distributed and reliable.

Each scale is computed as a 10-point scale by first recoding each item to a range of 10 points and

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then taking the average score among the group of items (Cole & McCormick, 2009). Three of

these scales are pivotal to this study: expected academic perseverance, expected academic

difficulty, and perceived academic preparation. According to Cole and Qi (2009), these

groupings serve as indicators of student motivation. For the purpose of this study, the

respondents’ combined score on these three benchmarks was used as a measure of academic self-

efficacy (Bandura, 2006). Two important considerations should be known regarding aspects of

validity for this study. First, since the perceived academic self-efficacy dependent variable was

created for this study, direct association to the benchmark values of the 2009 BCSSE reliability

correlations is sufficient (Ahern, 2009). Second, the use of responses to generate a quantity for

first-year students’ communication confidence reflects low apprehension communication

patterns and was thoroughly discussed in Chapter II of this study. The reliability for this measure

is .66, and is consistent with a communication theory scale rating of .71 for similarly worded

items in Norton’s Communication Style Inventory (Rubin, Rubin, & Piele, 2000).

Data Preparation

The accuracy of a dataset is important in any study attempting to correlate patterns and

predict trends. Missing data (no answer) for independent variables (gender, college-credit, and

type of high school) cannot be substituted due to the anonymous nature of the data; student

names and identifiers are not provided in the sample. Therefore, I eliminated the participant’s

response by coding a “system missing” for the missing data. Based on the research from the

administrators of the survey, missing data usually accounts for 1% of the participants (Kuh,

2003a).

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Data Analysis Procedures

Research Question 1

This study combined three BCSSE scales into a single composite score called academic

self-efficacy. The first research question—Do first-year college students from different high

school types (public, private religious, private college-prep, home school) differ in their

academic self-efficacy?—is addressed using one-way ANOVA. One-way ANOVA is usually

used to compare means among three or more groups created from a single independent variable

to a single dependent variable (Frey, Botan, Friedman, & Kreps, 1991). For this analysis, the

dependent variable is one’s perceived academic self-efficacy and the independent variable is the

type of high school a student graduated from. ANOVA calculations produce an F value that is

used to determine if the results are significant. If an F value is significant, post hoc tests are run

to pinpoint differences among all possible two-group combinations.

For the purpose of this study, academic self-efficacy was measured by a composite scale

composed of the individuals’ combined scores from the three benchmarks. To measure academic

self-efficacy, the following pattern was followed: PAP + PAD + EAP . This equates to an

academic self-efficacy score. Table 3 illustrates the composite scores and the associated research

question utilizing the composite score, and shows how the combined scores on the BCSSE (PAP,

PAD, and EAP) and on items depicting communication behaviors are used to answer research

questions. The three factors, PAP, PAD, and EAP, are gathered from the 2009 BCSSE

participants and are associated with that individual’s high school type. Cronbach’s alpha tests the

reliability for this sample across the composite subscales.

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Table 3

Composite of BCSSE Test Items and the Research Domain to be Measured

2009 Benchmark Research question

Perceived Academic Preparation Perceived Academic Difficulty Expected Academic Perseverance

Academic self-efficacy (Do first-year college students from different high school types differ in their academic self-efficacy? To what extent are gender, dual credit coursework, and type of high school attended contributors to a first-year college student’s academic self-efficacy?)

Three established assumptions are considered when calculating the F value. First, the

value on each of the groups follows a normal curve. This assumption is addressed by calculating

the mean and standard deviation of scores for academic self-efficacy for each type of high school

environment and reporting the distribution of scores. Second, different population averages are

considered normal. This assumption is addressed by presenting the mean score of each group in a

table in Chapter IV. The third assumption of an accurate F value is that the populations have

equal standard deviations. Researchers feel assured in using ANOVA if the largest standard

deviation is not larger than twice the smallest (D. Hinkle, Wiersma & Jurs, 2003). This

assumption is addressed using bootstrap estimates and reporting the results.

If the one-way ANOVA resulting F value is statistically significant, a Tukey post-hoc

analysis is conducted on the results to determine the significance of the pairs. A Tukey post hoc

analysis explains the difference and magnitude in variance found when using an ANOVA (D.

Hinkle et al., 2003), and this research meets the requirements to use it. The level of significance

used for this study is .05.

Research Question 2

Ordinary least-squares analysis, otherwise known as multiple regression, was used to

answer the second research question: To what extent are gender, dual credit coursework, and

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type of high school attended contributors to a first-year college student’s academic self-efficacy?

For Research Question 2, the independent variables included the following student

characteristics: gender, prior college experience (dual credit), and type of high school.

Multiple regression is an expansion of bivariate regression to examine two or more

independent variables’ impact on the dependent variable (Frankfort-Nachmias & Leon-Guerro,

2006). According to Gall, Gall, and Borg (2003), multiple regression assigns an order to factors

as they influence variability in the dependent variable. A regression equation is used to guide the

regression model and analyze the results. For this research study, the following regression

equation was used:

Academic Self-efficacy= β0 + β1 (gender) + β2 (dual credit) + β3 (school type)

Research Question 3

Research Question 3— Is there a relationship between measures of academic self-

efficacy and perceived communication confidence? —was analyzed in two steps. First,

exploratory factor analysis of communication items showed two types of communication existed

in the BCSSE, one low-level interpersonal, the other more formalized and authoritative. Both

factors of communication were highly correlated. A communication confidence variable was

compiled using the sum of the scores on five low apprehensive interpersonal factor items (9 H,

L; 14 L, O; 17 B). Second, the communication confidence variable was entered into a bivariate

regression comparing it to academic self-efficacy.

