University of Southern California Dissertations and Theses

An examination of classroom social environment on motivation and engagement of college early entrant honors students

(USC Thesis Other)

An examination of classroom social environment on motivation and engagement of college early entrant honors students

PDF

Download a page range

Download transcript

Copy asset link

Request this asset

Transcript (if available)

Content
AN EXAMINATION OF CLASSROOM SOCIAL ENVIRONMENT ON
MOTIVATION AND ENGAGEMENT OF COLLEGE EARLY ENTRANT
HONORS STUDENTS

by

Richard S. Maddox

____________________________________________________________

A Dissertation Presented to the
FACULTY OF THE USC ROSSIER SCHOOL OF EDUCATION
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF EDUCATION

May 2010

Copyright 2010 Richard S. Maddox

DEDICATION

This dissertation is dedicated to my late parents, Ann Maddox who taught me the value
of education and Jim Maddox who taught me the value of hard work and discipline. My
success in academia and life is due to the values of these parents.

iii
ACKNOWLEDGEMENTS
To my dissertation chair Dr. Robert Rueda, my committee members, Dr.
Gisele Ragusa, Dr. David Olsen, my students, CSULA supporters, friends, parents,
brothers and the late Gus the Super Dog for their support, companionship, guidance
and patience throughout this doctoral process.

iv
TABLE OF CONTENTS
Dedication………………………………………………………………………… ...ii
Acknowledgments……………………………………………………………….. ...iii
List of Tables………………………………………………………………………...v
List of Figures……………………………………………………………………. ...vi
Abstract………………………………………………………………………….. ...vii
Chapter One: Introduction……………………………………………………….. ...1
Chapter Two: Description of Literature Search………………………………… ...14
Chapter Three: Methodology…………………………………………………… ...63
Chapter Four: Data Analysis……………………………………………………. ...79
Chapter Five: Discussion……………………………………………………….. ...93
References……………………………………………………………………… ...129
Appendices
Appendix A: Honors Student Study 2008 Instrumentation……………….. ...139
Appendix B: Csula Honors Classes……………………………………….. ...142
Appendix C: Script of Study Solicitation…………………………………. ...143
Appendix D: Consent Form - Adult……………………………………….....144
Appendix E: Consent Form - Parent……………………………………… ...149
Appendix F: Consent Form – Youth………………………………………. ...155
Appendix G: Adjusted Survey Instrument…………………………………. ...160

v
LIST OF TABLES
Table 1: Cooperative Learning Techniques…………………………………... ...29
Table 2: Honors’ Program Estimated Demographics…………………………....64
Table 3: EEP Demographics………………………………………………….. ...67
Table 4: Task-Related Interaction Scale……………………………………… ...69
Table 5: Demographics of the Sample (N = 65)……………………………… ...80
Table 6: EEP Student Characteristics Based on Program Data Collected……. ...81
in 2006-2007-Years 1-3

Table 7: Academic Characteristics of the Sample (N = 65)…………………... ...83
Table 8: Reliability of the Subscales………………………………………….. ...86
Table 9: Reliabilities, Means, Standard Deviations, and Ranges for…………. ...87
the Subscales

Table 10: Intercorrelations of the Main Variables……………………………... ...89
Table 11: Summary of the Multiple Regression Model with Classroom………. ...91
Environment and Motivation Predicting Engagement

vi
LIST OF FIGURES
Figure 1: Patrick (2007) Conceptual Model…………………………………… ...59
Figure 2: Honors Student Study Conceptual Map……………………………... ...61
Figure 3: Regression Model with Classroom Environment and Motivation…... ...91
Predicting Engagement

vii
ABSTRACT
This study set out to examine the relationships between the classroom social
environment, motivation, engagement and achievement of a group of early entrant
Honors students at a large urban university. Prior research on the classroom
environment, motivation, engagement and high ability students was examined,
leading to the assumption that the classroom environment was linked to student
achievement. Early entrant students (n= 65) were surveyed to determine their
perceptions of the classroom environment and their levels of motivation, engagement
and achievement. An instructor support for engagement scale (Ryan & Patrick 2001)
was used as an indicator of classroom environment. A goal orientation scale
measuring mastery orientation, adapted from the Patterns of Adaptive Learning
Survey (PALS; Midgley et al., 1996) was used to measure student motivation and
engagement was assessed using the modified task-related interaction subscale
Patrick (2007). Student achievement self-reported as grade point average (GPA)
was collected. The results of the analysis revealed correlations between the
classroom and student experience (r=.32, p>.01) and engagement (r=, .30, p>.05);
engagement and motivation were correlated (r= .32, p> .01). None of the variables
were correlated with achievement.

1
CHAPTER ONE
INTRODUCTION
According to the most recent data available for the state of California, 15 to
20% of college students drop out each year and nationally the rate has been near 25%
over the last decade. Amazingly, Armstrong’s (1989) quantitative study of college
Honors students using a self report Student Profile Questionnaire and a survey of
student and faculty perceptions, reports attrition rates for college Honors students in
Southern California that average near 30%. Dropout is a serious problem in higher
education and may be an especially critical issue for high-risk fringe groups like
those who are either very low or very high achieving students.
High Ability Honors Students
The needs of high ability and/or high achieving students may be more
neglected than the needs of any other group that is high risk for drop out as these
students are often viewed as the least likely to require special attention. However,
like their low ability counterparts, high ability students are not immune from student
performance problems (Haugen et al, 2004; Neihart et al 2002; Reis 1998). High
ability students may be perceived as low maintenance high achievers who do not
warrant or need attention in order to succeed academically. This misperception may
be based on social myths regarding high achievers and school characterized by the
erroneous notion that, since school is easy if you are smart, then gifted students and
high achievers do not need help or attention because they are smart and therefore
school should be easy (Callahan et al, 2001).

2
Another common misperception is that high ability students such as college
honors students retain those internal salient scholastic qualifications, potential, and
abilities associated with achievement (i.e. intelligence, work ethic, motivation, self-
discipline) so external interventions would be ineffective to pursue or implement.
Yet even considering the positive protective characteristics of high ability achievers,
these top students are susceptible to factors associated with drop out such as
underperformance, disengagement and disinterest in school, though for different
reasons than their low achieving peers (Haugen et al, 2004; Neihart et al 2002).
However, interestingly, one similarity between these groups involves student
feelings of belongingness and peer social connectedness (Baumeister, 1998, Patrick
& Ryan, 2005, Reis, 1998). Dropouts include students who feel disconnected from
their peers regardless of ability. In regard to the population of early entrance high
ability Honors students under current investigation, disconnections from peers and
resulting dropout may be a particular concern. Students with high intellectual ability
may have difficulty truly connecting with peers who are of differing ability levels.
Also, students who are early entrants to college may struggle with building a sense of
connection to more traditional aged college peers in the classroom and may also be
impacted by such factors as emotional immaturity and less developed abilities to
self-regulate and self-motivate which leave them vulnerable to dropout. Gifted
students, such as early entrants, who are grouped with non-gifted students, may have
their opportunities for learning curtailed (Patrick, Bangel, Jeon and Townsend, 2005)
potentially resulting in boredom or feelings of disconnectedness. Since adolescents

3
have a strong desire to be a part of the social world (Santrock, 2004) early entrants’
feelings regarding their associations or disassociations with peers in school may have
particularly negative ramifications in a learning context. The current study proposes
to investigate the relationships between the variables of engagement, motivation and
classroom factors in order to further understand how to best promote academic
success and reduce incidence of underperformance and college dropout within a
population of early entrant high ability students who attend a four year university and
are enrolled in a university Honors program. Enrolled in the particular university
Honors program surveyed for this study, there are college students who have been
identified as high achieving and who followed the standard educational path of
completing high school prior to enrolling in the university. These students are
typically in the age range of 18-20 years of age and above. Additionally, there are
enrolled Honors students who are early entrants to college, students who did not
attend high school and fall within the age range of 11 to 17 years of age. In the
current study, the term high ability or high ability Honors student will be used to
refer to the specific group of early entrant students who are enrolled in the university
Honors program. When necessary to distinguish between the two subgroups within
the university Honors program, the term Early Entrance Honors students (EEHS)
will be used to refer to those honors students who entered college early and the term
University Honors students (UHS) will be used for those students who followed the
standard educational path.

4
The Problem
Data from the U.S. Census Bureau revealed in 2000 that one in three
admitted American students drop out of college, including those identified as high
achieving. In terms of educational research it is as important to understand how to
most effectively meet the unique needs of high ability students as any other at- risk
group. Attention to problems involving high ability students may be especially
important considering that this population may be the most overlooked in terms of
dropping out and yet have the most potential for success and talent development.
Since high ability students may be important future contributors to academia and
society, completing college seems logical and important for the realization of their
talents and development of their potential. As college retention is related to student
performance and preparation (Hertzog, 2004) as well as to self-efficacy and goal
orientation (Carraway, et al., 2003), attention to the performance of this specific
population of high-ability students seems appropriate and justified to address drop–
out risk (Letterman & Dugan, 2004, Reis 1998; Haugen et al, 2004; Neihart 2002)
and to help promote the success of this population which may hold the most potential
as future positive contributors to society through the realization of their academic
talents via higher education (Armstrong et al, 1989).
Engagement and Academic Success
Student academic success is supported by learning methods which increase
motivation and lead to higher levels of student engagement (Patrick, 2007).
Engagement is defined broadly as, “being actively committed or attracted, involved

5
and interacting,” (Merriam Webster Collegiate Dictionary2008; New Oxford
American Dictionary, 2008). In terms of the research literature, engagement is
defined in three ways: Behavioral engagement includes participating or interacting,
and student involvement in both social and academic activities. Behavioral
engagement relates to positive academic outcomes and retention. Emotional
engagement refers to reactions (positive and negative) to people, behaviors and
places including teachers, peers, academics, studying and school itself. Emotional
engagement is related to a student’s connectedness to school and willingness to
complete work. Cognitive engagement refers to the notion of investment,
thoughtfulness and willingness to exert effort necessary to complete school tasks and
master academic material. Cognitive engagement is related to motivational goals and
self-regulated learning (Fredrick’s, 2004).
Engagement as a form of student participation and involvement has been
noted as a possible answer to problems involving declining academic motivation,
retention and achievement (Fredrick’s, 2004). One possible method of encouraging
student engagement is the utilization of collaborative and cooperative learning
methods. Student engagement as collaboration has been linked to effective learning
and student success in a variety of different contexts from elementary grades through
higher education. This includes the areas of teacher-student relations and
achievement (Hughs, Kwok and Loyd, 2008), the positive effects on peer and social
relationships (Roseth, 2008), and the positive effects on student satisfaction (Antil,
1998).

6
Efforts that involve student engagement through collaboration in the
classroom as a way to increase student motivation and success are grounded in
social-cognitive learning theories that stress learning as a collaborative and
cooperative social activity. The beneficial effects of human collaboration and
cooperation have been well established by a variety of disciplines and theoretical
perspectives for centuries (Mead, 1934/1959) and have been adapted in education as
a method to improve learning since the mid 1960’s (Johnson, Johnson & Stanne,
2000).
Collaborative Learning
As discussed above, student interaction with classmates or collaboration has
been related to both motivation and engagement (Ryan and Patrick, 2001). Task
related interactions defined as the extent to which students answered questions,
interacted, explained content and shared ideas with their classmates was used as an
indicator of student engagement (Patrick, 2007; Ryan and Patrick, 2001). Ryan and
Patrick (2001) note that because of the adolescent’s increased capacity for
considering the perspectives of others, being reflective, generating opinions, and
evaluating alternatives, interaction in the classroom may be especially beneficial as
far as learning is concerned, for students in this developmental period. For the
purposes of the current study, the term Collaborative Learning will be defined as any
expression of student engagement involving students working, communicating, and
interacting together in a positive manner in various environmental and social
contexts to achieve a common scholastic objective. Considering these definitions,

7
task related interaction would clearly be construed as collaborative learning.
Collaborative learning can include both informal student interaction (e.g., discussing
an assignment over lunch) as well as more formal teaching methods that incorporate
structured group interactions such as Cooperative Learning methods (Dillenbourg,
1999; Johnson and Johnson, 2001; Sherman, 1991). Cooperative Learning involves
teachers directing students to work in small groups to achieve a common goal;
groups may vary in duration dependent on the task and course objective (Ormrod,
2004). Cooperative learning groups have been noted as helpful in allowing students
to clarify assignments, provide assistance with notes and meet class goals in addition
to providing a general sense of support and feelings of belonging (Ormrod, 2004).
Additionally, other student interaction for the purposes of academic success such as
peer-assistance and peer tutoring will be considered under the category of
Collaborative learning for the present study.
Motivation
Another important factor, which may contribute to academic success, is the
level of student motivation for learning. Motivation can affect both new learning and
the performance of previously learned skills; motivation affects what, when and how
students learn. Students motivated to learn are apt to engage in activities they believe
will help them learn (Schunk and Pintrich, 2008). In other words, motivated students
are oriented toward and engage in learning methods. This behavior likely leads to
rewards that are intrinsically valued by the motivated student that then lead to
continued motivation to learn, a dynamic between the individual (behavior and

8
cognition) and the environment; thus tridactic reciprocality exists. This study will
focus on aspects of motivation that may include efficacy, task value and goal
orientation that may be related to class factors.
Classroom Factors
Because student perceptions of the classroom environment influence their
beliefs about themselves (efficacy) and these beliefs then influence the nature and
extent of engagement in academic tasks, the association between student perceptions
of the classroom and engagement is presumed through social cognitive theory to be
mediated by motivational beliefs (Patrick, 2007). Classroom factors or classroom
social environment has been noted to play a role in student engagement, motivation
and school success (Patrick, 2007). Class factors include affiliation, fairness,
cohesion, mutual respect and support from teachers and peers. The current study will
extend the work by Patrick (2007) by exploring one specific class factor, teacher
support. Specifically this study will explore the relationship between teacher support
for peer related interaction and collaboration among high-ability college Honors
students as mediated by motivation.
Promoting Academic Success in High Ability Students
Honors faculty may often assume high ability, motivated, independent, and
engaged students. However, some high ability Honors students do not achieve well
in these classes even though they have high ability. A possible reason for this
discrepancy is that assumptions about student learning may not be justified for this
population. Classroom structures and activities may need to be organized differently

9
to promote more effective learning, especially at the college level where instructor
support or structure may be less prominent than in high school. One re-
organizational possibility is collaborative learning, which has been shown to be
beneficial for a variety of students in different contexts. Currently, collaborative
learning as an influential factor in student performance enhancement is commonly
accepted, yet there is a gap in understanding exactly how to most effectively
motivate high ability students toward engagement in collaborative learning efforts in
a university Honors context. Understanding this factor may be particularly important
as battling student disengagement and disconnectedness and encouraging peer social
relatedness and belonging, is important to discouraging underperformance and drop
out (Baumeister, 1998, Neihart, 2002).
Statement of the Problem
The underperformance of high ability students who achieve at lower than
expected levels is a continuing issue. The present study is motivated by this specific
pattern in the context of a four-year university honors program. One possible
explanation for this performance problem may be related to classroom factors that
affect student motivation and engagement in the use of learning strategies like
collaboration and self-regulation. Though relationships between the classroom
environment (e.g., level of teacher support for student collaboration), student
motivation, engagement and achievement have been established (Patrick, 2007),
current class designs and practices may not provide the support necessary for student
engagement.

10
Purpose of the Study
More completely understanding classroom factors in relation to addressing
performance problems is worthwhile since classroom factors, unlike certain stable
student characteristics such as family and school history, intelligence and
temperament, are malleable and may be manipulated to improve student success. The
nature of the relationship between these factors and student achievement is not fully
understood and, for this particular student population of university honors students,
is virtually unknown. The purpose of the present study is to investigate the
relationships between classroom factors, student motivation and engagement for high
ability early entrant students in Honors classes in order to potentially resolve
underperformance problems. These relationships will be examined through assessing
student perceptions of classroom environment, student level of motivation, and
student level engagement as measured by the amount of student collaboration that
occurs. The information gleaned may be useful in the following three areas:
improving student academic performance, strengthening existing and future Honors
program curriculum, and informing educational research literature on classroom
social environment and engagement.
Significance of the Problem
The importance of improving academic performance through understanding
the mechanisms involving student engagement in collaborative learning efforts, is
important as high ability students who underperform represent a valuable lost
resource. Presently, there is particularly little known of the relationships within a

11
college honors environment between classroom factors and student learning
variables. Understanding these relationships may be especially important for high
ability Honors students whose learning needs may be overlooked or underestimated.
Discovering the educational factors affecting high ability students’ performance may
contribute to increases in effective performance, satisfaction, retention and
graduation of these high-potential students.
The importance of the current localized problem involving high ability early
entrant Honors students’ under performance and Honors classroom factors is greatly
enhanced/accentuated by links to larger socio-economic factors. The success of high
ability students may be especially relevant to the continued success of university
Honors programs and on the ability of the university themselves to attract and retain
top performing students. High ability Honors students’ success is then linked to the
success of the university as a social institution. Assisting high ability Honors
students toward academic success would benefit the students, Honors Programs,
university, the nation and society in general. By increasing our knowledge base and
implementing appropriate classroom improvements based on this knowledge, future
generations of high ability students may be more academically successful and
thereby may more easily reach their full potential as citizens and as future
contributors to the economy and culture. Despite the importance of the current
problem, there are factors that may influence this research effort and these will be
discussed next.

12
Limitations
There are several limitations of the present study that include the following
three factors:
1. The populations of Honors students under review are only those that are
early entrants to college from the EEP, thus limiting the generalizability
findings to larger, traditional populations of Honors students.
2. The researcher’s role as a university administrator of the early entrance to
college program may be known to participants.
3. The majority of student participants have limited experience as Honors
students; their responses may reflect attitudes and perceptions more
heavily influenced by their previous traditional secondary school
experiences.
Delimitations
Delimitations of the present study may include the following four factors:
1. Time, project scope and resource constraints will limit the data analysis to
only several possible variables related to the research questions. Factors
that include age, gender and experience will be minimally tested and used
in the analysis. Also, only several variables used in the model research by
Patrick (2007) will be assessed.
2. Only quantitative data will be collected, though qualitative data gleaned
from interviews would strengthen the study by potentially discovering
specific class factors that may lead or inhibit collaboration. Also, specific

13
student collaborative behaviors that may lead to academic achievement
will not be discovered through use of the present research design.
3. Data is limited to early entrants enrolled in Honors classes with honors
faculty. Top performing student perceptions may differ greatly from
mainstream student populations, and faculty selected to teach honors
courses may use different teaching practices and styles than other
university faculty. The study will not assess traditional university
students, courses, or faculty.
As a teaching university, the results on classroom practices at CSULA may
not translate to larger research based universities.
To fully investigate the relationship between classroom factors, motivation
and engagement (collaborative learning), a review of the related literature will
follow. This literature review will explore the theoretical underpinnings of
engagement including social learning, social cognitive and social constructionist
theories, will provide an overview of characteristics of high ability Honors students,
will discuss classroom factors, review motivational variables, and provide a
summary of patterns in the research and potential current knowledge gaps.

14
CHAPTER TWO
DESCRIPTION OF LITERATURE SEARCH
The literature search was conducted using the following general parameters:
The search was limited to research with publication dates between 1995 and 2008
and focused on school/education learning based, peer-reviewed work. The search
terms included collaborative and cooperative paired with learning, classroom,
motivation, value, and intrinsic value. Additionally, the term student was paired with
collaborative and cooperative and the following pre-fix terms: honors, gifted early
college entrance, and high ability. Literature searches on ERIC for all peer reviewed
work from the last ten to fifteen years, with the number of items discovered, in
parenthesis, are as follows: using the terms cooperative learning (882) adding the
term motivation (78), adding the term engagement(43), adding the term Honors (1),
adding the term early college entrant (0) and for collaborative learning (915) adding
the term motivation (57), adding the term engagement (48), adding the term Honors
(1) and adding the term early college entrant(0). Searches combining the terms
cooperative and collaborative learning, motivation and honors resulted in only two
items and only four items when the term classroom factors was also added to the
search parameters. No items were located when the terms college, higher education,
gifted student or early college entrant were combined. Clearly, there is a gap in
research specific to the variables presently under consideration involving classroom
factors related to collaborative learning of high-ability college honors students.
Moreover there is little research available on cooperative or collaborative learning

15
and honors students in general and minimal contemporary studies on either
cooperative or collaborative learning or motivation (i.e. 78+57=135) and engagement
(43+48=91). Research is needed to help discover the relationships between
classroom and motivational factors and collaborative learning for high-ability college
students. Those ten articles and empirical studies assessed as most pertinent to the
present investigation were collected and are reviewed in detail.
During the literature searches, several thematic gaps in the research emerged.
While work on cooperative learning was numerous, the majority of research
involved qualitative investigations of teacher perception regarding strategy
implementation, studies of strategy use on elementary school environments and
students, studies specific to the design and implementation of various policy and
strategy designs and several meta-analysis of such work previously completed.
Examples from these types f research are included in the present review, yet much
additional research is apparently needed for the subject area.
Honors Students, Giftedness and Achievement
Characteristics of High Ability Honors Students
Understanding the characteristics being applied to the student population
currently under investigation is important, so a literature search was completed for
research on the characteristics of high ability students and, specifically, university
Honors and early entrance to college students. Unfortunately, few studies exist on
the characteristics of university Honors students using the research parameters
previously defined. One reason for this may be the difficulty in fully and accurately

16
defining high ability students. Motro and Yuan (1990) acknowledge the ambiguous
nature of defining the characteristics of an Honors student. This difficulty resulted in
the authors recognizing the most common defining feature of an Honors student as
academic performance measured by grades or grade point average (GPA).
High Ability Honors Students and Learning
In a qualitative study examining Honors students’ orientation toward learning
in higher education, 25 Honors students were interviewed and Honors classes were
observed with the goal of identifying various types of student learning and realities
(Storrs & Clott &, 2007). Storrs & Clott (2007) utilized a symbolic interactionism
framework. This is a perspective that perceives student learning as a cultural process
using students’ feelings and interpretations of school experiences. The purpose of the
study was an effort by the author to establish the limitations of students’
humanitarian growth, as reflected by a liberal arts education, completed within a
dominant business model and culture of higher education. The study objectives
included contrasting liberal arts and business oriented education models for high
achieving students within small liberal arts school environments. Data from the
study identified four learning types for Honors students: The first type was termed
Liberal Scholar; these are Honors student who embrace a liberal arts education. The
second type was termed Getting By; these are students who are successful yet
minimally curious or engaged. The third type was termed Players; these are students
who were academically engaged, future-oriented and performance-oriented. The
fourth type was termed Critical Player; these were students who tended to have a

17
mastery orientation and who felt pressured away from a liberal arts education to
more narrow specialties, more congruent with a business model (Storrs & Clott ,
2007).
The authors acknowledge that these student types are not exclusive but
dynamic and shifting and that other factors can effect students’ perceptions of their
own learning. Examples of factors that help shape Honor student perceptions and
learning include: previous academic experiences, family characteristics, and
individual biographies that could involve psychological, emotional and personal
characteristics (Storrs & Clott , 2007). The present study seeks to further the
understanding of some of these factors related to Honors students’ perceptions of
their own learning.
High Ability Honors Students and Giftedness
Giftedness is one personal characteristic that may be included as an Honors
student characteristic, both universally and particularly in the current study. As
noted, a large number of the Honors students surveyed in the present study were
admitted to the university as gifted early entrant students. Due to the tremendous
ambiguity in defining and characterizing a gifted and talented student, identifying a
universal list of characteristics is a significant challenge. Although perhaps not
universal or exhaustive, one standard used to define giftedness includes observing
the following six criterion types: general intellectual ability, specific academic
aptitude, creative or productive thinking, leadership ability, visual or performing arts
ability and psychomotor ability (Colangelo 2002). The first three criteria seem most

18
applicable to characterizing the population of Honors students currently under
review as they are likely most applicable to a college Honors students who may not
be involved in leadership, psycho motor or art related activities. Learning activities
and class success may be influenced by Honors students’ general academic ability,
academic aptitude and critical thinking skills.
A more contemporary investigation of giftedness by Cigman (2006)
classified gifted students using an environmental framework where the term bright
substitutes for gifted. This framework defines giftedness through intelligence testing
and academic performance standards (top 1-5% of students). Gifted students were
characterized within four dimensions: The first is the child who is very bright and
benefits from a propitious environment. The second is the child who is very bright
but lacks a propitious environment. The third is the trophy-child who achieves
highly as a result of a pressured environment, but who seems 'not bright' or only
'moderately bright' and is strained or alienated by the experience. The fourth is the
child who seems 'not bright' and also lacks a propitious environment. Environmental
factors, including parenting techniques and classroom structure, were important
variables identified in this study that influence assessment of a child as bright or
gifted. In general, the school environment was established as being very influential
in the identification and development of gifted students and the learning process. The
author notes that natural ability (giftedness) and the environment are deeply
intertwined and a discouraging, unsupportive learning environment may neglect the
gifted child’s natural ability. It is important that educators try to understand

19
interactions between high-ability students’ natural abilities and the learning
environments (Cigman, 2006). Gifted students’ unusual ease or mastery of material
allows them to note they are different from others and similar to each other, thus
learning with similar peers seems a logical and effective method to address learning
(Cigman, 2006). These findings give particular credence to the importance of
understanding the influence of class factors on the learning process for Honors
students.
Colangelo (2002) noted some defining characteristics of the gifted student.
In general, Colangelo suggested that gifted students are as well adjusted as same age
peers. However, social and emotional issues may be present due to their exceptional
abilities. Also, adolescence is a particularly difficult period for gifted students as
gifted students are generally more sensitive to the social needs of non-gifted peers
than the inverse. This sensitivity to the social environment and sensitivity to peer
interactions may be an important discovery in relation to the present study. Most
gifted students are not, as commonly perceived, loners who are insensitive to the
social needs and cues of others. Therefore, for these students feeling a sense of
engagement and collaboration with teachers and peers may be particularly important
for learning and academic success, especially when collaborating with like-ability
peers (Colangelo 20002; Cigman, 2006).
Further supporting this supposition, Noble (2007) conducted a qualitative
follow-up study on the experiences of early college entrants specifically focused on
the long-term effects and experiences of students. Over 200 student participants in

20
the Early Entrance Program (EEP) were sent survey questionnaires with a response
rate of 45%. The 100-item questionnaire focused on participants’ assessments of
their educational and work experiences, friendships and social lives following
completion of college. Overall, analysis of the qualitative data revealed that the early
entrance to college through the Early Entrance Program had a profoundly positive
effect on students. It is especially interesting to note that the factor that was
identified as the most beneficial aspect of this experience was peer group support.
The benefit of peer interactions was noted as affecting both the social and intellectual
development of the students in a positive manner. This gives further credence to the
importance of connectedness and collaboration for high ability students. While it
was revealed that social influences and peer support were reported to be extremely
beneficial, little was discovered in the study regarding how the school environment
may help promote these helpful peer interactions or collaboration. The present
study seeks to begin to fill in this important gap.
Academic disciplines and the Honors Program
As the present study will draw a sample of students from a variety of Honors
classes spanning various disciplines, a better understanding of any disciplinary
distinctions and characteristics seems prudent.
Pollio (1996) conducted a qualitative study on the pedagogical differences
between the disciplines of natural sciences and humanities to determine how
individuals in various disciplinary areas view their own field as related to other
fields. Two hundred and twenty two faculty members from 36 fields of study were

21
surveyed on the characteristics of their discipline as related to teaching and learning.
Data was analyzed using non-metric scaling, resulting in a classification schemata or
taxonomy characterized along the following two contrasting dimensions: humanities
or sciences/mathematics and physical or social. Of specific interest to the current
review are results revealing differences in social relationships and the student
learning that may occur in various types of classes. Results indicated that natural
science faculty reported more frequent team or collaborative teaching and research
efforts. Humanities faculty indicated greater preference for teaching than research
and viewed research as a more individual pursuit than cooperative group activity. In
general, Pollio (1996) noted the pursuit of knowledge is often more solitary for
humanities faculty than natural sciences faculty but humanities faculty were more
likely to encourage student participation and involvement in class. Pollio (1996)
suggested that natural science faculty were more effective than humanities faculty in
classroom form and procedure and in preferring collaboration in research.
Humanities faculty were rated as better in interacting with students and encouraging
student involvement (including collaboration and peer assistance efforts) but
preferred solitary research endeavors. In regard to goal orientation, results indicated
science faculty were more inclined to support performance or grade based goal
orientation whereas humanities faculty focused on learning and mastery based
orientation. This data on faculty preferences and class type may be especially
informative with regard to addressing the current research question involving
understanding the class factors that may contribute to student collaboration.

22
Theoretical Underpinnings: Social Cognitive Theory and Social Constructivism
Current thoughts within the field of education on the importance of
engagement and collaboration in learning have evolved from seminal theoretical
works such as social cognitive theory, social learning theory and social
constructivism which address the role of human interactions and the environment in
learning. Following is a discussion of the theoretical foundations relevant to the
present study.
Social Cognitive Theory
According to Bandura (1989), peoples’ behavior tends to reflect what they
have learned socially. Bandura termed this interactive learning dynamic triadic
reciprocality whereby human functioning is explained in terms of behavior and
cognition shaped in a social context. Each factor is a determinant of the others
(Bandura, 1986). In regard to learning, social cognitive theory postulates that
individuals learn skills and strategies by observing models and then demonstrate
what they have learned when needed and motivated to do so. Behavioral change is
thought to be dependent on the interactive and dynamic factors of environment,
people, and behavior (Glanz, 2002).
Bandura’s theory rests on three major factors. The first is Triadic
reciprocality where behavior is driven by interactions of personal, environmental and
cognitive factors. The second is that learning and involvement (engagement) may be
future events where learned behaviors and/or skills are not exhibited until
appropriately motivated. The third factor is that enactive and vicarious learning can

23
occur. Enactive learning involves learning that is based on experiencing the actions
of others. Vicarious learning is learning that occurs from observing models that may
be in-person, symbolic, or in print form.
The conceptual model of social cognitive theory can be illustrated as a
triangulation of the three factors behavior, environment and personal (Ormrod,
2004). This model has several important educational implications, including the fact
that students may often learn simply by observing their peers, the consequence of
student behaviors may shape future behaviors, modeling may be an effective method
to change student behavior and teachers, and that other adults, such as parents, and
peers can all model appropriate learning behavior (Ormrod, 2004).
Nearly all cognitive science theories entail some form of constructivism.
This continuum ranges from the individual constructing knowledge in the class
environment through personal information processing to the view that knowledge
develops as one engages in dialogue and interactions with others (Palincsar, 1998).
The importance of constructivism in understanding the process of learning suggests
that an exploration of social constructivist theory is warranted.
Social Constructivism
Learning is characterized as a duel process involving the individual and the
group. Group learning involves socially constructed knowledge. This is a socially
based construct that is related directly to the present discussion of collaboration and
peer interaction (i.e. knowledge is constructed socially). Palincsar (1998) notes that
the post-modern social constructivist rejects the view of the locus of knowledge

24
resting with the individual for the perspective that learning and understanding are
inherently social and cultural activities. Constructivist tools are regarded as integral
to conceptual understanding (Palincsar 1998).
Social constructivism as a learning process involving the social construction
of knowledge is akin to collaborative learning involving peer interactions that lead to
the achievement of learning objectives and knowledge construction.
Underperformance may occur if students are not participants in the construction of
class knowledge. Aronson (2002) notes the importance of social context in
education. He suggested that the way things are presented and described (the social
context) affects our judgments and, by extension, our learning. The following four
aspects of social context were noted as a basic principal of social thinking: a)
comparison of alternatives, b) situational thought, c) decision framework and d)
presentation of information (Aronson 2002).
All constructivist theories view learning as a process where students build
understanding and knowledge on the basis of experiences, peer interactions and
active involvement. Task-related interactions or peer collaboration plays a major role
in promoting learning and conceptual understanding (Patrick, 2007). Interaction
encourages students to integrate information, explain it in their own words, and
consider others’ perspectives in a process of evaluating data to form ideas and
understanding. High-level thinking and strategies are most appropriate for this type
of social-constructivist interactive learning (Ryan 2001) and such higher-order
strategy use is most appropriate for high ability students (Patrick, 2005).

25
Social Cognitive and Social Constructivist theories share a common theme of
understanding learning as a process that occurs in a social context through
interactions between individuals and their social environments. Engagement and the
related concept of collaboration explore how this understanding of the learning
process translates to education.
Engagement: Definitions and Importance
Engagement
Student engagement as a solution for motivation, underperformance, drop out
and achievement problems is increasingly popular among educators and can be
characterized as involving students who are actively committed, involved, and
occupied in participating in learning (Fredrick’s, 2004). Research has identified
three distinct forms of engagement. These are behavioral engagement, emotional
engagement, and cognitive engagement (Fredrick’s, 2004).
Behavioral engagement is defined as involvement in social, academic or
extracurricular activities. Emotional engagement involves both positive and negative
reactions to teachers, peers and institutions. Cognitive engagement involves the
notion of investment, thoughtfulness, and willingness to exert effort. These factors
involving student cognition, emotion and behavior are considered to be dynamically
interrelated. Fredrick’s (2004) notes support for positive correlations between
student engagement and achievement related outcomes.

26
Self-Regulation and Engagement
Self-regulation refers to the degree to which students are metacognitvely,
motivationally and behaviorally active participants in their own learning process.
Self-regulation is a process that promotes learning whereby students activate and
maintain behaviors, affects and cognitions oriented toward realizing their academic
goals (Zimmerman, 2000). This includes the extent to which they use learning
strategies to achieve goals and manage their learning processes (Schunk &
Zimmerman, 1998). Through this participatory activity in the learning process, self-
regulation may be categorized as a type of engagement.
Self-Regulation has emerged as a method to improve student performance
especially for gifted underachievers (Ruban & Reis, 2006). In a study on
perfectionism, goal theories, and gifted students, the authors noted that one
characteristic common to all three types of gifted student goal-orientation was the
characteristic of evaluation. Gifted students have a tendency to evaluate their work
and performance and this is a self-regulatory behavior.
A mixed methods study exploring the nature of self-regulation strategies
among different populations of college students was conducted by Ruben and Reis
(2006). Two groups of students from a northeastern university comprised of low
achieving at-risk and high achieving honors students were assessed using a self-
report instrument entitled the Learning Strategies and Study Skills (LSSS) measure.
This instrument was designed to elicit information about students’ use of self-
regulation strategies. Quantitative and qualitative data analysis revealed that, in

27
general, high achievers were more likely to use self-regulatory strategies. However,
there were several other characteristics discovered that may be of importance to the
present investigation. This includes the finding that the Honors students sampled
used more advanced deep processing strategies (i.e. organizing, interpreting, and
condensing data) as opposed to surface processing strategies (review and rote
memorization). High achievers exhibited an enhancement model of learning as
opposed to the survival model demonstrated by low achievers. In summary, Ruben
and Reis (2006) noted the positive relationship of self-regulation and achievement,
suggesting that self-regulation enhances motivation. They also put forth that self-
regulation is a learned skill and that there are important differences related to self
regulation strategy use for high achieving Honors students as compared to other
populations.
As peer interactions, collaboration, and self- regulation are student activities
that have been noted as expressions of student engagement and achievement
(Glanville, 2007; Patrick, 2001, 2005, 2007, Ryan, 2001), it is essential to explore
the relevant research in these areas.
Collaborative Learning
Collaboration as an effective and positive human social trait and behavior has
been firmly established for several decades (Kropotkin, 1902; Mead, 1934; Axelrod,
1984). People in general and adolescents specifically, have indicated an important
concern for how others react to or like them (Santrock, 2004). According to
sociological theory, people have an overwhelming desire for others to like them and

28
to have social connectedness. Such concerns for connectedness may be greatest in
adolescence (Aronson, 1992, 2002). Essentially, we like people who cooperate with
us more than people who compete with us or criticize us (Aronson, 1992, 2002).
Collaboration then seems an organic and appropriate method to foster learning and
address student performance gaps, perhaps especially for gifted adolescent students
(Patrick et al., 2007). As mentioned previously, collaboration in learning may
include, for the purposes of the present study, the concepts of more formalized
cooperative learning teaching strategies, peer assistance, peer tutoring as well as
general collaboration/task-related interactions (Patrick, 2005).
Cooperative Learning
Cooperative learning may be broadly used to refer to any instructional
method in which students work together in a somewhat structured format to achieve
a shared learning goal. This term may also refer more specifically to one of seven
major structured forms of teacher implemented cooperative learning techniques.
These techniques are defined as specific, structured teaching strategies as seen in
Table 1 (Sherman 1991; Johnson and Johnson, 2000).

29

Table 1: Cooperative Learning Techniques
Researcher-
Developer
Date Method Description
Johnson &
Johnson
Mid
1960s
Learning
Together and
Alone
5 key elements:
Positive interdependence, individual
accountability, face to face interaction, teaching
collaborative skills, processing group interaction
DeVries &
Edwards
Early
1970s
Teams-
Games-
Tournaments
(TGT)
Teacher provides lecture/instruction. Students
assigned to pairs or teams to study material.
Students play weekly academic games in
tournaments to demonstrate individual mastery
of material. During games, students are teamed
into tables of three comparably performing
students and maintain this team for
approximately 6 weeks. At the end of the
tournament, team scores are used to determine
recognition and awards.
Sharan &
Sharan
Mid
1970s
Group
Investigation
Facilitates cooperative learning through
organization of entire classroom into
investigative groups. Groups are heterogeneous.
Teacher chooses subject area to investigate and
students divide into groups to research subtopics
and information is shared within and among the
groups. Teacher’s role is to guide construction
and progress of student investigative groups.
Johnson &
Johnson
Mid
1970s
Constructive
Controversy

Aronson &
Associates
Late
1970s
Jigsaw
Procedure
Each group member has a piece of the
information needed to complete the required task
and group members must cooperate in order to
obtain all needed information and complete the
task. Group success is dependent on all
members mastering all of the parts.