Variables were entered into SPSS 19 statistical software program. SPSS 19 is a computer

software package that analyses data input by researchers. The results and findings are presented

in tables in Chapter IV.

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CHAPTER IV

RESULTS

This chapter presents the results of the study. The purpose of the study was to investigate

the effects of a college freshmen’s high school environment on academic self-efficacy and to

measure the impact of gender, confident communication and dual enrollment in college classes

on academic self-efficacy and college-experience expectations. It was guided by three research

questions:

RQ1. Do first-year college students from different high school types (public, private

religious, private college-prep, home school) differ in their academic self-efficacy?

RQ2. To what extent are gender, dual credit coursework, and type of high school

attended contributors to a first-year college student’s academic self-efficacy?

RQ3. Is there a relationship between measures of academic self-efficacy and perceived

communication confidence?

Descriptive Statistics

High School Type

Of the 15,400 people in the overall sample, 77% were from public schools, 12.1% from

private religious schools, 6.5% were from private independent schools, and 4.4% were from

home schools. The descriptive statistics showed that the sample was predominately from public

school, and of the others, private-religious was the largest group. The responses coming from

public and private religious schools represented 89% of the responses. No missing data were

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identified for the type of school variable included within the sample. Table 4 shows the number

of survey respondents attending each type of high schools.

Table 4

Frequency Table for Type of School

Type of school Frequency Percent

Public 11,855 77.0 Private, religiously-affiliated 1,864 12.1

Private, independent 1,000 6.5 Home school 681 4.4

Total 15,400 100.0

Gender

Of the 15,400 people in the overall sample, 39.9% were male and 57.1% were female,

and 462 (3%) did not report their gender. This distribution matches the overall gender

distribution of all BCSSE participants. In Table 5 is shown the breakdown of BCSSE

participants according to reported gender.

Table 5

Frequency Table for Gender

Gender Frequency Percent

Male 6,145 39.9 Female 8,793 57.1

Total 14,938 97.0 System missing 462 3.0

Total Sample 15,400 100.0

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Dual Credit

Of the 15,400 people in the sample, 58.2% did not participant in dual credit programs in

high school and 34.1% participated. A total of 1,195 (7.8%) students did not respond to this

question. In Table 6 is reported the descriptive statistics of participants’ accumulation of dual

credit coursework.

Table 6

Frequency Table for Participation in Dual Credit Opportunities

Dual credit Frequency Percent

No (.00) 8,960 58.2 Yes (1.00) 5,245 34.1

Total 14,205 92.2 System missing 1,195 7.8

Total sample 15,400 100.0

Research Question 1

Reliability index Cronbach’s alpha were calculated for the academic self-efficacy scale

and the communication confidence scale. The alpha coefficient of reliability measures internal

consistency and ranges from 0 to 1. A score of 0.6 to 0.7 is questionable, 0.7 to 0.8 is acceptable,

0.8 to 0.9 is good, and greater than 0.9 is excellent. Cronbach’s alpha for the academic self-

efficacy scale was 0.77. Cronbach’s alpha for the communication confidence scale was 0.66 and

is slightly lower than desired for comparison purposes. Tables 7 through 9 below include the

results of comparing average self-efficacy scores by school type using a one-way analysis of

variance (ANOVA). Table 7 includes the descriptive statistics for self-efficacy by type of school.

The public school sample was the largest (n = 11,515), followed by private religiously-affiliated

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schools (n = 1,809), private independent (n = 957), and home school (n = 659). The mean of

academic self-efficacy scales ranged between 18.98 (SD = 3.03) and 18.61 (SD = 3.10).

Table 7

Descriptive Statistics for Academic Self-Efficacy by Type of School

Type of school N Mean Std Dev Std Err

Public 11,515 18.98 3.03 0.03 Private, religiously-affiliated 1,809 18.61 3.10 0.07

Private, independent 957 18.89 3.03 0.10 Home school 659 18.93 2.76 0.11

Total 14,940 18.92 3.03 0.02

The results of the one-way ANOVA indicated that high school graduates from different

types of schools were significantly different in academic self-efficacy, F(3,14936) = 7.5, p <

0.001. The assumption of homogeneity of variances was tested using Levene’s test, and this

assumption was upheld., F (3, 14936) = 3.16, ns. Based on the statistically significant results for

the one-way ANOVA, post-hoc tests (Tukey) were conducted to determine which pair of groups

had statistically significant results. Table 8 shows the one-way ANOVA results, and Table 9

summarizes the results of the post-hoc Tukey tests.

Table 8

One-factor ANOVA results for academic self-efficacy

Source of variation Sum of squares df Mean square F Sig.

Between groups 207.1 3 69.0 7.5 < .001

Within groups 136,995.0 14,936 9.2

Total 137,202.1 14,939 Note. Dependent variable: Academic self-efficacy; Levene’s statistic: F(3,14936) = 3.17, p > 0.01

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Table 9

Post-Hoc Tukey test results for Academic Self-Efficacy

Group I Group J Mean difference (I–J) Std. error Sig.

Public Private, religious 0.363** 0.077 < .001 Private, independent 0.086 0.102 0.834

Home school 0.048 0.121 0.979 Private, religious Public –0.363** 0.077 < .001

Private, independent –0.277 0.121 0.101 Home school –0.315 0.138 0.101

Private, independent Public –0.086 0.102 0.834 Private, religious 0.277 0.121 0.101

Home school –0.038 0.153 0.995 Home school Public –0.048 0.121 0.979

Private, religious 0.315 0.138 0.101 Private, independent 0.038 0.153 0.995 Note. * The mean difference is significant at the 0.05 level; ** The mean difference is significant at the 0.01 level.