30

Table 1, Continued
Slavin &
Associates
Late
1970s
Student teams
Achievement
Divisions
(STAD)
Teacher provides lecture/instruction. Students
are assigned to heterogeneous teams to study
material for quiz on topic. Students receive
individual scores as well as contribute to a team
score. Individual’s team scores are determined
based on improvement from past quiz scores so
that all may have an equal potential impact on
the team score. Team scores are used to
determine recognition and awards such as
certificates.
Cohen Early
1980s
Complex
Instruction
Used to teach higher academic level utilizing
open ended, interdependent group tasks in a
classroom organized to maximize student
interaction.
Slavin &
Associates
Early
1980s
Team
Accelerated
Instruction
Combination of individualized instruction and
team learning focused on mathematics.
Students are placed in heterogeneous groups but
work on individually appropriate mathematics
materials. Teammates grade each other’s work
according to answer keys. Team scores are
determined by the average number and accuracy
of units completed by team members. Teams
which meet preset criteria for success are
provided with rewards and recognition.
Kagan Mid
1980s
Cooperative
Learning
Structures

Stevens,
Slavin, &
Associates
Late
1980s
Cooperative
Integrated
Reading &
Composition
Teachers use readers and reading groups.
Student’s teams are composed of pairs of
students from different reading groups. While
teacher is working with one group, students in
the other groups work in pairs to master reading
and writing tasks.

31
Cooperative learning whereby students work in small groups to achieve a
common goal provides a means through which students can clarify assignments as
well as help provide a support system for one another, may lead to higher self-
efficacy and achievement. Cooperative learning strategies serve to create models for
effective learning and problem-solving strategies for students who are engaged.
However, for cooperative learning to be successful teachers must structure classroom
activities in such a manner that cooperation is both helpful and necessary for
academic success (Johnson and Johnson, 1991). Class factors and faculty
involvement are then an important factor in the implementation of cooperative
learning strategies and likely overall collaborative efforts as well.
A study by Antil et al. (1998) examining the prevalence and forms of
cooperative learning used among elementary teachers was reviewed. Among the
topics addressed in the study was the prevalence of cooperative learning; the shape
cooperative learning takes in the classroom, the correspondence between classroom
and research models of cooperative learning, as well as the teachers’ reasons for
using cooperative learning. Additionally, the capacity of cooperative learning to
address academic and social goals in the heterogeneous classroom setting was
assessed. Eighty-five teachers from four urban and two suburban elementary schools
were surveyed and 21 were selected for interviews. Survey questions sought
information on their utilization of cooperative learning practices. Interviews were
also conducted and sought information on a) teachers’ current use of cooperative
learning, b) teachers’ goals and rational for cooperative learning strategies and c)

32
teachers’ judgments about the efficacy of cooperative learning strategies. Data was
analyzed with qualitative data transcribed and coded using Ethnograph software. In
regard to the reasons for using cooperative learning, the results indicated the
following four major themes: academic learning, active involvement, social learning
and teachers’ personal experiences as learners. The latter, interestingly, was
described as how teachers recalled cooperative learning from their own past school
experiences. Results indicated that all teachers reported using some form of
cooperative learning, though they used different grouping strategies and aspects of
traditional cooperative learning format. Such individualized versions of cooperative
learning were modified from Johnson and Johnson’s (1991, 2000) model and the
five-element standard for cooperative learning strategies. Results indicated that the
most critical element of cooperative learning was noted as positive interdependence.
This is the belief that one can only reach their learning goals if others also reach their
goals. Positive interdependence can be a malleable class component (Ghaith, 2007).
The teachers perceived overall cooperative learning as a method to achieve
academic and social benefits and to improve student participation and engagement.
The utilization of these techniques corresponded to their personal beliefs in the
benefit of learning together. Antil et al. (1998) noted that findings of their study
revealed that instructor support for cooperative learning is essential and that
cooperative learning strategies were most effective when under faculty influence or
control. The issue of teacher or faculty influence or control in the classroom may be
of particular relevance to the present study as college faculty may be accustomed to,

33
desirous of, and comfortable with control over pedagogical processes that encourage
support for student collaboration.
Johnson, Johnson, and Stanne (2000) produced a comprehensive review of
literature on the effectiveness of increasing achievement through the use of
cooperative learning strategies. This meta-analysis reviewed several studies within
the field in order to describe and determine the empirical support validating the
effectiveness of the different methods of cooperative learning in education. These
authors discovered that there were at least 164 studies on specific cooperative
learning methods and that seven of the distinct cooperative learning methods
identified have been subjected to empirical validation (Table 1). All of the
cooperative learning methods studied were found to relate to significantly higher
achievement than competitive or individualistic learning approaches, although effect
size varied dependent on the particular cooperative learning method utilized. The
characteristics of the most effective methods were determined to be those methods
that were more direct-oriented and more conceptual, as these characteristics provided
teachers with the most structure, flexibility and freedom regarding cooperative
learning implementation and specific strategy design. Direct-oriented methods refer
to very specific, well defined techniques teachers employ, and conceptual methods
are general frameworks teachers use as a template to structure lessons.
As cooperative learning has been noted to exist when students work together
to accomplish a learning goal (Johnson & Johnson, 2000), peers assisting one
another, or collaborating, may be classified as a component of cooperative learning.

34
Tutoring is one of the more common forms of academic assistance and has been
noted as having a positive impact on academic achievement, persistence and
graduation (Hodges & White, 2001). The majority of college students, both low and
high achieving, showed a high preference for peer teaching and discussion (Butler,
1992). Considering this information, peer tutoring seems appropriate to explore more
fully in regard to the present study.
Peer Tutoring
Peer tutoring has been noted as an effective alternative teaching strategy and
has been shown to have a positive impact on teaching fundamental knowledge and
skills (Ormrod, 2004). Peer tutoring has also been found to have a positive impact on
learning outcomes (Hendrickson, 2005), grades, course completion and retention
(Weinsheimer, 1998), student attitude (Hodges, 2001) and writing skills (Griswold,
2006).
Butler (2006) completed a literature review and analysis n peer tutoring and
cooperation, specifically changes in college teaching related to peer support,
discussion and cooperation (Bond, 2006). The author notes that the majority of
college students, including high achievers, display a high preference for peer
teaching, discussion and cooperative learning. Analysis of related literature
indicated that females tend to prefer collaboration at a higher rate than males. Butler
(2006) hypothesizes that learning to teach, (i.e. peer tutoring efforts), facilitates
intrinsic motivational processes that supports conceptual learning. Her hypothesis
was based on research comparing students asked to learn data with the purpose of

35
teaching it to other students as opposed to students asked to learn data for a test.
Results showed that the first group displayed higher conceptual learning and
perceived themselves to be more actively involved (engaged) in the course than the
second group. Collaboration, as peer tutoring, then may be related to motivation
and effective learning for college honors students. Understanding the relationships
between the class environment, motivational processes, and collaboration is the
objective of the present investigation and may be associated to the proposed link
between tutoring and motivation reported by Butler (2006). The present research
may better inform this potential relationship.
Collaborative Learning Conceptualized Using Social Cognitive Learning Theory
Collaborative learning may be characterized through a socio-cognitive
framework as a learning strategy involving the interaction between personal,
behavioral and environmental factors. The hallmark of collaborative learning is that
individuals learn from each other in a social context, thus revealing the roots of this
construct in social cognitive and social learning theory as previously discussed.
An illustration of how a collaborative learning process occurs within this
theoretical model is when students (personal) work together on tasks (behavioral).
They receive feedback from each other (environmental) and this feedback may allow
them to see progress in learning thereby influencing their self efficacy (personal).
This may then lead to further learning (motivation). This example describes the
previously reviewed social cognitive concept of triadic reciprocality in the context of
collaborative learning.

36
Collaboration as a means of engendering student engagement is a strategy
based in social cognitive theories. Bandura described four basic principles of social
cognitive theory:
1. People learn by observing the behaviors of others and the outcome of
those observed behaviors;
2. Learning can occur without an immediate change in behavior;
3. The consequences of a behavior play a role in learning; and
4. Cognition plays a role in learning through awareness, memory and
expectations of reinforcements, punishments and of meeting objectives.
Framing collaboration according to these principals may include the
following examples:
1. Students may modify their behavior and beliefs by interacting and
observing their classmates (People learn by observing);
2. Students' thought processes and future reflections and revelations may
occur internally and may be ongoing and additive (Learning can occur
without an immediate change);
3. Student collaboration may lead to positive consequences like improved
performance which may then motivate future collaboration and
performance improvements (consequences of a behavior play a role); and
4. Student awareness of the positive results of collaborating with their peers
may serve as a self reinforcer that, along with other cognitive processes

37
like attention and retention, serve as learning components (Cognition
plays a role) (Ormrod, 2004).
In addition to Bandura’s (1989) model, both Piaget and Vygotsky supported
the importance of peer interactions in learning and cognitive development. Piaget
talked about these constructs as a means of creating disequilibrium (Piaget, 1970).
Vygotsky viewed them in terms of facilitating the internalization of interpretations
(Ormrod, 2004). Internalizations refer to social peer activities that evolve into
internal mental learned knowledge.
Piaget
Jean-Claude Piaget a psychologist and researcher whose theories of cognitive
development are integral to Social Cognitive theory proposed a global theory of
development that incorporates language, reasoning and moral and spatial thinking
(Ormrod, 2004). Piaget hypothesized that children learn through active exploration
of their environments. They construct knowledge through experiences that re-shape
their perceptions of the world and hence their learning develops. Piaget termed these
internal perceptions of the world as schemata. Since people are naturally motivated
to understand the world they are considered active participants. When information
they experience fits their schemata they are in a temporary state of equilibrium.
Disequilibrium is a state of mental discomfort occurring when the individual is
exposed to new and unexplainable information that must be re-organized into new
schema (accommodation) or integrated into existing schema (assimilation). This then
leads to a state of equilibrium and learning (Ormrod, 2004). New information then

38
results in a repeat of the cyclical process where disequilibrium leads to equilibrium
and learning. It is through this process called equilibration or cognitive development
that children develop more complex and integrated schemata over time.
Disequilibrium may be most influential for gifted adolescent students who are
reported to be most influenced and interested in collaborative learning that involves
conflicting ideas from diverse sources (Patrick, 2005).
Piaget viewed learning as a relatively individual process. While new
information may be presented by others, developing children do most of the
cognitive work alone (Ormrod, 2004). In this Piagetian view, learning happens in
the mind and individuals construct knowledge individually. Another type of
constructivism put forth by Vygotsky involves more social influences. Vygotsky
theorized higher mental functions as originating on an interpersonal plane between
two people before existing on an intra-psychic plane within an individual (Archer,
1995).
Vygotsky’s sociocultural theory
In contrast to Piaget, Vygotsky (1962) postulated a more influential role that
others, usually adults, have in fostering children’s learning in a systemically
purposeful, helpful manner through providing challenging activities. In this
perspective, Vygotsky stressed the importance of social and cultural factors in
learning (Ormrod, 2004). His theory may be characterized by five primary
assumptions:

39
1. Complex mental processes begin as social activities. Through interactions
with others, children internalize information and processes.
2. Thought and language become intertwined and children begin to express
their thoughts verbally. They think in terms of words.
3. Through formal and informal methods adults impart cultural lessons on
how to respond to the world. Culturally appropriate behaviors including
language are developed.
4. Children’s ability to complete more complex tasks evolves with the help
of more experienced others.
5. Maximum cognitive growth is realized through challenging tasks within a
child’s Zone of Proximal Development (ZPD).
Vygotsky’s model of learning explores children’s developmental learning
process and has implications for the field of education. This model of learning
highlights the idea that interacting with others, particularly on tasks that challenge
the learner, formulates the basis for and facilitates the learning process. As
previously reviewed, Johnson and Johnson (2000) conducted a meta-analysis which
determined that cooperative learning methods overall tend to be related to higher
achievement. These findings provide support for this model of learning as
cooperative learning methods are based on the idea that learning will be facilitated
through interactions with other students to achieve learning tasks. Vygotsky
acknowledged that much learning occurs outside schools and informally within
schools through explanation, demonstrations and verbal prompts in interactions with

40
peers and teachers. This process, termed assisted discovery, is also evident in small
groups of students where more advanced students assume a teacher role. This
process is akin to peer assisted or collaborative learning. Vygotsky stressed that the
personal activity of the student must be placed at the base of the educative process
(Vygotsky, 1962).
Vygotsky additionally points out the role which models (more experienced
learners) have in assisting a child to learn and further develop cognitively and this
focus on more experienced learners has implications both for peer interactions and
the teacher’s role in learning. Peers who are at different stages of learning or
development may facilitate each other’s learning through collaboration.
Additionally, teachers can provide both direct assistance and modeling in the
learning process as well as can structure their classrooms in a way that helps
challenge learners and provides a framework for helpful collaboration.
Motivation
Another construct which has implications for student engagement with others
and achievement is motivation. A review of recent literature pertaining to
understanding motivation and factors that help to encourage and maintain it is
important.
Motivational Variables Expectancy-Value theory
A cognitive perspective on motivation is reflected in expectancy-value
theories of motivation. Expectancies refer to people’s beliefs, judgments, and
perceptions of their capability to perform a task. Values refer to beliefs about why a

41
task is selected to be completed. Atkinson (1964) proposed a theory of motivation
around a framework of needs, expectancies, and values. Atkinson’s model stressed
that people’s behavior is a function of motives (i.e., to approach success and to avoid
failure), incentive value (pride in accomplishment) and probability for success.
Four types of value include: task value (subjective beliefs about reasons for doing a
task), interest or intrinsic value (subjective interest and enjoyment in a task), utility
(usefulness in the task and assessment of the cost of completing a given task (Schunk
& Pintrich, 2008). In expectancy-value theory of motivation, both expectancies and
values are important for predicting students’ future task-choice behavior, persistence,
engagement levels and actual achievement. When students value a task and expect to
do well, motivation, engagement and achievement is a likely result.
Underperformance is reduced when students value engagement and collaboration
and expect to improve when they interact and collaborate.
A contemporary expectancy-value theory of motivation comes from the work
of Eccles and Wigfield (2000) who postulate that student motivation for success is
based on student expectancy for academic success and the value students place on
academic tasks. This viewpoint reflects a social-cognitive perspective involving the
reciprocal dynamic of student, environment and behavior. The theory may be
described as a linear model flowing from the social world (environment and culture)
to cognitive processes (perceptions of social world), motivational beliefs (task values
and expectancies) resulting in achievement behaviors (engagement, learning
strategies). In relation to the present investigation, the model may be described as

42
reflecting a linear representation proceeding from classroom factors like teacher
support to student perceptions of task values resulting in engagement, collaboration
and achievement.
Expectancy
An analysis of research on the expectancy value theory of motivation was
conducted by Wigfield and Eccles (2000) to test two issues. First, these authors
wished to assess changes in children and adolescents’ beliefs about their own
abilities and expectations for success. Secondly, they wished to assess the
relationships between adolescents’ ability expectancy beliefs and task values to their
performance and choice of activity. These authors utilized a confirmatory factor
analysis (CFA) to explore these two issues. Results indicated that ability beliefs and
expectations for success are not empirically distinguishable. Adolescents appear to
have specific beliefs about what they are good at and these ability related beliefs
decline across elementary school years though high school. However, adolescents’
valuing of some activities becomes slightly more positive in later adolescence.
Eklof (2006) investigated students’ levels of test-taking motivation as related
to low-stakes assessments. Based on expectancy value theory, the author’s intent was
to develop an instrument that measured test-taking motivation. The expectancy
component was operationally defined as general ability and self-efficacy beliefs;
concepts that are highly related for adolescents. The value component was
conceptualized as the amount of importance the student attaches to the task, also
known as task value. As the factors involved in expectancy value theory occur in a

43
social context, Eklof assumed student test motivation might be associated with the
manner in which tests are presented to students and their attitudes toward the test,
both of which may be construed as classroom factors. These factors were regarded
as indicators of student beliefs, expectations, perceptions and attitudes. 350 Swedish
8
th
graders taking a standardized math and science test (TMSS) were given the Test
Taking Motivation Questionnaire (TTMQ) designed by Eklof (2006). Items on the
TTMQ assessed perceptions toward the TMSS. Factor analysis revealed data on
validity and reliability of several test items (including value perceptions) indicating
the item’s usefulness as a test of student motivation. Test items correlated with
Wigfield and Eccles (2000) research on achievement motivation for children and
adolescents. Results also indicated that perceived task value is closely connected to
motivation to perform well.
Value
Achievement values are defined as the incentives or purposes students have
for succeeding on any given task (Wigfield, 1994) including collaboration.
According to expectancy—value theory, the amount of value a person places on a
task along with the perceived probability of success helps determine the level of
effort made to complete the task. Adolescent student achievement values impact
their motivation as the value placed on the goals influence how students approach
and engage in academic tasks. When students value a task, they are more likely to
engage, persist, and expend energy on that task (Wigfield, 1994).

44
A gifted student research center at the University of Connecticut (Renzulli,
2002) released a report that described value constructs applicable to the value gifted
students place on activities: intrinsic value, utility value and attainment value.
Intrinsic value is value that results from the enjoyment an activity produces
for the gifted student. Students typically are intrinsically motivated to pursue tasks
that are novel, interesting, enjoyable, exciting and optimally challenging.
Challenging tasks are noted as especially important to gifted student collaboration in
learning (Patrick, 2005). Deci and Ryan (1985) put forth that educators could
improve intrinsic value by creating classroom environments that provide students
opportunities to engage in interesting, personally relevant challenging activities. This
finding is encouraging to the present study as collaboration may be considered a
novel learning strategy involving the challenge of exploring conflicting ideas
between students.
Utility value refers to how a task relates to future goals. Students may value
the future reward or outcome a task has for helping them achieve a goal. The task
with utility value must be perceived as instrumental to future or long-term goals. In
regard to the present research, these findings suggest that Honors instructors may
construct classes that support collaboration as necessary in meeting learning
objectives for the course, thus creating utility value. Additionally, Peterson (2001)
demonstrated that gifted underachievers improved their performance when value was
placed on career and future academic goals so utility value that links collaboration in

45
Honors classes to graduation and career success may be an important construct for
addressing high ability student motivational needs.
Attainment value refers to the importance a student attaches to a task as it
relates to their perception of their own identity or their competence in a given
domain. (Wigfield, 1994) For instance, student athletes may set goals related to their
sport. Student motivation is related to attaining goals associated with the student’s
self-perceptions. For honors students, self-perceptions likely involve high
achievement standards reflected by superior grades and corresponding GPA’s.
Linking self-perceptions to learning goals may be effective considering the role of
identity formation in adolescent student development (Santrock, 2004). Additionally,
exposing students to models who value academic achievement has been noted as an
effective method to increase attainment value (Rimm 1995). Therefore, faculty that
model collaboration may serve to help motivate gifted adolescents to employ
collaborative learning techniques.
Classroom Factors
Teacher Support for Interaction
In the previous discussion, engagement, collaboration and motivation have
been identified as factors that have been shown to be positive in the learning process
and related to student academic success. An important extension of these factors is
the consideration of how they may be encouraged by faculty within the classroom
setting.

46
Snidow (1995) produced a qualitative evaluative study looking at the
effectiveness of an interdisciplinary cooperative learning approach for adolescent
Honors students. The study was conducted to answer questions involving effective
student learning and teachers’ construction of effective learning environments. The
author’s purpose was to determine if classroom structure is effective in student
success and to identify elements of the classroom related to success. The study noted
a focus on four elements within the classroom: cohesiveness, cooperation, conducive
environment and concept involvement. Effective instruction was hypothesized to be
defined as a product of the degree to which students perceive that cohesiveness and
cooperation exist in the classroom. Perceptions of support were also associated with
effective instruction and achievement. Twenty-three high school age students and
teachers were surveyed. Participants came from both a traditional class and an
interdisciplinary Honors class employing cooperative learning strategies. Measures
utilized included student journal entries that were coded and analyzed for thematic
commonalities, teacher grade records, and direct observations from a school special
services staff member. Results from data collected led the researchers to surmise that
many factors contribute to academic success and student growth, including a class
environment designed to provide cohesiveness and cooperation. Results were
framed by two components: The first was student success as defined and observed
by the teacher; the second was teacher success defined by the student. Both were
noted as essential to achievement.

47
In summary, data revealed that cooperative learning was a necessary tool in
the enhancement of the academic environment for both student and faculty. In
addition, Snidow (1995) noted that students who pooled resources, learned from and
taught each other, and who accepted a more active role in their own and their peer’s
academic success were also capable of positive personal growth. In general,
cooperation supported by class design was indicated as a component in effective
teaching, learning and positive personal growth for students.
Engagement and Motivation
Research by Lin, Lin and Laffey, (2008) centered on social compatibility
including collaboration in a web based learning environment. This study examined
how social and motivational attributes influence learning experiences using the
establishment of four constructs. These constructs included: social ability, goal
orientation, task value, and self-efficacy. 250 graduate students of a Midwest state
university in education were surveyed. A 20 item social ability instrument (CSSW)
was utilized as the survey instrument. The CSSW is a modified version of a measure
of social presence designed by Picciano (2003). This measure was used to assess the
social presence of students taking an on-line course. Unfortunately, the basis of the
acronym CSSW was not provided. Picciano (2003) notes the survey questions were
based on the Inventory of Presence Questionnaire developed by the Presence
Research Working Group located at (http://www.presence-research.org) (Picciano,
2002). The survey was modified and expanded to examine how instructors and peers
might differentially influence learners’ social ability. In addition to the CSSW,

48
students’ scores on goal orientation, task value, and self-efficacy were measured
using the Motivated Strategies for Learning Questionnaire (MSLQ) (Pintrich, Smith,
Garcia, & McKeachie, 1993). The authors sought to understand how social and
motivational factors contribute to collaboration and to learning satisfaction in an on-
line learning environment.
To create the theoretical framework for their study that included learning
satisfaction and social interaction, the researchers examined several key constructs.
Social interaction was defined as the Vygotskian notion that learning occurs as a
result of social practices, a concept similar to collaboration. Also, the framework
included social ability, self-efficacy, task value and intrinsic goal orientation, all
motivational constructs. A factor analysis revealed a structural model depicting
dynamic relationships that existed among the four exploratory constructs. Results
indicated that students’ perceived social ability influenced their satisfaction and they
had a more positive perception of the learning experience. Also, students’ perceived
task value and self-efficacy had a direct impact on learning satisfaction so that
students who placed higher value on a task and had a high sense of self-efficacy were
more satisfied with their learning. In addition, social ability was positively correlated
with intrinsic goal orientation, task value and self- efficacy. Students with high social
efficacy were more positive and had more intrinsic value and motivation for learning
and collaboration.
The study’s data analysis supported the concept that a sense of being
connected to the learning community is correlated to effective learning.

49
Interestingly, student connectedness is more closely tied to interacting with
classmates than with instructors according to the authors. Peer support was
demonstrated to be very important. A psychological sense of community,
characterized as an acknowledged sense of interdependence among students, was
noted as a partial explanation for the study’s findings. The implication is that peer-
to-peer collaboration is more influential than other class factors involving student to
teacher interactions and satisfaction.
The study reviewed above examined how well motivational variables and
social ability together explained learning satisfaction in an on-line atmosphere (Lin,
Lin and Laffey, 2002). Results revealed that learning satisfaction, social ability and
peer interactions, and motivational constructs including intrinsic goal orientation,
task value and self-efficacy were all positively correlated and led to increased
student satisfaction and performance. These findings further highlight the
importance of examining the relationships of these factors in regard to the high
ability student population.
Underperformance
The research reviewed within this overview of current research has served to
begin to illuminate ways in which the constructs of collaboration, motivation and
class factors come together to promote student success. Conversely, the issue of
underperformance presents a difficult challenge to student academic success and is
one that warrants further exploration.

50
Researchers have investigated several contributors to current
underperformance problems. These problems may be rooted in the absence of strong
achievement orientated models (Bandura, 1986), perceptions of an individualistic
culture (low expectations for success, poor self-efficacy, lack of reinforcements for
achievement (Patrick, Bangel, Jeon & Townsend, 2005). Additionally, low task
value (Eccles, Vida & Barber, 2004), under-developed observation skills (Ormrod,
2004 p 125), minimal peer and environmental interactions and problems associated
with the developmental period of adolescence (Eccles, Midgley, Wigfield, Miller &
Buchanan, 1993) may be related to underperformance.
The following causal themes were identified in relation to possible causes of
underperformance within the population of honors students under review. First, peer
tutoring is neither sought nor delivered. Secondly, there is a lack on interdependence
that creates competitive performance and not collaborative mastery goal structures
thus limiting achievement. Thirdly, existence of uncooperative individualistic school
environments, and lastly, socially constructed class knowledge is lost due to an
uncooperative class or school environment.
In addition, the four principals of social thinking in regard to learning may be
maladaptive including a) no data alternatives are provided which leads to an existent
linear, homogeneous thought process in students that is limiting effective learning, b)
a weakened decision-making framework exists where minimal information is
presented and c) a lack of diversity in thought is caused in individualistic
environments, thus limiting learning effectiveness (Aronson, 2002).

51
In addition, school cultures may not be open and cooperative thus negatively
affecting help-seeking behaviors and mentor opportunities that may lead to
underperformance. In general, underperformance in high ability students may be
related to various social cognitive constructs that are presently ineffective for
learning. These include a lack of reinforcements, underdeveloped observational
skills, poor or non-existent learning models and adolescent non-conformity to
collaborative efforts or conformity to individualism. This non-conformity in regard
to learning may possibly be fueled by adolescents’ rebellious attitudes that may lead
to the minimized impact of positive role models (Santrock, 2008). Additionally, low
or poor motivation as characterized by students’ low expectancies for success and
poor self-efficacy may also be related to underperformance.
Underperformance problems may be rooted in competitive, unsupportive
individualistic social environments where help seeking is discouraged and therefore
learning problems arise and where students have access to limited information and a
limited diversity of thoughts and perspectives (Ryan, 2001). Eilers (2007) discussed
ways in which educators can challenge this unhelpful individualistic environment.
He utilized a social systems context approach to discuss ways in which a change in
school culture toward collaboration can take place. A social context change toward a
culture of openness for improvement may involve improvement in communication
between and among school staff and students, expectations for culture change by
school leadership and, professional development efforts stressing support for student
peer collaboration. All three factors would assist in creating a culture where it is

52
acceptable to be mentored, coached and supported. These changes would be helpful
in creating a social context of cooperation and collaboration (Eilers, 2007). The
social context is established as a valuable factor in regard to student collaborative
learning strategy implementation and to combat underperformance.
Gaps in Current Research/Knowledge
Review of the literature reveals gaps in current knowledge involving two core
areas: methodology and student populations under study. Currently, in regard to
methodology, most studies were qualitative in nature and some had ill-defined
methodologies that did not fully address relationships among variables. Research on
the relationships between class environments, motivational factors and engagement
has been noted as a relatively new area of research (Ryan and Patrick, 2005) and
therefore it seemed that efforts, instruments, and study designs which lend
themselves to most fully measuring these constructs and their relationships were
somewhat lacking.
In regard to student populations, many of the studies on collaboration and
cooperative learning at the classroom level involve elementary pre-secondary school
age students with minimal research available on other age and educational groups
including secondary and post secondary school environments. Additionally, studies
on collaboration tended to focus on on-line and web based learning, intra-district
personnel development, organizational, business related environments and disabled
students. Few studies were found on the effects of student learning based
collaboration on achievement, aside from those on peer tutoring and even fewer on

53
the relationships between the classroom environment and collaboration (Ryan 2001).
No research was found on college honors students and either collaboration or
cooperation, and no empirical work on collaboration and gifted students.
Additionally, no research was discovered regarding early college entrants and
collaboration. The lack of empirical data on early college entrants specifically is
likely related to the scarcity of such programs and student participants across the
nation. However, this certainly should not minimize the importance of discovering
beneficial knowledge of those that do exist. Currently, no data exists on
relationships between early entrants, classroom factors, engagement, motivation and
collaboration. There is a need for research regarding classroom environments,
motivation and engagement to address underperformance problems in this
population, to close research gaps involving gifted early entrants and other high
ability students, and to extend the results from research that has established
relationships between the perceptions of classroom factors and achievement (Patrick
2005, 2007; Ryan and Patrick, 2005; Patrick, 2007).
A Comprehensive Research Model
Study Premise
A study conducted to assess students’ perceptions of the classroom social
factors related to engagement and motivation by Patrick et al (2007) provides the
framework for the present investigation. Patrick (2007) sought to investigate the
presumption that task-related interaction (engagement) was related to perceptions of
the classroom social environment. Additionally, these researchers sought to discover

54
whether these relationships were mediated by personal motivational beliefs. A link
between engagement and achievement was proposed. In her study, Patrick defined
collaboration as being characterized by self-regulation and task-related interactions.
A social cognitive perspective of learning supports the idea that students’ social
relationships and perceptions (i.e. peer interactions) are related to and predictive of
school outcomes. The authors proposed that students’ perceptions of their class
environment (i.e. levels of affiliation, cohesion, fairness, teacher and peer respect
and support) are related to engagement and achievement and are mediated by
adaptive motivational beliefs. As this research forms the framework for the current
investigation, it is logical to examine it further.
Study Methods
Patrick (2007) surveyed 602 5
th
graders from a Midwestern elementary
school. Three main domains were addressed by the study: support, engagement and
motivation. Student perceptions of the classroom social environment were assessed
through the use of six scales measuring emotional and academic support in the three
different domains. Patrick (2007) reported that she adapted several measures from
previous survey instruments which have been shown to be reliable and valid as well
as designing some of her own subscales in creating the measures which she used to
assess the constructs under investigation for her research.
In regard to the domain of support within the classroom, there were two
measures of perceived teacher support for the student (emotional and academic) and
two measures of peer support for the student (emotional support and academic

55
support). These measures were adapted by Patrick from the Classroom Life Measure
(Johnson et al., 1983).
Student engagement in academics was assessed using two scales, one which
measured self-regulation and one which measured task-related interaction. Self-
regulation was defined in this study as the extent to which students regulate their
own cognition. Task-related interaction was the extent to which students worked
collaboratively through sharing information and answering questions. These scales
were created by Patrick in order to measure these constructs.
Student academic motivation was measured using two scales from the
Patterns of Adaptive Learning Survey (PALS) (Midgley et al., 1996). A survey of
students’ mastery goal orientation (referring to students’ desire to develop their
understanding and mastery of material) was used along with a measure of students’
academic self-efficacy. Academic self-efficacy referred to students’ judgments
about their capability to complete work successfully.
Student course grade data was also collected as a measure of academic
performance and achievement. The importance of the PALS instrument in regard to
student motivation is worthy of additional discussion and follows.
PALS Measurement
According to Midgley, Kaplan, Middleton, Maehy (1998), beginning in 1990
a research team from the University of Michigan began work on developing and
validating scales used to assess student goal and achievement orientations. These
scales are used in the study of student motivation using goal-achievement theory

56
within a framework of Social Cognitive theory. In essence, rather than considering
students’ overall motivation, the presence or lack thereof, Achievement-Goal
orientation researchers instead focus on how students think about themselves, their
tasks and their performance. Goals are viewed as a mechanism through which
students interpret and react to events in their learning, thus it is assumed that
environments affect their cognition, behavior and ultimately, performance.
These theorists have identified two general types of goal orientations: The
first is the goal to develop ability, also known as task, learning and mastery goal
orientation that has been related to adaptive patterns of study and is often labeled as
an approach motivational orientation; students try to increase their understanding
and skill and judge success in self-referential terms. The second is the goal to
demonstrate ability and/or avoid the demonstration of a lack of ability also known as
ability, ego and performance goal orientation and has been related to both adaptive
and maladaptive patterns of study. Ability orientations may be approach-orientated
whereby students try to gain favorable judgments of their abilities and avoidance-
orientated whereby they strive to avoid unfavorable perceptions of their competence;
success is judged in terms of comparison to others. These relationships between the
two goal orientations have been established across a wide range of studies though
there is significant overlap among these differing concepts. Continued goal
orientation research by Elliot & Harackiewicz (1996) and Elliot & Church (1997)
revealed that while both task and ability orientations overlapped, that only ability-
goals rooted in an avoidance of failure undermined intrinsic motivation and task

57
goals were related to achievement motivation while ability goals were related to fear
of failure. The researchers concluded that students concerned with their ability
selected approach or avoidance depending on whether they perceive the situation as
threatening or challenging. Perceived ability was distinguished as an influential
component whereas perceived high ability was a precursor to task and ability-
approach orientations, low perceived ability was antecedent to ability-avoidance
goals.
Goal orientation scales were administered to a variety of elementary and
secondary public school students throughout the Midwest. The samples were
primarily European; of five (5) waves of testing, the percentages of European-
American students topped at 80% and was no lower than 43%. Additional work in
goal-orientation theory included the inclusion of items from these scales in the
Patterns of Adaptive Learning Surveys (PALS) that were administered to students in
classrooms. Scales were found to be reliable and valid across all constructs with
Cronbach’s Alphas for task-orientation at no lower than .70 and often above .80.
Though lower overall, the alphas for the ability orientation scales were no lower than
.60. The PALS instrument was developed to use Goal Motivation theory to examine
the relations between learning environments and motivation. The measures of both
teacher and student perceptions were comprised of 5 point Likert-type scales based
on previous research on the association between mastery and performance goals as
related to adaptive and maladaptive patterns of learning (Midgley et al 2001).

58
Study Results
Data analysis revealed that student academic support provided by peer
interactions contributed to student engagement. Also, student engagement was found
to be mediated by the motivational constructs of mastery goals and academic self-
efficacy. Adaptive classroom social environments were proposed to enhance
students’ focus on mastery goals (motivation) thereby facilitating engagement. This
would then lead to achievement. More simply stated, students’ classroom interaction
with peers (collaboration), and their perception of teachers’ support for such
interaction was related to motivation and engagement thus leading to increased
achievement. To more fully understand the relationships between variables see the
conceptual model of Patrick’s study, Figure 1.
This research framework created by Patrick (2007) that supports a
relationship between perceptions of class factors and engagement, will be simulated
and extended for a population of college honors students. The scope of the present
study will be limited to the use of only one scale per research construct.

59

Figure 1: Patrick (2007) Conceptual Model

60
The Present Study
Similar to the model presented by Patrick (2007), the present study will
employ a research structure exploring the relationships between the classroom
environment, motivation, and engagement. The current study predicts a positive
relationship between student perceptions of classroom support and engagement.
Student perceptions of classroom support will be measured by assessing level of
teacher support for task-related interaction in learning. Engagement will be
measured by assessing perceived level of task-related interaction (collaboration). In
addition, as Patrick reported, it is presumed that motivational beliefs such as holding
a mastery goal-orientation will mediate the relationship between student perceptions
of class factors (teacher support) and engagement.
As the Patrick model guided the present study and the measurement
instruments she utilized have been validated and vetted statistically, the current
researcher will also utilize select scales from Patrick’s survey instrument and employ
a similar design in measuring the perceptions of the university Honors students.
Based on the current author’s interest in collaboration as an effective form of
student engagement and as a possible solution to underperformance problems,
similar or complimentary constructs from Patrick will be replicated.
The current researcher puts forth a model (Figure 2) wherein classroom
factors interact with the students’ internal features of motivation and engagement,
that then predicts level of student achievement. Following the Patrick model, the

61
present investigation will address the following key variables: class environment,
motivation, and engagement.
The research questions to be addressed through the study include the
following:
1. What are the relationships between student perceptions of the class
environment, motivation and engagement?
2. Will results from previous studies of social environment and engagement
be replicated in a university honors context for early entrant students?
3. Is the degree of student collaboration in classrooms related to student
motivation and learning characteristics?
4. Is there a relationship between collaboration and achievement?
The conceptual model under investigation in the current study is put forth in
Figure 2.

Figure 2: Honors Student Study Conceptual Map

62
It is presumed that similar findings to those realized by Patrick for a
homogenous group of elementary students will be evidenced in this diverse
population of university Honors students. Considering the malleable nature of
classroom factors, discovering the relationships between these variables and student
engagement may allow for positive effects on student achievement and performance,
thus building a basis by which to begin addressing underperformance problems.
Such positive effects may be realized in practice by providing a basis for faculty to
initiate support for student engagement in Honors courses based on valid research
findings.
The following chapter will discusses the methodology of the current study
including procedures, instrumentation, hypotheses, and assumptions and limitations.

63
CHAPTER THREE
METHODOLOGY
Introduction
This research will involve the assessment of student perceptions of classroo
factors, motivation and engagement. The design is descriptive and Correlational. In
order to determine the relationships between classroom environment, motivation and
engagement, the researcher will survey students using measures that will specifically
assess their perceptions of teacher support, goal orientation and task-related peer
interaction.
Sample Population
Participants sampled will be those early entrant high ability students enrolled
in an Honors program located at a large urban Southern California state university.
The enrollment of the University is approximately 22,000 students and the Honors
program enrolls approximately 50 new students yearly with approximately 25 as
early entrants, with an overall enrollment of 291 students. On average, 80-90% of
students in this Honors program taking introductory courses are high ability students
who entered college early through an early entrance to college program. It is likely
that a large proportion (est. 95%) of student participants will be completing their first
year in college.
Demographics
Students enrolled in the University Honors program are diverse in regard to
gender, age, ethnicity, socioeconomic status, and major. Currently, there are a total

64
of 291 undergrads participating in the Honors Program. In terms of gender, 40% are
males and 60% are females. It is assumed that the ethnic distribution of university
Honors program students, excluding the early entrance Honors participants, mirrors
the university as noted in Table 2.