The results of the post-hoc Tukey test suggest a significant difference in mean academic

self-efficacy between public (mean = 18.98, SD = 3.03) and private (religious) (mean = 18.61,

SD = 3.10) schools. A significant mean difference in perceived academic self-efficacy was found

between these schools (mean difference = 0.363, p < 0.01). The mean perception of self-efficacy

was found to be significantly higher for public schools when compared to private (religious)

schools.

Research Question 2

To what extent are gender, dual credit coursework, and type of high school system

attended contributors to a first-year college student’s academic self-efficacy?

Next, a multiple regression analysis was conducted to determine if statistically significant

relationships exist between school type, gender, dual credit coursework, and the dependent

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variable academic self-efficacy. The following table (Table 10) summarizes the results of the

multiple regression analysis.

Table 10

Multiple Regression Results—Initial Model

Independent variables B Std. error Beta t Sig.

Constant 18.680 .047 394.702 < .001 Priv_Rel –.289 .079 –.031 –3.639 < .001

Priv_Ind –.029 .108 –.002 –.267 .789 HomeSch –.080 .125 –.006 –.644 .520

Female .354 .052 .058 6.770 < .001 Dual credit .240 .053 .038 4.482 < .001 Dependent variable: Academic self-efficacy; Public high school type was used as the reference category for the dummy variable coding of high school type.

The R2 value for the model identified within Table 10 was very low (R2 = 0.006). Only

0.6% of the variation in academic self-efficacy was explained by type of school, gender, and dual

credit coursework. The possibility of multicollinearity was also checked using the variance

inflation factor (VIF) diagnostic. VIF values ranged from 1.00 to 1.02; therefore, no problems

with multicollinearity were detected. The assumption of normality of the residuals was checked

using a histogram of the residuals, and the assumption of normality of residuals was upheld.

Three of the independent variables were statistically related to academic self-efficacy.

These three variables were private (religious) high schools (B = –0.289, t = –3.639, p < 0.01),

females (B = 0.354, t = 6.770, p < 0.01), and dual credit (B = 0.24, t = 4.482, p < 0.01). Private

(religious) schools were significantly lower in perceptions of self-efficacy than the reference

category of public schools. Females had higher perceptions of self-efficacy than males, and the

dual credit group with some college credit ( value = 1) had higher perceptions of academic self-

efficacy than those students who did not accrue college credit during high school (value = 0).

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A Second Model of Prediction

An unexpected result emerged from the creation of a second model to measure variability

in academic self-efficacy. Another multiple regression analysis was conducted to determine if

statistically significant relationships exist between school type, gender, dual credit, and the

dependent variable academic self-efficacy; however, for this follow-up model, an additional

independent variable (communication confidence) was also included.

The R2 value for the model identified within Table 11 was much higher (R2 = 0.173). For

the final regression model, 17.3% of the variation in academic self-efficacy was explained by

type of school, gender, dual credit coursework, and communication confidence. The following

table (Table 11) summarizes the results of the second multiple regression model.

Table 11

Multiple Regression Results—Final Model

Independent variables B Std. error Beta t Sig.

(Constant) 12.746 .122 104.616 < .001 Priv_Rel –.318 .073 –.035 –4.366 < .001

Priv_Ind –.199 .099 –.016 –2.005 .045 HomeSch –.161 .116 –.011 –1.394 .163

Female .145 .048 .024 3.015 .003 Dual Credit .146 .049 .023 2.962 .003

Comm confidence .399 .008 .411 52.137 < .001 Dependent variable: Academic self-efficacy; Public high school type was used as the reference category for the dummy variable coding of high school type.

The possibility of multicollinearity was also checked using the variance inflation

factor (VIF) diagnostic. VIF values ranged from 1.01 to 1.02; therefore, no problems with

multicollinearity were detected. The assumption of normality of the residuals was checked using

a histogram of the residuals. The assumption of normality of residuals was upheld.

67

To determine the amount of variance explained by dual credit, a bivariate analysis was

run using academic self-efficacy as the dependent variable. The Pearson correlation was

significant (r = 0.06 , p < 0.01, n = 5,245) though not as strong as other independent variables.

Research Question 3

Bivariate analyses were used to determine the correlation of perceived academic self-

efficacy and the independent variable communication confidence. The relationship between

communication confidence and academic self-efficacy was found to be positive and statistically

significant (r = 0.41, p < 0.01, n = 14,669). The Pearson correlation reflects a strong relationship

between the independent variable communication confidence and the dependent variable

academic self-efficacy. As communication confidence increases, academic self-efficacy also

increases.

Summary of Findings

Five of the independent variables were statistically related to perceived academic self-

efficacy. These variables were private-religious high schools (B = –0.318, t = –4.366, p < 0.01),

private-independent high schools (B = –0.199, t = –2.005, p < 0.05), females (B = 0.145, t =

3.015, p < 0.01), dual credit (B = 0.146, t = 2.962, p < 0.01), and communication confidence

(B = 0.399, t = 52.137, p < 0.01).