Table 2: Honors’ Program Estimated Demographics
Ethnicity Percentage
American-Native 9.5
African-American 9.6
Asian-American 23.1
Latino
White/ Caucasian 15.3
Other/non-caucasian 14.1

Overview of School and Programs
University
The university from which the study participants are drawn offers excellent
and innovative educational opportunities to an urban student population that reflects
the diversity of the Los Angeles basin. The university enrolls 15, 727 undergraduates
of which 17.9 % are first time freshmen. There are also 5,324 graduate students at its
campus. Bordered by East Los Angeles and the city of Alhambra, it is a commuter
campus that serves a largely Hispanic non-Caucasian student population at
approximately 37.0%. The university has suffered from a self-proclaimed image

65
problem that affects recruitment of top tier students thus making its innovative early
college entrance program and Honors Program especially significant to success
(Miron, 2008). It is important to note that the university is identified, internally and
externally, formally and informally, as an Hispanic Serving Institution. This identity
frames much of the university culture, atmosphere, support systems, planning,
infrastructure and mission and consequently, its programs and students.
Early Entrance to College Program
The early entrance to college program is a unique educational program that is
specifically designed to permit young, highly gifted students to enroll in college as
full time students. The early entrance to college program was established at the
university under study in 1982. The early entrance to college program allows
qualified students as young as 11 years of age the opportunity to excel at the
university level. The average entering age is currently 13.5 years and all early
entrance students must be under the age of 16 by June 1
st
of the year in which they
apply. Students are admitted each fall term after completing a mutual assessment/
application during a summer term of classes. Yearly cohorts of new admits do not
exceed 30 new students per year. The early entrance to college program maintains a
population of approximately 125 full-time highly gifted teen-age students. All
freshmen early entrance students complete a standard curriculum of general
education (GE) classes and all first year classes are offered through the university’s
Honors Program (See Appendices). Ninety-five percent of all early entrance to
college freshmen takes Honors selections in their first year. The early entrance to

66
college population demographics are depicted in Table 3. The Program began as a
research project intended to assist area gifted students achieve an appropriate
academic challenge and recognition, apart from their traditional schools. Although
the program has grown and developed since its inception, there has been an historic
lack of support from the university. The program survived and thrived institutionally
due primarily to the attention of one administrator, the Program Director, several
prominent faculty members and one Dean. The minimal support, in resources,
recognition and operationally, is assumed to be due to two primary factors: The first
factor involves the university identity and culture that presupposed serving a
program that consisted primarily of middle to upper class SES caucasian and Asian
high-ability teenage students from the Valleys, Orange County and West Los
Angeles as contrary to its primary mission to serve lower income, average to low-
ability SES Latino students from the surrounding area of East Los Angeles. The
Program may have been viewed as elitist and early entrants as a threat to the
traditional student Latino population who are largely first generation college
students from first generation immigrant families. The second factor may be related
to the general cultural perception of acceleration as a negative educational alternative
and of teenagers on a college campus as detrimental to normative development. This
lack of support was perceived by the early entrant student population and staff as
institutional disinterest and, at times, animus thus affecting the culture of the
Program and self-perception of those involved with it as being second-class,
marginalized members of the university community. This negative culture may have

67
far reaching effects on students and staff that may have minimized the perceived
importance of research related to the Program.

Table 3: EEP Demographics
Ethnicity % of EEP Students
American-Native 0
Asian 45
Hispanic/Latino 10
African-American 5
Caucasian/white 40

Honors Program
The Honors program under current study provides highly qualified students
with diverse, enriched intellectual activities through a separate curriculum that
includes Honors classes, seminars, and research. Honors courses promote
intellectual curiosity, critical reading, and logical thought and writing. These courses
have a lower student enrollment than other general education courses and are taught
by the university's finest professors, many of whom are nationally recognized
authorities in their field of study. Honors students not only have the opportunity to
accelerate their academic program, they also encounter challenging and rewarding
educational experiences. The Honors Program notes the following five main
objectives:

68
1. Provide high potential students an opportunity to participate in
intellectually demanding and academically challenging general education
courses.
2. Offer opportunities for greater interaction with peers and involvement in
interdisciplinary learning.
3. Identify university resources through which high potential students can
receive academic, personal, and career counseling that will help them to
better define and reach their goals.
4. Create opportunities for high potential students and faculty members to
establish closer educational and personal relationships.
5. Prepare students for participation in upper division Departmental Honors
Programs.
Currently, the majority (98%) of enrolled students in Honors Program Fall
through spring class offerings are early entrance to college students (Olsen, 2008).
Instrumentation
The measurement scales utilized in the current study were taken from Patrick
et al. (2007) designed to assess student perceptions of the classroom environment as
related to their engagement as mediated by motivational factors. The measures used
in the current study were minimally adapted from Patrick (2007) to measure the three
general student perceptual variables under investigation. Adaptations are limited to
three specific areas where the original term “kids” was changed to “students”, the
term “math” or the phrase “math class” changed to honors or “Honors class” and the

69
term “collaboration” inserted where appropriate, fitting and where grammatically
correct to questions regarding task-related interactions (See Table 4).

Table 4: Task-Related Interaction Scale
Patrick (2007) measurement of task-related interaction
Original Instrument / Task-Related Interaction
Considering your math class please select the best response 1-5 that reflects your
agreement with the following statements

1. During math class I explain how I work out math problems to other kids.
2. I help other kids with math when they don’t know what to do.
3. I share my ideas and materials with other kids in math.
4. In math class I help other kids learn.
5. I answer questions about math in class. (a)
Bold terms are deleted or revised in the current study Maddox (2008)
Maddox (2008) revised measurement of task –related interaction as collaboration
Collaboration/ Task-Related Interaction
Considering your Honors classes please select the best response1-5 that reflects your
agreement with the following statements, where 1= not at all true and 5 - very true

1. During classes I explain how I work out problems and difficult concepts
to other students.
1 2 3 4 5
2. I help other students with class work when they don’t know what to do.
1 2 3 4 5
3. I collaborate by sharing my ideas and materials with other students in
my Honors classes.
1 2 3 4 5
4. In classes I help other students learn through collaboration.
1 2 3 4 5
5. I answer questions about coursework in Honors classes.
1 2 3 4 5

Bold terms are additions and or revised for the current study

70
Classroom social environment was measured using a measure of teacher
support for interaction. Motivation was measured using a measure of mastery goal
orientation. Engagement was measured using a measure of task-related interaction.
The response format for each item is based on a five point Likert scale ranging from
1 (not at all) through 5 (very true). All items were specific to university Honors
classes and are shown in the Appendices. Responses reflected how strongly the
students agreed with the statements whereby the higher the score, the more they
tended to agree. Reliability and validity has been established for each scale used in
the present study and is presented later in this study.
Teacher Support for Interaction Subscale
The three-item promoting task-related interaction subscale measured the
extent to which the teacher was perceived as encouraging interaction among peers
involving academic tasks. This subscale was a shorter version of a scale developed
by Ryan & Patrick (2001). The teacher support scales used by Patrick were
minimally adapted from the Classroom Life Measure instruments (Johnson et. al.,
1983). Johnson & Johnson’s (1983) research involved surveying 839 9th graders’
perceptions of the classroom environment to obtain correlational analysis of
relationships between scales measuring social interdependence and attitudes toward
teachers and peers. Results indicated that cooperative learning experiences were
positively related to perceptions of support, help and friendships from teachers and
peers. This scale was modified for the current study to include the term
“collaboration” directly. An example of a question from this subscale is: “My

71
teacher encourages us to collaborate and share ideas with one another in class.”
Reliability and validity for the promoting task-related interaction instrument was
established with a Cronbach’s alpha of .70.
Mastery Goal Subscale
The Mastery Goal Subscale was used to measure students’ desire to develop
their ability and understanding of course material and academic achievement. The
six-item mastery goal orientation scale measures students’ level of mastery
orientation and was adapted from the Patterns of Adaptive Learning Survey (PALS)
(Midgley et al., 1996). An example of a question from this subscale is: “An
important reason I do my school work is because I like to learn new things.” This
subscale consisting of 6 items was taken from the Patterns of Learning Survey
(Midgley, 1996). This scale was noted to have been proven reliable and valid
(Midgley et al, 1998) with Cronbach’s alpha of .77. Due to the emphasis by the
Patrick study on the PALS scales used to measure motivation constructs, it seems
prudent to more fully explore these measurement instruments later in this section.
Task Related Interaction subscale
The five-item task related interaction subscale assesses the extent to which
students answered questions, explained content, and shared ideas about the course
subject matter with classmates, and was a short version of a scale developed by Ryan
& Patrick (2001) specifically for the Patrick (2007) study. Ryan & Patrick surveyed
233 8
th
graders’ perceptions of the social environment of their classrooms as related
to their levels of motivation and engagement in the transition from 7
th
to 8
th
grade.

72
Results indicated that prior motivation and engagement were strong indicators of
subsequent motivation and engagement while gender, race and prior achievement
were not related. Furthermore, student’s perceptions of teacher support were
positively related to positive changes in motivation and engagement. This scale was
modified slightly in the present study to more accurately represent the construct
collaboration by adding the term “collaborate and/or collaboration” where
appropriate and semantically accurate. Also, within this measure the term math was
substituted with “honors class” and the term “kids” was replaced with the term
”students”. An example of a revised question from this subscale is: “I share my
ideas and materials with other students in Honors classes.” See Table 4 and
Appendix G for both original sub-scale questions with revisions. The task-related
interaction scale was noted as reliable and valid, demonstrating a Cronbach’s alpha
of .83 (Patrick, 2007).
Demographic Measure
Demographic data was surveyed from each participate and included: age,
gender, year at university, number of honors classes taken or in the process of
completing, units completed and cumulative GPA, ethnicity and major (see
Appendix A). Student permission to link grade and survey data was also sought, and
received.
Data collection and procedures
Faculty of fall quarter Honors classes were contacted through the university
Honors program faculty advisor and asked to assist in the solicitation of student

73
participants through granting a small portion of class time to allow the investigator to
make a brief presentation. Once permission was granted to do so, the researcher
attended a class session of each Honors class offered in the fall term to explain the
study to the students. A live presentation to students of approximately 5 minutes in
length was given (see Appendix C). In addition, a copy of the script was sent
electronically to all early entrants currently enrolled including the following brief
message:” As a current early entrant your help is sought in completing a research
project designed to assist early entrants, the honors program and to help inform the
research literature on both…”
Students were informed that the purpose of the current study is to help
improve early entrant student performance and satisfaction and to strengthen the
Honors program including gathering data that could inform future class design.
Students were informed that only those students currently enrolled as early entrants
were needed for the study. Students were also informed that their participation was
entirely voluntary and would have no effect on them whether or not they
volunteered. Students were informed of their right to refuse participation. This
information was also repeated during mandatory student meetings held twice
quarterly. Students were informed that those who participated were going to be
entered into a raffle for one prize TBA not to exceed $300.00 in value. Students were
then be asked to send an e-mail to the researcher expressing interest. Students
received a response email from the researcher that included three consent forms
(Appendices D, E and F) with instructions to return the completed forms to the

74
researcher’s campus office. When students returned the appropriate completed
forms, they were sent code numbers to access the surveys and further instructions on
participating, including information regarding the web site address where the surveys
were to be completed. Code numbers produced through a random number generator
was used to avoid duplication, to retain confidentiality, and to enter students in the
raffle. A roster of code numbers assigned to student participants were collected to
ensure consent. This roster was kept completely separate from any data collected
and any materials related to student identities. Students were asked to give
permission to use and link GPA to survey data. Other than that, no other identifying
student information was collected, needed or used.
In order to complete the survey, students were directed to a web based survey
site at http://www.qualtrics.com/. A copy of the complete survey materials is
included in Appendix A.
Hypotheses and Data Analysis
Hypothesis 1a.
It is presumed that there will be a positive relationship between teacher
support and task–related interaction. Higher scores on the teacher support of
interaction subscale will be related to higher scores on the task-related interaction
subscale.

75
Hypothesis 1b.
It is presumed that there will be a positive relationship between teacher
support and mastery goal orientation. Higher scores on the teacher support subscale
will be related to higher scores on the mastery goal orientation subscale.
Hypothesis 2.
It is presumed that there will be a positive relationship between mastery goal
orientation and task-related interaction. Higher scores on the mastery goal
orientation subscale will be related to higher scores on the task-related interaction
subscale.
Hypothesis 3.
It is presumed that motivation will serve as a mediator between class
environment and engagement. Scores on the mastery goal orientation subscale will
mediate the relationship between scores on the teacher support for interaction
subscale and the task-related interaction subscale. The mediating role of motivation
variable is indicated by a significant drop in the direct relations between social
environment and engagement variables compared to relations between these two
variables without mediation. (Patrick, 2007)
Hypothesis 4.
It is presumed there will be a positive relationship between task-related
interaction and achievement. Higher scores on the task-related interaction subscale
will be related to higher Grade Point Averages.

76
For a conceptual map indicating the presumed relationships between
variables noted above, see Figure 2.
Data Analysis
Descriptive statistics as means, sd’s, n’s were completed for demographic
data. Means and standard deviations were computed for each of the three scales.
Statistical analysis utilized the SPSS or similar statistics program to compute the
Pearson’s correlation co-efficient to reveal possible relationships between variables.
Additionally, data was analyzed using SPSS or similar statistics program in order to
assess relations and mediating effects between variables. Various hypothesized
models (i.e. teacher support will lead to increased engagement mediated by
motivation) were considered and assessed for relations between variables. Multiple
regression procedures were employed to control for factors including student type,
sex, class type and experience levels.
Ethical considerations
All students were informed that the current author and student researcher is
bound to, and intended to comply with all stipulations and guidelines set forth by the
University of Southern California (USC) and California State University, Los
Angeles (CSLA) Institutional Research Board (IRB) offices. The current author
submitted a completed site permission form aUSC IRB’s Site Permission Letter in
order to complete the class presentations seeking student volunteers. Students were
advised that all participants who are under the age of 18 were to be provided with,
and must submit, a completed permission form a USC IRB’s Parent Permission

77
Form signed by their parents in addition to an informed consent form a USC IRB’s
Youth Assent Form completed and signed by the student participant him / herself;
students 18 years of age or older submitted a signed adult consent form. Participants
were also be informed that they could seek counsel, as appropriate, with any
questions or for any problems pertaining to their interpretation and/or understanding
of the survey instrument or participation in the study.
The current author’s role as a university administrator was fully disclosed and
all students were informed that there was no connection between participation in the
present study and participation and involvement in the early entrance program. In
addition, participants were informed that while they were entered in a raffle for a
prize there was no penalty for not choosing to participate or for withdrawing at any
time. Participants were also informed that no personal identifying data was
collected and permission had to be provided to use select self report data.
Role of the Researcher
As previously noted, the current researcher also served as the university
administrator (i.e. Program Director) in charge of the early entrance program from
which all the participants were selected. As Program Director the researcher was
very familiar with all early entrants currently enrolled and those recruited as subjects.
The Program Director is responsible for all aspects of program operation including
recruitment, admission and advisement. In addition to these supervisory
responsibilities, the Director instructs an orientation class that is part of the Year One
curriculum mandatory for all new students. Due to this dual role of the researcher,

78
extra effort was made to ensure the students targeted during recruitment were aware
that the research was not mandatory nor a university or program project. Students
were assured their participation was as a volunteer, and that their status as early
entrants and university students would not be affected. To this end, a portion of
mandatory student meetings held twice per term was allotted to explain the current
research and to allow students the opportunity to ask questions. Each meeting
included the following statement, "As you may know as part of my doctoral work I
am conducting research involving your perceptions of Honors classes. I am asking
for volunteers to participate in the study but your participation is entirely voluntary
and whether or not you choose to participate there will be no effect on your status as
an early entrant or as a university student.” Furthermore, students were informed
that while the researcher would be aware of the identities of the volunteers, their
identities would be kept confidential and not linked to their survey responses and that
all volunteer consent forms would be kept in a secure location in the Program offices
and would not released to either university (i.e. CSLA, USC) involved. All students
were informed repeatedly that their participation was voluntary and that all
volunteers could withdrawal from the study at any time.

79
CHAPTER FOUR
DATA ANALYSIS
In brief, a descriptive correlational study of college early entrant Honors
students’ perceptions of classroom social factors, engagement and motivation was
hypothesized to reveal positive relationships; factors including the generalizability of
findings based on the sample population of minor students, researcher bias and the
limited scope of the study were considered and discussed as potential contributing
influences. The following chapter is a presentation and discussion of the results of
the completed analysis of the collected data.
The current chapter presents the data analysis of the research previously
detailed. The purpose of the research was to examine possible relationships between
the classroom social environments (as teacher support for engagement), student
motivation (as mastery goal orientation), engagement (as collaboration) and
achievement (as grade point average) of early entrant college Honors students. The
research was modeled after and sought to extend previous research conducted by
Patrick (2007) of similar variables on middle school students. The following three
subjects were addressed: sample population, instrument reliability, and the research
questions.
Sample
The sample consisted of 65 students (see Table 5) in the early entrance
program (EEP) at a state university in California and represented 52% of the total
population of the EEP. The sample was comprised of 47.7% males (n = 31) and

80
52.3% females (n = 34). The gender distribution of the sample was not significantly
different, χ² (1, N = 65) = 0.48, ns, from the gender distribution in the total
population of the EEP program, which is comprised of 44% males and 56% females.
Consistent with the population of the EEP program, Asians and Caucasians were the
majority of the sample. Fifty-seven percent of the sample was Asian (n = 37) and
32.3% was Caucasian (n = 21). The majority of subjects were 15 years of age and
above (90.7%). Student characteristics of the total EEP population are displayed in
Table 6.