First, as stated earlier, students from private religious schools were significantly lower in

perceptions of self-efficacy than students from public schools. When communication confidence

was entered into the regression model, students from private independent schools showed

statistically significant lower perceptions of academic self-efficacy than the reference category of

public schools. High school graduates from a public school have higher perceived academic self-

efficacy compared to those from other forms of private religious education.

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Second, females had higher perceptions of academic self-efficacy than males. The

limitations of this study did not examine causes of academic self-efficacy in women; perhaps

choosing to attend a single-sex institution founded as an all-women environment increases the

likelihood of engagement (Pascarrella & Terenzini, 1991).

Next, the students who acquired college credit via dual credit programs had higher

perceptions of academic self-efficacy than the respondents with no college credit during high

school. Significance was found in those who had acquired college credit through college-based

curriculum and/or contact with a college campus.

Finally, one’s higher communication confidence led to higher academic self-efficacy

perceptions. As communication confidence increases or decreases, one’s perceived academic

self-efficacy increases or decreases in the same way.

This chapter outlined the statistical procedures and outcomes for the study. Results

indicated that the model in Research Question 2 accounted for only 1% of the variance.

Comparisons revealed several statistical differences impacting academic self-efficacy, most

notably a negative relationship with a type of high school and the strong correlation with one’s

ability to communicate in most situations free of apprehension.

Chapter V will discuss specific applications of these findings, connect the reader to the

literature on the topic, and recommend further research.

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CHAPTER V

DISCUSSION

The purpose of the study was to investigate the effects of a college freshmen’s high

school environment on perceived academic self-efficacy and college-experience expectations.

The methodology also provided an opportunity to explore the impact of gender, confident

communication, and dual enrollment in high school and college classes on academic self-

efficacy, and which types of high schools graduate students with the highest levels of academic

self-efficacy. The following discussion presents the implications of research findings as they

relate to the literature, other research, and future directions for further research. The chapter is

divided according to the research questions that focused the study:

RQ1. Do first-year college students from different high school types (public, private

religious, private college-prep, home school) differ in their academic self-efficacy?

RQ2. To what extent are gender, dual credit coursework, and type of high school

attended contributors to a first-year college student’s academic self-efficacy?

RQ3. Is there a relationship between measures of academic self-efficacy and perceived

communication confidence?

Summary of Data, Methods, and Results

Results of RQ1 were addressed using one-way ANOVA. The findings revealed that, in

isolation, high school type is not significantly correlated to perceived academic self-efficacy of

first-year students. However, significant differences were found among the four types of high

schools when compared to perceived academic self-efficacy. Post-hoc analysis showed private

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religious school graduates scored lower in academic self-efficacy compared to public school

graduates. For RQ2, a regression analysis was used to test for correlations between academic

self-efficacy and high school type, gender, and dual credit. Though the amount of variance was

small, significance was found when the final model included communication confidence. The

combined factors accounted for 17.3% of the variance associated with perceived academic self-

efficacy. This result shows a moderate accounting for the variance in the variables; the social

sciences prefer a correlation of at least 20% to report strong relationship. For RQ3, the

independent variable communication confidence produced two important results: first, an R

square of .41 in bivariate correlation, indicating a strong correlation with academic self-efficacy,

and second, produced a significant negative relationship with private independent high school

graduates.

Results of the Research Questions

The purpose of the study was to investigate the influence of several factors on the

perceived academic self-efficacy of first-year college students. The design was intended to

explore the effect of high school experiences on beginning college freshmen’s academic self-

efficacy, and identify unique markers that create academic self-efficacy levels in graduates from

different types of high schools.

RQ1. Do first-year college students from different high school types (public, private

religious, private college-prep, home school) differ in their academic self-efficacy?

The difference in academic self-efficacy between public and private school graduates was

found to be significant. Additionally, significance can be found in what is not significantly

different. The findings indicate that there is not a difference within the student body educated in

a public school system than the student groups educated in other types of school. Academic self-

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efficacy scores indicated common and stable outcomes inside the four types of high schools.

Students are very much like their peers in their self-evaluation of perceived academic self-

efficacy. The findings for high school type and perceived academic self-efficacy indicated no

difference.

The findings confirm research by Sutton (2000) and Duggan (2010) that showed school

choice is not related to perceived college success. However, the finding of difference between

public and private school settings impacts first-year confidence. It indicates that academic self-

efficacy is lower outside of public school systems. This finding informs the literature on

academic self-efficacy in a new way, as discussed later in this chapter.

According to Astin’s I-E-O theory, college enrollment and other associated perceptions

gained from a student’s cultural background, including the type of high school attended, affect

orientations and ideas related to the college transition (Enberg & Wolniak, 2009). Beginning

students hold pre-existing ideas of the college experience based on inputs determined outside of

the college’s control. Researchers have also examined the inputs of individual cultural and social

capital that precollege experiences create (Engberg & Wolniak, 2009). Bandura (2003) noted that

beliefs shaped in prior educational activities powerfully influence behaviors, and that perceptions

of capability determine a course of action for individuals. These internal judgments of self-

efficacy determine how much effort college students will expend and how long they will persist

through adversity.

There may be several reasons why religious schools display considerably less academic

self-efficacy than public schools. Private religious schools do not lend to raising the academic

self-efficacy of students because that may not be the primary mission. One conclusion that might

be drawn from this finding is that because they are religious schools, a curriculum based on

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values and biblical world view philosophies might lessen the value of one's self perception and

perceived academic self-efficacy. This finding indicates usefulness of further research on what

makes private religious education different from education in a public school system. A

perception of difficulty may be present in graduates of private religious schools, anticipating a

tough road filled with challenges ahead. Though this perceptual “lens” (rosy vs. skeptic) is not

related to issues of first-semester “freshmen myth”, a longitudinal study would bear out any

persistent environmental inputs in the perceptions of incoming students from non-public schools.

There is another conclusion that can be drawn from this study. Whether or not in-coming

first-year student perceptions of their abilities are skewed from reality, new student orientation

programs should emphasize the large difference between high school and college and ready

students from all types of high schools for the coming transition (Tierney & Hagedorn, 2002).

Kirst posited that segments of higher education should function as “bridge” institutions (Kirst &

Venezia, 2004) for less-prepared students transitioning into college. It is the responsibility of

higher education to ease students into and through the last step in a seamless educational system

(Boyer, 1987; Godwin, 2002; Palmer, 2000). Fostering student engagement will influence

perceptions of academic self-efficacy that will in turn influence student’s locus of control for the

college years. Students can see themselves as successful, regardless of their precollege

experiences (Astin, 1993, Pajares, 1996b).

Based on these findings, the research hypothesis 1, a student’s perception of preparation

for beginning the freshman year will be different according to the type of high school attended is

accepted.

RQ2: To what extent are gender, dual credit coursework, and type of high school

attended contributors to a first-year college student’s academic self-efficacy?

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All three of the independent variables were statistically related to academic self-efficacy.

Gender

Among first-year students taking the 2009 BCSSE, females showed statistically higher

academic self-efficacy than males. Scores from male participants fell within the standard

deviation around the mean for gender.

Females’ higher perceived academic self-efficacy is consistent with research showing

females view future challenges with a tenacious outlook ( Chee, Pino, Smith, 2005; Christie &

Segrin, 1998; NCES, 2004b; Ruban & McCoach, 2005). Females starting college have definite

plans to persist to graduation in higher numbers than males (NCES, 2004b). Further confirmation

of this finding is found in the 2009 BCSSE Grand Mean report (see the BCSSE website). In

regards to the three domains that were used in this study to measure academic self-efficacy,

females were similar to males only in perceptions of Perceived Academic Preparation The

difference between the genders emerges in the significant female scores reported on both the

Expected Academic Difficulty scale and the Expected Perseverance scale. Compared to males,

females have a very different perception of academic engagement moving forward.

Astin (1985) and Kuh (2003) note that the engagement of first-year students is based on

the campus culture and fit. Once on campus, females tend to integrate more quickly into the

campus climates, and attachment to it does not produce fear associated with male patterns of

engagement on campus (Wood, 1994; Yakoboski, 2011). Involvement and engagement is seen as

a natural routine for females in the first-year of college (Sontam, & Gabriel, 2012). Perceived

academic self-efficacy in females may be higher, in part,due to parents and family encouraging

engagement and change (NCES, 2007b).

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Precollege Experiences Involving Dual Credit Coursework

Dual credit coursework during high school influences perceptions of academic self-

efficacy. Those who attempt dual credit are higher in perceived academic self-efficacy. Previous

studies have documented similar findings. In contrast, each of the previous studies by Swanson

and Duggan were conducted within a limited context; yet, the findings of this study using a

national sample are in agreement. The large sample of 15,400 first-year students in the present

study provides further support that high school type is not a large part of the academic self-

perception equation.

The literature on early college enrollment indicated that dual credit coursework is

available in all 50 states and is increasing annually in the numbers of participants (Education

Commission of the States, 2011a). In some places, students are acquiring 24 to 36 hours of

college credit prior to arrival on the college campus, creating a difference for advisors and

departmental programs (Swanson, 2008). “Freshmores” (students with 24 to 30 semester hours

complete before the first day of college) are on campus (Jacobson, Nickerson, Polito, & Zunkel,

2012), and causing problems in orientation and mandatory beginning-level student success/FYE

assignments. Additionally, Jacobson et al. found that common classes associated with transcripts

of dual credit students are “core” classes: college English, public speaking, math, and

psychology. Despite the difficulties noted in admissions and advising, dual credit coursework

contributes to a higher sense of academic self-efficacy in the transition to college. Students with

dual credit hours had fewer instances of changing majors and were more likely to complete a

minor or second major (Alwin & Otto, 1977; Tinto, 2007).

The conclusion from the findings of this study is consistent in validating the strength that

early exposure to the college environment brings to the perception of college and change

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(Adelman, 2006; Boyer, 1987). In contrast, this study reveals that early exposure to college

experiences is only one factor of several that together produce academic self-efficacy. Based on

these findings, the Research Hypothesis 2, gender, dual credit coursework, and/or type of high

school will increase or decrease a first-year college student’s academic self-efficacy is accepted

for RQ2.

RQ 3: Is there a relationship between the measure of academic self-efficacy and

perceived communication confidence?

As a result of this study exploring the impact of interpersonal traits in first-year students,

findings showed that a sense of communication confidence is a very large part of academic self-

efficacy. In this study the domain of communication confidence was used to reflect a relaxed

disposition and low-apprehension in speaking. The 2009 BCSSE survey provided students the

chance to respond to items measuring perceived cognitive abilities in communication and asked

if students perceived themselves to be an effective communicator. Together, the responses

measured perceptions of past action, present self-image, and future likelihood of action in areas

involving communication.

The literature on communication showed that low communication apprehension

characterizes numerous psychological strengths (Ortlieb, 2011). Smith et al. (2006) and Hansford

and Hattie (1982) argued communication is the lifeblood of the first-year college student

transition and alone can influence how first-year students are perceive by others on campus.