Table 5: Demographics of the Sample (N = 65)

n Percentage
Gender
Male 31 47.7%
Female 34 52.3%
Ethnicity
African American 2 3.1%
Asian 37 56.9%
Caucasian 21 32.3%
Hispanic 2 3.1%
Other 3 4.6%
Age
10-12 years old 1 1.5%
13-15 years old 5 7.7%
15-17 years old 34 52.3%
18-20 years old 24 36.9%
20 years old and above 1 1.5%

81
Table 6: EEP Student Characteristics Based on Program Data Collected in 2006-
2007-Years 1-3

Characteristic Percentage
Gender
Male 44
Female 56
Ethnicity
African American 3
Asian 45
Caucasian 40
Hispanic 10
East Indian 2
Age
12-13 years old 44
14-15 years old 56
15+ years old N/A
College
Natural and Social Science 44
Business and Economics 9
Computer Science, Engineering
and Technology
13
Arts and Letters 12
Undecided 17
Unknown 6
GPA
Regular (years 1-3) 3.56
Elder (years 4-6) 3.52

82
The academic characteristics of the sample are displayed in Table 7. Overall,
the students reported high GPAs. Three-fourths of the sample (n = 49) reported
having a GPA between 3.6 and 4.0, 21.5% reported having a GPA between 3.1 and
3.5, and only 3.1% reported having a GPA below 3.0. These numbers reflect the total
population where the average GPA since 2001 has been 3.5+ and, because Program
policy stipulates students must maintain a minimum 3.0 GPA, the overall percentage
of students under 3.0 typically constitutes students on Program academic probation.
Since 2001, no more than 4% of the total population has been on probation, which is
consistent with percentage of the sample reporting GPAs below 3.0. For analysis
purposes, GPA was re-coded as 0 = 3.5 and below and 1 = 3.6 and above. The
recoding was done because the students’ GPAs were obtained from self-reported
data based on four intervals (i.e., 0-2.0, 2.1-3.0, 3.1-3.5, and 3.6- 4.0) and only a
small number of students were below 3.0. Consistent with the Program population,
the majority of the participants identified themselves as declared majors within the
College of Natural and Social Sciences (58.5%). The number of students declared in
the College of Business and Engineering (9.2%) was slightly higher than the overall
Program population, which in 2007-08 was 9.0%. Also, the participants’ years in
EEP skewed higher than the overall population with 53.9% having participated for 3
or more years whereas for the entire population it is approximately 48%.

83
Table 7: Academic Characteristics of the Sample (N = 65)

n Percentage
GPA
2.1-3.0 2 3.1%
3.1-3.5 14 21.5%
3.6-4.0 49 75.4%
College
Natural & Social Science 38 58.5%
Arts & Humanities 9 13.8%
Business & Economics 6 9.2%
Engineering, Computer
Science & Technology
7 10.8%
Undecided 5 7.7%
Years in EEP
0-1 years 9 13.8%
1-2 years 11 16.9%
2-3 years 10 15.4%
3-4 years 23 35.4%
5 or more years 12 18.5%
Number of units completed
0-45 units 3 4.6%
45-90 units 12 18.5%
90-135 units 18 27.7%
135 units and above 32 49.2%
Number of honors courses
3-5 courses 15 23.1%
6 or more courses 50 76.9%

84
For analysis purposes, the number of units completed was recoded as 0 = 90
and below, 1 = 90 through 135, and 2 = 135 and above. The number of honors
courses was recoded as 0 = 3-5 courses and 1 = 6 or more courses. Program and
university policy states that all students wishing to graduate with Honors distinction
must complete 6 or more Honors classes so the sample reflects compliance as only
approximately 20% of the total population has yet to complete this requirement as of
fall 2008. This data also conformed with data on years in EEP and age, because, the
longer a student remains in the program the more they age and the more Honors
courses they have time to complete.
Reliability of instrumentation
The current research was modeled from a study by Patrick (2007) and
employed three of the subscales developed and used by Patrick including classroom
environment, motivation and engagement. The reliability statistics for the Patrick
study scales and corresponding scales used in the present research are presented in
Table 8. See Appendix A for all subscales.
The three-item promoting task-related interaction subscale measured the
extent to which the teacher was perceived as encouraging interaction among peers
involving academic tasks. This subscale was a shorter version of a scale developed
by Ryan and Patrick (2001). This scale was modified slightly to include the term
“collaboration” directly. An example of a question from this subscale is: “My
teacher encourages us to collaborate and share ideas with one another in class.” The

85
reliability of the promoting task-related interaction instrument was established with a
Cronbach’s alpha of .70.
The Mastery Goal Subscale was used to measure students’ desire to develop
their ability and understanding of course material and academic achievement; this
scale has been established as an indicator of student motivation. The six-item
mastery goal orientation scale measures students’ level of mastery orientation and
was adapted from the Patterns of Adaptive Learning Survey (PALS; Midgley et al.,
1996). An example of a question from this subscale is: “An important reason I do
my school work is because I like to learn new things.” This scale has been shown to
be reliable and valid (Midgley et al., 1998) and, with the current sample, there was a
Cronbach’s alpha of .77.
The five-item task related interaction subscale assesses the extent to which
students answered questions, explained content, and shared ideas about the course
subject matter with classmates and was developed specifically for the Patrick (2007)
study. This scale has been established as an indicator of student engagement. This
scale was modified slightly to more accurately represent the construct collaboration
by adding the term collaborate and/or collaboration where appropriate and
semantically accurate. Also, within this measure the term math was substituted for
“honors class” and the term “kids” was replaced with the term “students”. An
example of a revised question from this subscale is: “I share my ideas and materials
with other students in Honors classes.” See Table 4, Chapter 3 for both original
questions and revised questions. The task-related interaction scale was noted as

86
reliable and valid (Patrick, 2007) and the Cronbach’s alpha was .83 with the current
sample. An exploratory factor analysis was conducted to test the reliability of the
scales used in the current study and the reliabilities are displayed in Table 8.

Table 8: Reliability of the Subscales

Subscale Patrick Study αs Maddox Study αs
Classroom environment .70 .80
Motivation .77 .77
Task-related interaction/Engagement .83 .78

The means, standard deviations and ranges for the three subscales are shown
in Table 9. Overall, the students in the EEP reported high levels of agreement with
the items in all three subscales. The mean for the Classroom Environment subscale
was 3.26 (SD = 0.56), which indicates that the students, on average, “agreed” or
“strongly agreed” with the statements describing a collaborative classroom
environment. The mean for the motivation subscale (M = 3.38; SD = 0.56) was
slightly higher than the environment subscale. The mean for the engagement scale
indicated a lower overall rate of agreement, but the standard deviation was similar to
the other scales, indicating low variability.

87
Table 9: Reliabilities, Means, Standard Deviations, and Ranges for the Subscales

α M SD Range
Classroom environment .80 3.26 0.56 2.33 - 4.00
Motivation .77 3.38 0.46 2.33 - 4.00
Engagement .78 3.10 0.51 2.00 - 4.00
Note. All items were rated on a 1 (strongly disagree) to 4 (strongly agree) scale.

Correlational data analysis was used to address the possible relationships
between the variables being investigated and a regression was used to ascertain if
motivation would mediate the association between classroom environment and
engagement. However, the mediating role of motivation could only be assessed if all
three variables were significantly associated with one another (Baron & Kenny,
1986). In the absence of significant associations among all three measures, a
regression model was employed to examine the simultaneous effects of classroom
environment and motivation on engagement.
The correlation between two variables reflects the degree to which the
variables are related. The most common measure of correlation is the Pearson
Product Moment Correlation (i.e., Pearson’s correlation). When computed in a
sample, it is designated by the letter “r” and is sometimes called “Pearson’s r.”
Pearson’s correlation reflects the degree of association between two variables
ranging from +1 to -1 (King & Minium, 2003).
Pearson’s correlations were calculated to determine if there were significant
associations among the classroom environment, motivation, and engagement

88
subscales (see Table 10) to address research questions 1-3. In addition, Pearson’s
correlations were calculated to determine if there were significant associations
between the three subscales and the students’ GPA, number of honors classes,
number of years in the EEP, age, and the number of units taken in order to address
research question 4.
Engagement was significantly associated with the Classroom Environment (r
= .30, p < .05) and Motivation (r = .32, p < .01). These findings indicate that students
who reported higher levels of engagement also reported more positively on their
classroom environment and reported greater levels of motivation. However, the
correlation between classroom environment and motivation was not significant (r =
.11, ns). In other words, there was no clear association between the two measures.
The proposed mediation model was not supported by the data because classroom
environment (i.e., the independent variable in the mediation model) was not
significantly related to motivation (i.e., the mediator in the model).
In general, the three subscales did not significantly correlate with the other
variables displayed in Table 7. For instance, GPA was not significantly related to the
Classroom Environment, Motivation, and Engagement subscales. Similarly, the
number of years in the EEP, age, and the number of units were not significantly
correlated with any of the three subscales. However, the number of honors classes
taken was significantly associated with the Classroom Environment (r = .32, p <
.01). In other words, students that took more honors classes rated their classroom
environment more positively or, rather, rated the classroom support for engagement

89
higher. There were additional significant correlations that should be highlighted.
First, having a higher GPA was positively related to the number of honors classes
taken (r = .28, p < .05). In addition, age, years in EEP, and the numbers of units
taken were all highly correlated with one other. These findings are not surprising
given that older students tended to have taken part in the EEP for longer and have
been enrolled in the university for a longer period of time allowing them to take
more units.

Table 10: Intercorrelations of the Main Variables

1. 2. 3. 4. 5. 6. 7.
1. Instructor support for
interaction
-
2. Mastery Goal Orientation .11 -
3. Task-related interaction .30
*
.32
**
-
4. GPA .07 -.02 .03 -
5. Number of honors classes .32
**
.07 .03 .28
*
-
6. Number years in EEP .09 .08 .05 -.14 -.07 -
7. Age .18 .12 .02 -.13 .03 .75
***
-
8. Number of units .21 .14 .13 -.12 .04 .84
***
.75
***

*
p < .05.
**
p < .01.
***
p < .001.

90
In order to examine the association between the classroom environment and
motivation variables and the engagement variable, a multiple regression analysis was
conducted. Multiple regression is a statistical technique used to predict one variable
from multiple independent variables. In this case, classroom environment and
motivation were assessed for their relationship with engagement. This technique
allows a researcher to calculate the amount of variability that is accounted for by the
predictor variables. Regression analysis refers to techniques for the modeling and
analysis of numerical data consisting of values of the dependent variable or response
variable and of one or more independent variables or explanatory/predictor variables.
The dependent variable in the regression equation is modeled as a function of the
independent variables, corresponding parameters or “constants”, and an error
construct. The error term is treated as a random variable and represents unexplained
variation in the dependent variable (King and Minium, 2003).
The multiple regression model (see Table 11 and Figure 3) with the
Classroom Environment and Motivation subscales predicting Engagement was
significant, F (2, 62) = 6.34, p < .01. The two predictors accounted for 17% of the
variability of the Engagement subscale. Both the Classroom Environment (β = .26, p
< .05) and Motivation (β = .29, p < .05) subscales were significant predictors after
accounting for the effects of the other subscale. In other words, higher ratings of
classroom support for engagement and student motivation significantly predicted
higher ratings for engagement and this relationship assessment is reflected in Figure
3.

91
Table 11: Summary of the Multiple Regression Model with Classroom Environment
and Motivation Predicting Engagement

B SE B β
Classroom environment 0.24 0.11 .26
*

Motivation 0.32 0.13 .29
*

*
p < .05.

Figure 3: Regression Model with Classroom Environment and Motivation
Predicting Engagement

Engagement was significantly associated with the Classroom Environment (r = .30, p
< .05) and Motivation (r = .32, p < .01).

In summary, the sample of EEP students obtained for the current study
mirrored the population of the entire program in terms of its gender, race/ethnicity,
and field of study distributions. The Classroom Environment, Motivation, and
Engagement subscales showed good reliability. In addition, the means for all three
subscales indicated that the average student “agreed” or “strongly agreed” with the

92
items in the scales. In other words, the students reported positively on their
classroom environment and rated their engagement and motivation levels highly. The
correlation analyses revealed that the Engagement scale was positively related to
both the Classroom Environment and Motivation subscales. On the other hand, the
association between the Classroom Environment and Motivation subscales did not
reach significance. The multiple regression analysis showed that both classroom
environment and motivation were significant predictors of engagement after
accounting for the effects of the other predictor variable. The correlation analyses
also revealed that GPA was not significantly related to the three subscales. However,
the Classroom Environment subscale was positively associated with the number of
honors classes in which the students had enrolled.

93
CHAPTER FIVE
DISCUSSION
This chapter discusses the data analyzed in the research presented earlier. The
research was designed to discover possible relationships between the classroom
social environment and student motivation and engagement. Research on these
variables related to student performance was explored in detail in previous chapters
and will be discussed in relation to the data from the present study. The current study
used test instruments measuring mastery goal orientation as an indicator of
motivation and task-relation interaction/collaboration as a measurement of
engagement, these terms will be used interchangeably for the purposes of the
following discussion. Also measured was teacher support for engagement as an
indicator of classroom social environment, referred to in this discussion as classroom
environment or classroom. Task–related interaction was measured as an indicator of
collaboration which is used presently as a synonym for engagement. Achievement
was measured through student self reported grade point average (GPA). The sample
size and recruitment efforts for the study may have been negatively affected due to
the inability of the researcher to gain access to Honors classes for in-person
recruitment presentations.
Results from the present study found significant correlations between
classroom environment and engagement (r= .30, p> .05). In addition, a strong
relationship between engagement and motivation (r= .32, p>.01) was discovered.
However, there was not a significant relationship found between classroom

94
environment and motivation thus precluding an analysis of the mediating effects of
motivation on engagement. However, both the classroom and motivation were found
to be predictive of engagement (β = .26p>.05) and motivation (β = .29, p> .05).
There were no significant differences discovered among participants in relation to
the demographic characteristics analyzed nor were relationships established between
the three variables under investigation and other student related factors such as
gender, age, ethnicity or college of choice. There was, however a strong relationship
between experience and classroom environment (r= .32, p> .01) so that the more
experience students gained in Honors classes the more positively they viewed
classroom support for engagement. Students across all groups reported high mean
levels of classroom environment ( , = 3.26), motivation ( , = 3.38) and engagement
( , = 3.10) as well as a high level of achievement with 96% reporting GPA’s
between 3.1 and 4.0. Because of these similarly high scores on classroom,
motivation, engagement and achievement it was unexpected to discover there were
no significant correlations found between these variables. It is presumed the lack of
significance was due in part to statistical causes related to the number of participants
and low variability across responses.
This chapter will address the research problem, a synthesis of the results in
relation to previous research reviewed, the limitations of the study, the implications
of the study and future research needs.

95
The Research Problem
The present research was completed to address an academic
underperformance problem of a group of highly gifted early college entrants
participating in a college Honors program and to address a research gap. One
possible explanation for the performance problem may be related to classroom
factors. Gifted students are vulnerable to various issues that may negatively affect
their school achievement including their environment and social relations therein
(Newhart et al 2002). Research has identified several important factors related to this
problem.
Gifted students including early entrants may be affected by social-emotional
issues because of their exceptional abilities, they are more sensitive to the social
needs of their non-gifted peers than visa versa, and unlike their non gifted same age
peers they may need their social-emotional to be adequately met in order to have
their cognitive needs met as well (Colangelo 2002). As environmental situational
variables have an effect on behavior, then a student’s classroom social environment
is important in understanding school performance, including for those classified as
high-ability or gifted (Aronson, 2008; Cigman, 2006). Since a gifted student’s
cognitive needs and social needs are mutually dependent based on differences in
their social-emotional development then it is logical to assume school performance
issues for early entrants may be particularly related to the classroom environment.
The influence of the classroom environment on student behavior and success has
been linked to student motivation and engagement whereby the more motivated and

96
engaged a student is the more likely they are to increase achievement (Fraser &
Fisher, 1982 and Ryan and Patrick, 2001).
The current underperformance problem may then be addressed by a focus on
the effect of malleable classroom social environments on student motivation and
engagement using a socio-cognitive theoretical foundation. Current opinions within
the field of education on the importance of engagement and collaboration in learning
have evolved from seminal theoretical works such as social cognitive theory, social
learning theory and social constructivism which address the role of human
interactions and the environment in learning.
The conceptual model of social cognitive theory may be illustrated as a
triangulation of the three factors behavior, environment and personal beliefs. This
model has several important educational implications, students may often learn
simply by observing their peers, that the consequence of student behaviors may
shape future behaviors and beliefs, that modeling may be an effective method to
change student behavior and that teachers, and other adults, can model appropriate
learning behavior (Ormrod, 2004). Nearly all cognitive science theories entail some
form of constructivism. This continuum ranges from the individual constructing
knowledge in the class environment through personal information processing to the
view that knowledge develops as one engages in dialogues and interactions with
others (Palincsar, 1998).
The discussion is organized in the following manner: a synopsis of the
literature previously reviewed in relation to the research questions posed and the

97
results of the present research. This synopsis will be framed using the research
questions established in an earlier chapter.
Research question I: The relationships between student perceptions of the class
environment, motivation and engagement
In the present study which explores relationships between the classroom,
motivation, engagement and achievement, results confirmed and extended previous
studies on similar variables through establishing significant correlations between the
classroom environment and engagement and between engagement and motivation.
Unfortunately, there were few, if any, previous studies focused on these specific
relationships, so literature involving these general variables was reviewed in order to
gain insight on the current research problem. Surprisingly, while students report
somewhat equally high levels of motivation, engagement and achievement with low
variability, the correlations between the three main variables and achievement were
not currently found to be significant. Also unusual was the lack of a significant
correlation between classroom environment and motivation that subsequently
eliminated the possibility of identifying possible mediating effects of motivation.
The absence of a relationship between the classroom environment and motivation as
well as the discovery that achievement was not related to either motivation,
engagement or the classroom was unexpected especially considering the rather high
level of achievement reported by a large majority of students (96%). It is presumed
that with a larger sampling of students including more of those who are currently
underperforming would have revealed relationships between the variables. Following

98
is an exploration of the literature previously reviewed and the related results from the
current study.
Honors students and Honors classes were examined in a qualitative study
examining student’s orientation toward learning in higher education (Storrs, 2008).
Results indicated that factors that help shape Honor student perceptions and learning
includes previous academic experiences, family characteristics, and individual
biographies that include psychological, emotional and personal characteristics
(Storrs, 2008). The present study sought to further the understanding of these factors
on Honors students’ perceptions of their own learning in regard to academic
experiences (i.e. classroom environment). Data from the current study revealed that
EEP students’ previous academic experiences influenced their perceptions of their
learning experience, students with more experience in Honors classes reported to
have a more positive perception of the classroom environment with experience
correlated to the classroom ( r=. 32 p>.01). These results support the results noted by
Storrs (2007). Other characteristics including gender, age and ethnicity were not
found to have a significant relationship to the variables of interest and family
characteristics and individual biographies aside from age, gender and ethnicity, were
not assessed and those characteristics that were assessed were not found to correlate
with the classroom environment.
A contemporary expectancy-value theory of motivation comes from the work
of Eccles and Wigfield (2000) who postulate that student motivation for success is
based on student expectancy for academic success and the value students place on

99
academic tasks. This viewpoint reflects a social-cognitive perspective involving the
reciprocal dynamic of student, environment and behavior. The theory may be
described as a linear model flowing from the social world (environment and culture)
to cognitive processes (perceptions of social world), motivational beliefs (task values
and expectancies) resulting in achievement behaviors (engagement, learning
strategies). In relation to the present investigation, the model may be described as
reflecting a linear representation proceeding from classroom factors to motivation
resulting in engagement achievement.
The present study employing a similar conceptual framework, revealed data
reflecting that engagement was related to both classroom environment (r=.30, p.>05)
and motivation (r= .32. p> .05 but, surprisingly, there was no significant relationship
established with achievement and the classroom (r=.07) nor between the classroom
and motivation (r = - >02); student task value was not assessed directly, though a
relationship between student engagement and achievement to task value beliefs
may be argued and will be explored later in this chapter. In the present study, the
social cognitive framework was substantiated through student perceptions of their
social world (perceptions of their classroom environment) to motivational beliefs
resulting in achievement as indicated by engagement. Though significant
correlations were, surprisingly, not established for each link in the process the
current study did find high levels of support for engagement in the classroom ( , =
3.26), motivation ( , = 3.38) and achievement.