As cited previously in the review of literature, Bandura (1993) noted the efficacy of

students shape future outcomes through the interplay of language in communicated messages.

Individual differences in student engagement show that the anxiety caused by having to prove

oneself leads to a greater effort in motivation (Sontam & Gabriel, 2012).

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Communication competence has the ability to reduce apprehensions and improve

academic achievement. The items drawn together to measure communication confidence are also

available on other surveys measuring one’s communication style free of apprehensions. Thus, it

can be concluded that communication is integrated within first-year college student academic

self-efficacy, regardless of introversion or extroversion characteristics. Communication

confidence creates and expresses a “can do” disposition, a perceived effortless ease, for a wide

span of life’s situations.

Two important conclusions emerge from the significance of communication confidence

in perceived academic self-efficacy. First, this research confirms the place that communication

plays in the transition to college (Bandura,1995; Smith, Carmack, & Titsworth, 2006; Zychowski,

2007). Students are redefining themselves and negotiating similarities and differences as they

move out of high school and onto the college campus (Astin, 1993). While they are establishing

identity and embracing new labels, they are simultaneously meeting others and forming

relationships. One’s communication style helps or hinders the first-year student negotiate these

initial intrapersonal and interpersonal steps of change (Norton, 1978; Ruban et al., 1993).

Second, the fact that communication confidence created a negative relationship between

private independent schools and academic self-efficacy is notable. It is possible that diverse

communication interactions are not prominent or likely in an independent private school setting.

Highly selective high schools with competitive standards for entry may be enrolling very similar

students. Thus, a shortage of widely diverse conversations may be an environmental factor.

In contrast to relatively widespread notions of superior precollege experiences (Goodwin

& Kemerer, 2002), private independent school graduates may have emerged as having lower

perceived academic self-efficacy for another reason. It is possible that these students perceive

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college interactions to be uniquely different than high school classes. M. Pancer et al. (2000)

noted that students with more complex expectations about the university had stress-buffering

characteristics different than those who had simpler expectations. The negative relationship may

be the result of anticipating excessively complex interpersonal challenges in the transition to

college. Finally, it should be noted that the results show a significant but weak correlation (p=

< .05), and a low academic self-efficacy score for private school graduates does not equate to a

lack of perceived overall college satisfaction or a lower commitment to remain engaged in the

college environment (Chemers et al., 2001). Based on these findings, the research hypothesis 3,

there is a positive relationship between measures of perceived communication confidence and

academic self-efficacy is accepted for RQ3.

Conclusions

Perceptions of academic self-efficacy in first-year students are dependent on gender, prior

college enrollment, and communication confidence. High school environment and experiences

matter more than school choice in establishing academic self-efficacy in first-year college

students. Being home schooled does not affect one’s perceptions of academic self-efficacy.

Females awareness of their academic self-efficacy is somewhat higher than males. First-year

college students with dual credit coursework also have higher perceptions of academic self-

efficacy. Finally, communication is an important mediator of first-year students’ acquisition and

maintenance of academic self-efficacy. These characteristics contribute to shape engagement

patterns and expectations of first-year students as they arrive on campus.

Findings of this study also affect how student outcomes are interpreted at the entrance of

college and inform institutions to improve educational quality through student efficacy, and

develop faculty for student engagement (McCormick, Pike, Kuh, & Chen, 2009). Academic self-

78

efficacy significantly predicted more successful adjustment to the first year of college (Martin,

Swartz-Kulstad, & Madson, 1999). It is preferred over academic ineptitude, as several

researchers have found a close tie between academic self-efficacy and college grades. As a result,

a conclusion then is that measures of self-efficacy can be accurately used to coordinate paths of

success for future educational tasks (Pajares & Schunk, 2001).

Implications for Practice

The dearth of research showed a need for further exploration of sources of in-coming

freshmen academic self-efficacy. Results of this study add to the body of knowledge available to

educational professionals concerned with college-going readiness. Change is imminent during

the college years and perceptions of self-efficacy can be shaped (Tagg, 2008). All types of

students from different environments can benefit from an organizational mindset to improve self-

efficacy during the transition into and through college. Findings of this study show the need for

further research into the ways humans interact with the environment, with knowledge of past

experiences, and with perceptions of well-being.

Several major implications are present. First, choosing a private education over a local

public school is about more than developing an attitude toward future educational endeavors.

School choice results in other differences. As Henig and Sugarman (1999) pointed out, a non-

public education is more about “fit” than college readiness. Furthermore, the fact that the

regression correlation is negative for certain types of high school graduates shows that

perceptions of a satisfying outcome in future endeavors lowers when communication

competencies are factored in.

Second, policymakers benefit by exploring the possibility of linking the school years into

a seamless, accountable system from preschool to college graduation. Acquiring agreement on

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what constitutes knowledge milestones transitioning upward through the system (elementary to

high school, high school to college, etc.) is problematic. This disconnect was noted 20 years ago

when Lieberman (1993) concluded that universities are top-feeders and often set standards too

high for lower levels of education (parts of the educational system) to attain. Hence, students

drop out of the preschool-through-college system before completion. The leakage in the pipeline

is unfortunate (Kirst, Venezia, & Antonio, 2005).

In contrast, Bong and Skaalvik (2003) contend that teachers should do more to fortify the

perceived academic self-efficacy of students, with a goal to improve perceptions of future

performance. This should also focus on curriculum development for males, including ability

inventories, and messages saying, “I see you can do this well; college will be a walk in the park

for you.” Bandura noted the important development of academic self-efficacy through

communicated messages. Dual credit coursework during high school creates predictions of

success, and yet, females dominate the rolls of these courses. Though females enroll in these

classes more often, males must improve their numbers in dual credit and engage in college early.