100
An analysis of research on the expectancy value theory of motivation was
conducted by Wigfield and Eccles (2000) to assess changes in children and
adolescents’ beliefs about their own abilities and expectations for success and to
assess the relationships between adolescents’ ability expectancy beliefs and task
values, to their performance and choice of activity. In addition, adolescents’ valuing
of some activities becomes slightly more positive in later adolescence resulting in
greater levels of motivation related to ability beliefs. It was also noted that ability
beliefs and expectations for success are not empirically distinguishable.
While no direct relation was established in the current study between
motivation and achievement as per the expectancy-value theory (r= .07), students
reported both strong levels of motivation and achievement. Since ability beliefs and
expectations for success were established as indistinguishable indicators of
motivation it may be assumed that motivated students also have positive ability
beliefs. In addition, as motivation and engagement have been linked to achievement
then it is reasonable to assume the current data that reflects both a strong relationship
between engagement and motivation (r=.32, p>01) would also support the notion of
expectancy beliefs related to achievement. It is unusual that such a direct correlation
was not established presently, though we may assume early entrants have strong
expectations for success. Interestingly, present data that shows students’ experiences
in Honors classes is related to their perceptions of classroom environment, does
confirm previous data showing an increase in motivation based on ability beliefs in
later adolescence (Winfield & Eccles, 2000). As student experience more Honors

101
classes they age and their perceptions of the classroom change so it is reasonable to
assume this is linked to changes in their self-efficacy in later adolescence.
Adolescents appear to have specific beliefs about what they are good at and
these ability related beliefs decline across elementary school years until late in high
school when they begin to increase (Wigfield & Eccles, 2000). Although the
present data did not reflect significant differences between age groups in terms of
motivation, the vast majority of participants ( 89%) who reported high levels of
motivation ( , = 3.38) were in late adolescence between 15- 21 years of age. So the
finding that students in late adolescence have a more positive value for ability related
beliefs was supported by the current research.
Eklof (2006) investigated students’ level of test-taking motivation as related
to low-stakes assessments. Based on expectancy value theory, the author’s intent was
to develop an instrument that measured test-taking motivation. The expectancy
component was operationally defined as general ability and self-efficacy beliefs,
concepts that are highly related for adolescents. The value component was
conceptualized as the amount of importance the student attaches to the task, also
known as task value.
As the factors involved in expectancy value theory occur in a social context,
Eklof (2006) assumed student test motivation might be associated with the manner in
which tests are presented to students, and their attitudes toward the test, both of
which would be construed as classroom factors. These factors were regarded as
indicators of student beliefs, expectations, perceptions, attitudes and motivation.

102
Results indicated that perceived task value is closely connected to motivation to
perform well. As current data shows participants report high levels of motivation
( = 3.38) and achievement, it may be assumed they also may have a high level of
task value in terms of test taking and class assessments. Though the present data also
shows a high level of achievement, oddly, there was no relationship established
between motivation and achievement. Current data that reflects a positive perception
of the classroom ( , = 3.26) and high achievement may reasonably indicate early
entrants have positive ability beliefs regarding test taking and, thusly, task value and
test motivation. The Eklof (2006) results showing a possible connection between
task value and motivation was then extended to the group of adolescent early college
entrants through the present study.
A gifted student research center at the University of Connecticut (Renzulli,
2002) released a report that described value constructs applicable to the value gifted
students place on activities: intrinsic value, utility value and attainment value. Task
values are associated with choice and persistence, indices of motivation. Current data
showing high levels of motivation ( , = 3.38) and engagement ( , = 3.10) indicate
early entrants value the activities associated with achievement.
Intrinsic value is value that results from enjoyment; students typically are
intrinsically motivated to pursue tasks that are novel, interesting, enjoyable, exciting
and optimally challenging. Challenging tasks are noted as especially important to
gifted student collaboration in their learning (Patrick, 2005).

103
Deci and Ryan (1985) put forth that educators could improve intrinsic value
by creating classroom environments that provide students opportunities to engage in
interesting, personally relevant challenging activities. As current data reveals
students’ high levels of motivation ( = 3.38), perceptions of a supportive classroom
( , = 3.26) and achievement ( 96 % reporting GPA’s between 3.1 and 4.0), it may
be presumed that they have some intrinsic value associated with the challenging
nature of Honors classes. This finding is encouraging to the present study as
engagement may be considered a interesting learning strategy involving the
challenge of exploring conflicting ideas between students during their interactions
with like-ability peers. As gifted students prefer challenging tasks (Patrick, 2005)
and may share similar emotional developmental issues that may allow them a degree
of comfort and pleasure in their learning with peers (Colangelo, 2006; Cigman,
2006; Storrs, 2000), then engagement with peers in challenging work would allow
them to develop intrinsic value for their study tasks ( Deci & Ryan, 1985). The
present study supports the previous research as the students report high levels of
engagement ( = 3.10) in their challenging Honors classes. Also, engagement and
motivation were significantly correlated (r= .32, p>.01) which may indicate the
students have developed intrinsic value for the collaborative tasks presented in
Honors coursework. Also, current data showing a significant relationship between
engagement and the classroom environment was presently established (r = .30,
p>.05) so the classroom environment established by university faculty that supported
engagement was effective in increasing student engagement which subsequently was

104
strongly associated with student motivation (r= .32, p>.01), likely as a result of
developing intrinsic value for their work. There was no such relationship currently
noted between engagement and achievement (r = .07) though the mean scores
reflecting student reports of classroom support for engagement ( , = 3.26),
motivation ( , = 3.38), engagement ( , = 3.10) were very similar. It is presumed
faculty were influential in provided an environment promoting intrinsic value noted
as important by Deci and Ryan (1985) and students’ favorable perceptions of this
supportive environment increased as they gained more exposure to Honors classes.
Utility value refers to how a task relates to future goals. Students may value
the future reward or outcome a task has for helping them achieve a goal. The task
with utility value must be perceived as instrumental to future or long-term goals. In
regard to the present research, these findings suggest that the current Honors
instructors may construct classes that support engagement as necessary in meeting
learning objectives for the course and the future, thus creating utility value for tasks.
Data suggests that these Honors instructors current support for the use of
engagement as an effective learning tool is supported by students, who reported high
levels of engagement ( = 3.10) and their perceptions of the classroom social
environment as supportive of engagement ( = 3.26). It is presumed that the utility
value associated with the classroom environment increased as student engagement
levels were strongly correlated with their motivation (r = .32, p> .01).
Additionally, Peterson (2001) demonstrated that gifted underachievers
improved their performance when value was placed on career and future academic

105
goals so utility value that links engagement in Honors classes to graduation and
career success may be an important construct for addressing high ability student
motivational needs and to helping underachievers. Presently motivation was not
significantly related to the classroom environment (r= .11) but was established as a
predictor of engagement, which was, in turn, related to the classroom environment
(r= .30, p>.05). Data was not collected on student perceptions of long-term goals nor
their relation to learning activities such as engagement.
Self-regulation has emerged as a method to improve student performance
especially for gifted underachievers (Ruban & Reis, 2006). In a study on
perfectionism, goal theories, and gifted students, the authors noted that one
characteristic common to all three types of gifted student goal-orientation was the
characteristic of evaluation. Gifted students have a tendency to evaluate their work
and performance and this is a self-regulatory behavior that is an indicator of a
mastery goal orientation and an indicator of motivation.
A mixed methods study exploring the nature of self-regulation strategies
among different populations of college students was conducted by Ruben and Reis
(2006). Quantitative and qualitative data analysis revealed that, in general, high
achievers were more likely to use self-regulatory strategies. In summary, Ruben and
Reis (2006) noted the positive relationship of self-regulation and achievement,
suggesting that self-regulation enhances motivation which is related to performance
(Lin, Lin & Laffey, 2000; Patrick, 2008). Current data did not establish a link
between motivation and achievement but as students report a high degree of

106
motivation ( = 3.38) and achievement, it may be assumed they are employing some
self-regulatory techniques. If engagement is related to achievement and current data
reflects engagement as significantly related to motivation (r= .30, p>.05) then the
current data may serve as further support for the notion that self-regulation is
associated with achievement as put forth by Ruban and Reis (2006). Furthermore this
data may support the use of self-regulation techniques to assist underachievers.
A study conducted to assess students’ perceptions of the classroom social
factors related to engagement and motivation by Patrick et al. (2007) provided the
framework for the present investigation. Patrick (2007) sought to investigate the
presumption that task-related interaction (engagement) was related to perceptions of
the classroom social environment. Additionally, this researcher sought to discover
whether these relationships were mediated by personal motivational beliefs. A link
between engagement and achievement was proposed.
A social cognitive perspective of learning supports the idea that students’
social relationships and perceptions (i.e. peer interactions) are related to and
predictive of school outcomes. The author proposes that students’ perceptions of
their class environment (i.e. levels of affiliation, cohesion, fairness, teacher and peer
respect and support) are related to engagement and achievement and are mediated by
adaptive motivational beliefs (Patrick 2007). As this research by Patrick addresses
the research questions presently being assessed and helps form the framework for the
current investigation, a more detailed review is logical.

107
Data analysis revealed that student academic support provided by peer
interactions contributed to student engagement (Patrick, 2007). Also, student
engagement was found to be mediated by the motivational constructs of mastery
goals and academic self-efficacy. Adaptive classroom social environments were
proposed to enhance students’ focus on mastery goals (motivation) thereby
facilitating engagement; this effect would then lead to achievement. More simply
stated, students’ classroom interaction with peers (engagement), and their perception
of teachers’ support for such interaction (classroom) was related to motivation and
engagement thus leading to increased achievement.
The current data did not support a mediating effect of motivation because the
classroom environment was not significantly related to motivation but it was
discovered that adaptive classroom environments were related to student engagement
(r=.30, p> .05), thus extending the Patrick results to an older population of
adolescent students in an urban university Honors setting. The linear relationships
between the classroom, motivation, engagement and achievement established by
Patrick were not currently replicated, although current data did reflect a high level of
student achievement, engagement and motivation across all demographic groupings.
While the research framework created by Patrick (2007) was simulated and
extended for a population of college honors students, the scope of the present study
was limited to the use of only one scale per research construct though it is still
meaningful in regard to the overall question involving the impact of classroom on
student achievement. The present study confirmed the impact of the classroom

108
environment on student engagement though several factors may be considered
limitations affecting the current study and will be explored later in this discussion.
Research question II: Will results from previous studies of social environment and
engagement be replicated in a university honors context for early entrant students?
The current study sought to extend previous studies exploring the classroom
environment and engagement with a group of gifted early entrants studying in a
college Honors context. Findings suggest limited support for previously established
effects of the classroom environment on achievement, support for the predictive
effects of classroom and motivation on engagement and strong support for the
relationship between engagement and motivation. Due to the limited availability of
research related directly to the specific research question, literature on gifted
students, the school environment and engagement was explored.
A contemporary investigation of giftedness by Cigman (2006) classified
gifted students using an environmental framework, environmental factors such as
parenting techniques and classroom structure, were noted as important variables that
influence student achievement. Results confirmed that the school environment is
very influential in the identification and development of gifted students, and the
learning process; natural ability (giftedness) and the environment are deeply
intertwined (Cigman, 2006). The author noted the importance for educators to
understand interactions between high-ability students’ natural abilities and the
learning environments in order to improve their performance (Cigman, 2006).
Current research data did not fully support the Cigman (2006) results of the

109
symbiotic relationship between environment and performance, a significant
relationship between classroom factors and achievement was not found in the current
study (r= .07) but perceptions of the classroom were significantly correlated with
engagement (r=.30, p>.05). Due to the relationship between engagement and
performance earlier noted it is reasonable to suspect the present data as somewhat
supportive of the Cigman (2006) results.
In a report on the counseling needs of the highly gifted, Colangelo ( 2002)
suggested that for gifted students, social and emotional issues may influence learning
due to their exceptional abilities, and that, since adolescence is a particularly difficult
period for gifted students who are generally more sensitive to the social needs of
non-gifted peers than the inverse. This sensitivity to the social environment and
sensitivity to peer interactions may be an important discovery in relation to the
present study. Current data revealed that student engagement was related to both
motivation (r=.30,p>01) and the classroom environment (r=.32,p>.01) and
although the relationship between engagement and achievement was not significant
(r= .07) most students reported a high level of engagement with their like minded
Honors peers ( =3.10) as well as other non early entrant students participating in
Honors classes. The implication is a connection between peer interaction and
motivation as noted by Colangelo (2002). Though, unexpectedly, no significant
correlations were found between achievement and engagement (r= -.02) student
achievement levels were high with 96.5% reporting GPA’s between 3.1 and 4.0. In
addition, engagement and motivation were strongly correlated (r= .32, p> .01). Most

110
gifted students are not insensitive to others social needs and cues. Therefore the
current data supports the research noting that gifted students sense of engagement
with teachers and peers may be particularly important for learning and academic
success, especially when engaging with like-ability peers in Honors coursework
(Colangelo 20002; Cigman, 2006).
Supporting the positive effects of engagement, Noble (2007) conducted a
qualitative follow-up study on the experiences of early college entrants specifically
focused on their long-term effects and experiences. Overall, analysis of the
qualitative data revealed that the early entrance to college through an Early Entrance
Program had a profoundly positive effect on students. It is especially interesting to
note that the factor that was identified as the most beneficial aspect of this
experience was peer group support. The benefit of peer interactions was noted as
affecting both the social and intellectual development of the students in a positive
manner. While it was revealed that social influences and peer support were reported
to be extremely beneficial, little was discovered in the study regarding how the
school environment may have specifically helped promote these helpful peer
interactions and/or collaboration. The present study sought to begin to fill in this
important gap by revealing that while in school, early entrants report high levels of
engagement ( = 3.10), there was a significant relation between engagement and the
classroom social environment. In addition, since having a high GPA was positively
related to the number of Honors classes completed ( (r=.28,p>.05) then it may be
concluded that the more exposure students have in the collaborative atmosphere of

111
Honors classes the better they perform thus potentially explaining the positive
perceptions noted by Colango. Since a gifted student’s self-concept of their
giftedness as positive is related to academic performance (Keer, Colango and Gaeth,
1988), the present study established students’ positive experience with in-school
collaboration through a supportive classroom environment as possible support for
the positive experiences of alumni as noted by Keer, Colango and Gaeth ( 1988).
Data on former early entrants who reported their positive experience as linked to
their ability to engage with other high-ability students may be traced to the adaptive
classrooms they experienced while in school and this link was supported by the
present study.
Pollio (1996) conducted a qualitative study on the pedagogical differences
between the disciplines and teaching environments of natural sciences and
humanities to determine differences in the use of cooperative classroom learning
environments. Of specific interest to the current review are results revealing
differences in social relationships and the student learning that may occur in various
types of classes. Pollio (1996) noted the pursuit of knowledge is often more solitary
for humanities faculty than natural sciences faculty, but humanities faculty were
more likely to encourage student participation and involvement in class. Pollio
(1996) suggested that natural science faculty were more effective than humanities
faculty in classroom form and procedure and in preferring collaboration in research;
humanities faculty were rated as better in interacting with students and encouraging

112
student involvement (including collaboration and peer assistance efforts) in the
classroom but preferred solitary research endeavors.
All faculty in the Pollio study reported some use of collaborative learning,
whether in the classroom or in research endeavors. This data is informative with
regard to addressing the current research question involving understanding the class
factors that may contribute to student collaboration. While data from the present
study did not reveal correlations between engagement and students’ college of choice
(NSS, Arts and Humanities), the majority of students (58.5%) surveyed, who
reported high levels of collaboration and classroom support, were Natural and Social
Science (NSS) majors and the second most popular college was Art and Letters and
Humanities (AL&H) at 13.8%. So while the present study did not assess specific
perceptions of research experiences as opposed to classroom experiences, it seems to
support previous research by Pollio indicating faculty preferences for supporting
collaborative work as 72.3% of students currently surveyed were within either
science or humanities colleges and reported high levels of engagement ( , = 3.10). It
is possible that faculty supported engagement, no matter the context, is related to
student engagement/collaboration.
Research question III: Is the degree of student collaboration in classrooms related to
student motivation and learning characteristics?
A social-cognitive theoretical framework guided the present research on the
effects of the classroom social environment on student motivation and engagement.
As indicated by previous literature, various forms of engagement as a learning

113
characteristic including collaboration and the closely related concept of cooperative
learning are related to student achievement, motivation and success. The current
study discovered equally high levels of student achievement, engagement and
motivation, in addition to positive perceptions of the classroom environmental
support for engagement, though surprisingly this study failed to discover significant
relationships between these constructs. The strong relationship between engagement
and motivation (r= .32, p>.01) in conjunction with the predictive effects of the
classroom environment and motivation on engagement does support the supposition
that a supportive engagement and motivation are affected by the classroom
environment. Though no relationship between the classroom and motivation was
discovered a connection may be extrapolated based on the relationships between
motivation and engagement (r= .32, p> .01), and of the classroom to engagement
(r=.30, p>.05). Since the classroom was related to engagement which was related to
motivation, a social-cognitive foundation was currently supported. The present study
assessed no learning characteristics aside from engagement.
Vygotsky’s model of learning explores children’s developmental learning
process and has implications for the field of education. Vygotsky stressed that the
personal activity of the student must be placed at the base of the educative process
(Vygotsky, 1926). Collaboration as a form of student activity is presently defined as
engagement. This model of learning highlights the idea that interacting with others,
particularly on tasks that challenge the learner, formulates the basis for and facilitates
the learning process.

114
Johnson and Johnson (2000) conducted a meta-analysis which determined
that cooperative learning methods overall tend to be related to higher achievement.
These findings provide support to this Vygotskian model of learning, as cooperative
learning methods are based on the idea that learning will be facilitated through
interactions with other students to achieve learning tasks.
Data from the current study revealed that both the classroom environment (β
= .26p>.05) and motivation (β = .29, p> .05) were significant predictors of
engagement. Higher ratings of classroom support for engagement and motivation
predicted higher ratings of engagement. It seems that for early entrants in Honors
classes, interacting with others facilitates learning as noted in the Vygotskian model.
A study by Antil et al. (1998) examining the prevalence and forms of
cooperative learning used among elementary teachers was reviewed. Results
indicated that all teachers reported using some form of cooperative learning, though
they used different grouping strategies and aspects of a traditional cooperative
learning format. Results indicated that the most critical element of cooperative
learning was noted as positive interdependence. This is the belief that one can only
reach their learning goals if others also reach their goals. Positive interdependence
can be a malleable class component (Ghaith, 2007); data from the current study
extended these results to university Honors faculty with data revealing students
perceived the Honors classroom as supportive of engagement ( = 3.26), as well as
reported high levels of collaboration, a form of positive interdependence.