The effect between academic self-efficacy and dual credit coursework indicates that there

may be a stronger relationship to examine regarding dual credit. For example, this study did not

consider high school Advanced Placement courses as a variable in the academic efficacy

equation. Perhaps further research in this area might indicate that dual credit and Advanced

Placement courses improve the relationship of pre-college experiences and perceptions of

academic self-efficacy. Together, the results of research on dual credit and college prep

Advanced Placement will provide direction for the nation’s school district’s developing new

college-ready curriculum plans.

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Third, trends are changing. It would seem obvious to those interested in student

engagement in the classroom that learning environments, especially communicative ones, create

judgments of success for future tasks (Dorman, 2001). Informing students of what college is and

how it is different than high school will lead to fewer instances of the “freshmen myth”.

Currently, a few institutions have undertaken a promising practice to educate high school

counselors in the differences between high school and college. This audience is critical to the

successful transfer of self-efficacy skills across educational arenas (Hill, 2012; Hong et al., 2012;

Pillemer et al., 1988).

Fourth, the new construct of communication confidence is based on questions associated

with the NSSE Communication Confidence scale. More items added to this scale could improve

the reliability coefficient above 0.66 found in this study. Communication researchers should be

at the forefront on issues related to communication skills and perceived student satisfaction at

college entrance. Internal dialogs remain powerful predictors of one’s perception of future events

(Smith & Zhang, 2010; Tinto, 2004)

Fifth, the public’s proclivity to lampoon home schoolers is moot. This study’s large

sample size, unavailable to previous studies, reveals normality in home schoolers’ perceived

academic self-efficacy. The optimism that the future will be bright due to past experiences

(Pajares, 1995) is unaffected by other factors (communication, gender, etc). Home school

graduates perceived the college-going transition with complete competence.

Finally, gender is a complicating factor. Being female results in significantly positive

academic self-efficacy. Females now attend higher education at higher rates than males,

demonstrate higher academic work ethic than men (Chee, Pino, & Smith, 2005), and also have a

higher estimation of persistence in higher education (NCES, 2004b). The remaining concern in

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the complexity of factors is the potential vulnerability of females’ perceived academic self-

efficacy when enrolled at non-public high school settings (Mottet, Martin, & Myers, 2004;

Simmons, 2008). This study shows a significant negative association between private schools

and academic self-efficacy but did not examine the environment to see if and how women are

affected in those environments. Whether it is smaller class sizes, the gender of instructors, or the

nature of the curriculum, further examination of gender is warranted.

Since precollege experiences might regulate feelings of academic self-efficacy for young

women having recently graduated from high school, college professionals in the area of

orientation would do well to provide information and acculturation activities in gender defined

settings, such as residence halls, Greek information sessions, guest speakers, and first-year

experience surveys. Women and men could be specifically targeted at informational sessions.

First-year students need different messages regarding perceptions of college classes, persistence

though the four years of college, and engagement in meaningful interpersonal communication

prior to the start of college (Jenkins, 2007; Ruban & McCoach, 2005). Sub-groups within the

student affairs division could also present specific messages of academic engagement and

success in the college’s multiple environments and offerings. In summary, academic self-

efficacy is too important to college engagement to judge it as a fixed point of reference and an

unmovable perception. Address it with both genders; do not avoid it.

Implications for Research

Although this research was an attempt to quantify factors contributing to perceptions

within in-coming freshmen, several questions remain. The large sample size from the 2009

BCSSE was sufficient to draw many conclusions from the results. Several of the following

research points could be addressed by studying perceived self-efficacy over several years. Future

82

researchers could also use path analysis and other quantitative research methods to depict the

strength of direct inputs into the academic self-efficacy equation.

The results of this study, paired with previously published self-efficacy research, opens

up possibilities that some preconceived notions of school choice outcomes are incorrect. To

examine these characteristics, researchers should continue to probe for the deep keys to an

incoming first-year student’s perceived academic self-efficacy. This leads to questions regarding

admissions and orientation. An analysis of promising practices that have emerged would show

the expenditure of resources and opportunities being exploited and for the intake of students

from different types of high schools. Since analysis of academic self-efficacy factors show home

schooled students are the only group that is not significantly different than public schools, it

would be helpful to examine the practices of institutions with tools to evaluate precollege

environments (high school type, high school grades, study habits, etc) and rates of degree

completion by type of high school (Cook & Lackey, 1999; Jenkins, 1998).

One aspect of the dataset not examined was the regional density of the significant

findings. NSSE allows schools to examine and compare results based on eight regions of the

United States (see NSSE website); BCSSE does not. With funding of secondary schools tenuous

in some hard-hit areas of the country, public policy would be well-informed to know, that

beyond the rigor of the high school curriculum, how confidently prepared students are for the

first day of college. A regional point of view could determine if academic self-efficacy is a by-

product of regionally-directed school policy (Sewell & Armer, 1966) . For example, perhaps

areas of the United States are doing more to build the academic self-efficacy of young women

entering college better than other areas. Home school students in this study revealed remarkable

sameness, but Arizona might produce different first-year well-being when compared to home

83

school students in Virginia. Dual credit programs and early college enrollment numbers in

certain areas of the United States could build the perceived academic self-efficacy of entering

college freshmen than other areas.

Next, the Communication Confidence scale could include more BCSSE items. It is

imperative, however, to not group all items alluding to interpersonal interactions together and

call them “Competence.”. Experts in the communication field would identify this as a

generalized state of talkativeness, even verbosity. Following Norton’s Communication Style

inventory (Rubin et al., 2000), this research regarded several items on the 2009 BCSSE as

redundant in measuring interpersonal engagement. Including some of those items might increase

the correlation score for reliability. For example, the literature in communication is ripe with

examinations of student-faculty interactions, which this study did not include since pre-college

experiences were not found to be associated with this domain.

The Final Word

The purpose of this study was to investigate the relationship between a high school

graduate’s high school environment and perceptions of academic self-efficacy before the first

day of college. The findings indicated that different precollege experiences produce different

levels of academic self-efficacy. The researcher tested and explained the interconnection of

efficacy and communication competence. As a result of this study, it can now be concluded that

in-coming students perceive higher education engagement differently based largely on traits

honed from their precollege experiences. Finally, the findings and conclusions inform higher

education entities of the need to assess the programs that admit students and open the gate,

improve the ease of transition from inputs to an environment, and judge the value of first-year

student programs that engage students with significantly different levels of academic self-

84

efficacy. This is an enormous and meaningful call to colleges and universities. The transition to

college and the perceived individual changes awaiting first-year students is too important to

leave to chance.

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APPENDIX A

2009 BEGINNING COLLEGE SURVEY OF STUDENT ENGAGEMENT BENCHMARKS

86

BCSSE Scales

BCSSE 2009 Scale Descriptions

cotherint, cfindinfo, ccourdis, caskinst, cfinish, cstaypos

clearnma, cmantime, cgethelp, cintfac

The following BCSSE scales were constructed by converting the responses for each item to a 0-10 range. A mean scale score was then calculated for each student. Below is a brief description of each scale with the component BCSSE items in parentheses.

Expected Academic Perseverance (EAP)

High School Academic Engagement (HSE)

Expected Academic Engagement (EAE)

Engagement in educationally relevant behaviors during the last year of high school.

Student certainty that they will persist in the face of academic adversity.

Expected academic difficulty during the first year of college.

Expected Academic Difficulty (EAD)

cacadpr, cclquest, cclprese, cfacgrad, cclassgr, coccgrp, cfacidea, coocidea

hreadasg, hwrite5, hwrite5m, hacadpr, hclquest, hclprese, hfacgrad, hclassgr, hoccgrp, hrewropa, hfacidea, hoocidea

Expected engagement in educationally relevant behaviors during the first year of college.

Perceived Academic Preparation (PAP) Student perception of their academic preparation.

Student-rated importance that the institution provides a challenging and supportive environment.

cenvscho, cenvsupr, cenvdivr, cenvnaca, cenvsoca, cenveven

Importance of Campus Environment (ICE)

cgnwrite, cgnspeak, cgnanaly, cgnquant, cgncompt, cgnother, cgninq

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APPENDIX B

PERCENTAGES WITHIN BCSSE 2009 FACTORS RELATED TO THIS STUDY

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Total Respondents: 73,274

Gender: Male: 44% Female: 56%

• Public high school graduates: 82%

• Private high school graduates: 4%

• Religious high school graduates: 13%

• Home schooled high school graduates: 1%

Participated in prior college credit/Dual credit coursework: 36%

Responded “prepared” (Likert scale scores of 4, 5, or 6) to Item 17b “I am an effective

communicator.”: 78%

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APPENDIX C

DUMMY CODING FOR MULTIPLE REGRESSION ANALYSIS

90

The variables in Research Question 2 was coded for regression as follows:

• Variable 1: Gender: male = 1 female = 0

• Variable 2: Prior college credit was answered using nominal responses of individuals

regarding past college courses (dual credit, concurrent enrolment, early high school) prior to

taking the BCSSE.

College credit: Response to Item 6c was coded by participation in college courses for

credit: yes = 1, no = 0

• Variable 3: Type of high school. School type will be run in regression as the

independent variable.

Public = 1

Religious = 2

Private = 3

Home school = 4

Research Question #3: Communication Confidence.

To gather a variable reflecting a relaxed communication style, the researcher used a sum

of participant scores from Items 9 J, 9 L, 14 K, 14 O, and 17 B.

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APPENDIX D

IRB APPROVAL

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IRB 12-114 First-Year Self-Efficacy and College Expectations Based on High School Types From: Harmon, Jordan Sent: Tuesday, February 28, 2012 8:36 AM To: Chen, Pu-Shih Subject: IRB 12-114 First-Year Self-Efficacy and College Expectations Based on High School Types Dr. Chen, The UNT Institutional Review Board has jurisdiction to review proposed “research” with “human subjects” as those terms are defined in the federal IRB regulations. The phrase “human subjects” is defined as follows: “A living individual about whom an investigator (whether professional or student) conducting research obtains (1) Data through intervention or interaction with the individual, or (2) Identifiable private information. Since the data you will be obtaining from Indiana University-Bloomington has been totally de-identified, then your use of that data falls outside the scope of the “human subjects” definition and UNT IRB review and approval is not required. We appreciate your efforts, however, to comply with the federal regulations and sincerely thank you for your IRB application submission! If you need a formal letter for your records, please let me know. Thank You, Jordan Harmon Research Compliance Analyst Office of Research Integrity and Compliance Hurley Administration Building 185A University of North Texas P: 940-565-4258 F: 940-565-4277

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