115
Antil et al. (1998) noted findings that revealed that instructor support for
cooperative learning is essential and that cooperative learning strategies were most
effective when under faculty influence or control. Current data supports this notion
of faculty preference for collaborative learning reflected through participants’
positive reports of support for engagement in the classroom ( = 3.26) across all
colleges and their subsequent engagement levels ( = 3.10). The present study
extended the findings of collaborative learning preferences of elementary school
teachers to university faculty.
Johnson, Johnson, and Stanne (2000) produced a comprehensive review of
literature on the effectiveness of increasing achievement through the use of
cooperative learning strategies. This meta-analysis reviewed several studies within
the field in order to describe and determine the empirical support validating the
effectiveness of the different methods of cooperative learning in education. Results
indicated that all of the cooperative learning methods studied were found to relate to
significantly higher achievement than competitive or individualistic learning
approaches, although effect size varied dependent on the particular cooperative
learning method utilized. Unlike the results from Johnson, Johnson, and Stanne
(2000), data from the current study showed no significant relationship between
achievement and collaborative learning but GPA was related to the number of
Honors classes taken ( r=.28, p>.05), so it seems that more exposure to Honors
classes results in higher levels of achievement. In addition, since engagement was
significantly related to classroom environment (r= .30, p> .05) it seems university

116
faculty support for collaborative engagement is effective in enhancing achievement.
Since motivation has been established as related to achievement, and the current
study established a link between motivation and engagement, then it seems
engagement is effective in supporting achievement. In the sense that cooperative
learning is a form of engagement then the current study has mirrored the findings of
(Johnson, Johnson, and Stanne, 2000) of cooperative learning as a more effective
technique than individualistic learning in supporting student achievement.
As cooperative learning has been noted to exist when students work together
to accomplish a learning goal (Johnson & Johnson, 2000), peers assisting one
another, or collaborating, it may be classified as a component of cooperative
learning. Tutoring is one of the more common forms of peer-to-peer academic
assistance and has been noted as having a positive impact on academic achievement,
persistence and graduation (Hodges & White (2001).
On peer tutoring and cooperation, Butler (2006) completed a literature review
and analysis on changes in college teaching as related to peer support, discussion and
cooperation, each of which were related to college success (Bond, 2006). Butler
notes that the majority of college students, including high achievers, display a high
preference for peer teaching, discussion and cooperative learning.
Analysis of related literature further indicated that females tend to prefer
collaboration at a higher rate than males (Bond, 2006). Butler (2006) hypothesizes
that learning to teach (i.e. peer tutoring efforts), facilitates intrinsic motivational
processes that supports conceptual learning that is related to the academic success of

117
high achievers. Results showed that the subject group that displayed higher
conceptual learning, perceived themselves to be more actively involved (engaged) in
their coursework than the other subject groups. Butler’s results indicate a linear
relationship between engagement and motivational processes that may reflect student
gender differences. Data results from the present research showed no significant
gender differences in responses to survey questions. Though females (52.3%)
outnumbered male participants (47.7%), these percentages are not significantly
different that the total Program population. Similar to previous findings on peer
interactions and engagement the current data also supported a strong link between
collaborative behaviors and motivational processes (r= .32, p> .01). Collaboration,
potentially as peer tutoring, is related to motivation and, thusly, effective learning for
college early entrant Honors students; although peer tutoring specifically was not
assessed. The availability of peer tutoring is prevalent as both the Program and the
university offer tutoring services for students. Early Entrant students have
established their own Peer Tutoring Program through their student government that
is organized and managed by early entrant students for early entrance students. In
addition, all new early entrant students are introduced to the university’s Tutoring
Services Program during their first term of study in mandatory orientation classes.
Program staff and student government support of all Tutoring services have not
served to significantly increase the numbers of students who utilize tutoring
assistance.

118
Understanding the relationships between the class environment, motivational
processes, and collaboration may be associated with the link between tutoring and
motivation as reported by Butler (2006). The present research strengthened Butler’s
work by extending data on peer tutoring to student collaboration in general. In
addition, the link between engagement and motivation was extended to early entrant
Honors students in particular.
Snidow (1995) produced a qualitative evaluative study looking at the
effectiveness of an interdisciplinary cooperative learning approach for adolescent
Honors students. The study was conducted to answer questions involving effective
student learning and teachers’ construction of effective learning environments. The
author’s purpose was to determine if class structure is effective in student success
and to identify elements of the class related to success. Effective instruction was
hypothesized to be defined as a product of the degree to which students perceive that
cohesiveness and cooperation exist in the classroom. Perceptions of support were
also associated with effective instruction and achievement. Results from data
collected led the researchers to surmise that many factors contribute to academic
success and student growth, including a class environment designed to provide
cohesiveness and cooperation, both of which may be associated with collaborative
student engagement.
In summary, data revealed that cooperative learning was a necessary tool in
the enhancement of the academic environment for both student and faculty. In
general, cooperation supported by class design was supported as a component in

119
effective teaching, learning and positive personal growth for students. Data reflecting
student perceptions of classroom environments that support engagement and their
motivation and engagement are encouraging in terms of support for effective
learning. The current data also supports the positive nature of the adaptive classroom
through its correlation with engagement (r= .30, p> .05) and the perceptions of
students of the classroom environment as supportive of engagement ( = 3.26) and
the correlation between achievement and Honors class experience (r=.28, p> .05).
Research by Lin, Lin and Laffey, (2008) centered on social compatibility
including collaboration in a web based learning environment. This study examined
how social and motivational attributes influence learning experiences using the
establishment of four constructs: social ability, goal orientation, task value, and self-
efficacy. The authors sought to understand how social and motivational factors
contribute to collaboration and to learning satisfaction in an on- line-learning
environment.
To create the theoretical framework for their study that included learning
satisfaction and social interaction, the researchers examined several key constructs.
Social interaction was defined as the Vygotskian notion that learning occurs as a
result of social practices, a concept similar to collaboration.
Results indicated that students’ perceived social ability influenced their
satisfaction and they had a more positive perception of the learning experience. Also,
students’ perceived task value and self-efficacy, both motivational constructs had a
direct impact on learning satisfaction so that students who placed higher value on a

120
task and had a high sense of self-efficacy were more satisfied with their learning. In
addition, social ability was positively correlated with intrinsic goal orientation, task
value and self-efficacy. Students with high social efficacy were more positive and
had more intrinsic value and motivation for learning and collaboration. Lin, Lin and
Laffey’s (2008) results supported the concept that a sense of being connected to the
learning community is correlated to effective learning. Peer support was
demonstrated to be very important. A psychological sense of community,
characterized as an acknowledged sense of interdependence among students, was
noted as a partial explanation for the study’s findings. The implication is that peer-
to-peer collaboration is more influential than other class factors involving student to
teacher interactions and satisfaction. In the current study collaboration was also
presently established as related to motivation (r= .32, p>.01) and a supportive
environment (r= .30, p> .05) but not to achievement (r= .07). In the present research
social efficacy may be related to engagement which was strongly related to
motivation(r= .32, p> .01), thus extending the research from on-line learning
environments to the physical environment currently under investigation.
The Lin, Lin and Laffey study reviewed above, examined how well
motivational variables and social ability together explained learning satisfaction in
an on-line atmosphere. Results revealed that learning satisfaction, social ability and
peer interactions, and motivational constructs including intrinsic goal orientation,
task value and self-efficacy were all positively correlated and led to increased
student satisfaction and performance. These findings further highlight the

121
importance of examining the relationships of these factors in regard to the high
ability early entrant student population. The same relationships were not presently
established, though both the classroom environment and motivation were predictors
of engagement. Student satisfaction was not currently assessed, but it may be
assumed that students’ high level of achievement reflects some degree of
satisfaction.
Limitations
Limitations to the present study include the minimized generalizability of the
data to university honors students in general and to those early entrants currently
underperforming. Also the collection of data required several requests for volunteers
though the research design specified a single e-mail request and classroom
presentations. The researcher was not permitted access to Honors classes so the in-
person request for volunteers presentation was not completed and the initial e-mail
request garnered too few participants, so was repeated multiple times until an
adequate n was achieved. These repeated and failed efforts to collect sufficient
student participants occurred over a 60 day period during which time students may
have discussed the research effort potentially leading to negative perceptions of the
worth of the project ( i.e. low task value) that may have affected the overall number
of student volunteers and their responses.
Also, the researcher’s duel role of Program Director may have negatively
affected the recruitment effort. In addition, as Director, the study concepts of student
engagement and motivation have been introduced to the student population through

122
study skills seminars, student meetings, newsletters and introductory freshmen
course materials thus potentially leading to a response bias. In regard to the research
problem involving student underperformance, the data collection methodology did
not include efforts to specifically isolate those students currently underperforming
thus resulting in the inability to fully address the research problem. Also the sample
population skewed older and more experienced than the general population with only
6% reportedly younger than 15 whereas the entire population under 15 is 34%.
Another factor that may limit the generalizability of the study is the lack of equality
among the five (5) colleges, the sample population was overwhelmingly associated
with the college of Natural and Social Science (NSS) and Arts & Letters; while NSS
is the most popular choice among all students (44%) a more balanced representation
especially reflecting the college of Engineering, Technology and Computer Science
would have been more effective.
Implications
As the current study was designed in part to address an underperformance
problem involving a group of early college entrants, a discussion of the implications
of the data currently under review is necessary. Following is an examination of
implications for future practice as related to the data presented earlier and the current
problem.
Results indicating student perception of the classroom as supportive of
engagement as well as their reported high levels of motivation, engagement and
achievement are encouraging, however, because these levels represent students who

123
largely reflect the highest achieving students, the impact on addressing the current
problem affecting a small sub-population of students may be minimal. Therefore the
data may best impact underachievers through use as a best practices template. As
students who report the highest levels of performance seem to also to report high
motivation and engagement, traits associated with school success (Eccles &
Wigfield, 2007; Wigfield & Eccles, 2000), then efforts to increase engagement and
motivation for underachievers is important. In addition, since the school environment
is influential in meeting gifted student learning (Storrs, 2008; Cigman, 2006 and
Noble, 2007), and has been linked to motivation, engagement and achievement
(Patrick, 2007), then ensuring all students participate in Honors class environment as
early and as long as possible, may be influential in increasing student
performance.
As the current data suggests, the more Honors classes students experience,
the more positively they perceive the supportive nature of the class, and
consequently, they experience higher levels of engagement. This finding, therefore,
implies a need to increase the numbers of honors classes students complete early in
their collegiate careers. Since a student’s first year in college is influential in terms
of future success, it seems reasonable to increase the number of Honors classes early
entrants complete in their first years in the program (Kuh, 2008).
Data indicating no significant differences between groups of students is also
an encouraging and positive indication of student equity. Since there are no

124
indications that underachievers constitute any particular group, the data results may
be applicable across all groups.
Results indicating a strong relationship between engagement, motivation and
the positive effects of peer tutoring (Butler, 2006), may allow for continued efforts to
enhance opportunities for student engagement including the expansion of the current
peer tutoring program. In addition the relationship between engagement and the
classroom environment provides support for recommendations that peer tutoring be a
structured component of all Honors classes. Because the classroom and motivation
indices were established as predictors of student engagement, continued efforts to
encourage a mastery goal orientation in regard to student attitudes toward learning
may be an excellent method to increasing engagement, which would naturally lead to
increase motivation and achievement. These efforts to encourage a positive goal
orientation and participation in peer tutoring activities may be targeted specifically
toward underachievers.
Deci and Ryan’s (2002) work establishing a link between intrinsic value and
the classroom environment, which was supported by the current research, holds
promise in addressing the current problem. Increasing the intrinsic value of academic
tasks, through the promotion of collaboration for underachievers, may improve their
achievement levels. Also since faculty support for engagement regarding future
career goals is related is related to improved utility value that is also related to
achievement, then promoting the establishment of future goals for underachievers is
a worthwhile objective. Present data establishing student engagement should be

125
specifically aligned with long-term goals to strengthen underachievers’ utility value
for school tasks (Peterson, 2001). High achievers are noted to use self-regulatory
behaviors that enhance motivation, so attention to the development of methods
which increase self-regulation for underachievers is necessary (Ruban & Reis, 2006).
Since current data reveals students’ high levels of motivation, as measured by
mastery goal orientation which is related to self-regulation, then emphasis to
underachievers’ goal orientation/ motivation is a possible solution to performance
problems. In addition, if intrinsic motivational factors are related to peer tutoring
and achievement, especially for female students (Butler, 2006; Bond, 2006), then
efforts should be made to target female underachievers who may benefit from peer
tutoring and learning to teach. It is possible that female underachievers may be
tasked with leading collaborative study groups and peer tutoring to other
underachievers.
Also the relationship between engagement and motivation is encouraging as
it supports the idea that improved motivation leading to increased engagement may
further increase the probability of achievement. Because the current study
instrumentation to measure motivation was the assessment of Mastery Goal
orientation, and such a learning focus may be taught to students, there is the
possibility to increase motivation through increasing the use of a Mastery
Orientation, consequently resulting in increased engagement as supported by the
current study results ( r=.32, p> .01) and, subsequently, increased achievement.

126
Future Research
Future research efforts to explore the effect of the classroom environment on
student achievement should follow a similar quantitative methodology as well as a
corresponding qualitative component. It is suggested that follow-up interviews with
faculty and students could strengthen future research through identifying specific
faculty practices, as related to an adaptive classroom environment. In addition,
student perceptions of the classroom could be used to select those best practices that
may be replicated in other classroom environments. Future research should also
include other student biographical data (Storrs, 2008) including parental
demographics, perceptions and parenting styles.
It will also be advisable to increase the number of test instruments in order to
measure other factors that may be influential in terms of student achievement
including self-regulation and self-efficacy. Additional data on student and parental
personal characteristics such as socio-economic status, and level of education would
be illuminating in terms of addressing achievement issues.
Conclusions
An underperformance problem and research gap involving early entrant
college Honors students prompted the current research. A group of full time early
entrant students participating in an urban university Honors program were surveyed.
Student perceptions of their classroom social environment, motivation and
engagement were assessed in an effort to test for relationships between the variables.

127
Other demographic and student characteristic data was also collected including
achievement indicators, age, gender, college of choice and school experience.
A literature review was completed to inform the current study revealing that
school experience (Storrs, 1995) and the classroom environment (Cigman, 2006) was
important in shaping student perceptions (Patrick, 2005), their expectancies for
success (Eccles & Wigfield, 2000), their task values (Bandura (2002), 2002; Deci &
Ryan,1985; Peterson, 20000) their motivation (Eccles & Wigfield, 2000; Wigfield
and Eccles, 2000; Eklolf, 2006) and their self regulation (Ruban & Reis, 2006). In
addition the positive effect of engagement on various forms of achievement was
established (Noble, 2007; Pollio, 1996; Johnson & Johnson, 2000; Johnson, Johnson
& Stranne, 2006; Butler, 2006; Snidow, 1995; Lin, Lin and Laffey, 2008). The
literature reviewed was framed through a social cognitive theoretical foundation
indicating the importance of student activity on learning (Vygotsky, 1962); the
relationships between the classroom, motivation, engagement and achievement was
established (Patrick, 2005) and used as a framework for the current study. Results
from the current study were varied in relation to the results of previous literature.
While the classroom was not significantly related to either motivation or
achievement it was related to engagement. Because data revealed high levels of
classroom support, motivation and engagement with low variability and no
significant group differences, the absence of a correlation between all three variables
was surprising. Most unusual was the lack of significance in the correlation between
achievement and motivation and engagement. Achievement was, though, related to

128
school experience. The predictive effects of the classroom and motivation on
engagement and the strong relationship between engagement and motivation were
expected and supported previous similar research while also informing implications,
possible future research and the current problem.
Limitations of the present study include weak generalizability to college
Honors students in general, and to the current early entrant underachievers
specifically. Also difficult recruiting efforts, the researchers dual role as Program
Director and the relatively skewed participant characteristics as older students from
predominantly two colleges, may have affected the strength of the research.
Future research efforts should be structured as quantitative studies of the
effects of the classroom environment on motivation, engagement and achievements,
including perceptions of faculty and parents. It would also be helpful to employ
measurements of related factors such as task value, self-regulation, expectancies for
success, SES and self efficacy among others.
The positive effects of the classroom social environment on student
achievement has been established and partially supported by the current research for
a group of early entrant honors students. Results have extended previous literature,
addressed a research gap and provided insight and informed implications on future
actions designed to assist early entrant underachievers. The study also has provided a
framework for similar future studies that may extend and broaden knowledge
regarding early entrant honors students.

129
REFERENCES
Antil L.R., Jenkins J.R, Wayne S. K., & Vadsky, P.F. (1998) Cooperative Learning:
Prevalence, Conceptualizations, and the relation between Research and
Practice. American Educational Research Journal, 35, pp 419-454

Archer, M. (1995). Realist Social Theory: the morphogenetic approach. Cambridge:
Cambridge University Press.

Aronson, E. (2002) The Social Animal. New York: Worth Publishing

Aronson, E., & Thibodeau, R. (1992). The jigsaw classroom: A cooperative strategy
for reducing prejudice. In J. Lynch, C. Modgil, & S. Modgil (Eds.) Cultural
diversity and the schools (Vol. 2, pp. 231-256.) London: Falmer.

Armstrong, W. B., & Demeo, L. (1989). Honors Program Evaluation (Reports-
Evaluative Feasibility (142) ED 313066; JC 890 545). San Diego, California:
Community Colleges, Curriculum Evaluation EDRS.

Atkinson, J. W. (1964) An Introduction to Motivation. New York: American Book-
Van Nostrand-Reinhold.

Axelrod, R.M. (1984). The evolution of cooperation. New York: Basic Books.

Bandura, A. (1986). Social foundations of thought and action: A social cognitive
theory. Englewood Cliffs, N.J.: Prentice-Hall.

Bandura, A. (1989). Self-regulation of motivation and action through internal
standards and goal systems. In L. A. Pervin (Ed.), Goals concepts in
personality and social psychology (pp. 19-85). Hillsdale, NJ: Erlbaum.

Bandura, A., (2002) Social Cognitive Theory in Cultural Context. Applied
Psychology- An International Review. 51 (2) pp. 269-290.

Butler, J., D., (1992) There’s got to be a better way: Alternatives to Lecture and
Discussion. Information Analysis (070) - Viewpoints (Opinion/Position
Papers. Essays, etc.) (120).

Butler, R. (2006). Are mastery and ability goals both adaptive? Evaluation, initial
goal construction and the quality of task engagement. British Journal of
Educational Psychology, 76, 595-611.

130
Bond, R., & Castagnera, E. (2006). Peer Supports and Inclusive Education: An
Underutilized Resource. Theory Into Practice, 45(3), 224-229.

Butler, J. (2002). There's got to be a Better Way: Alternatives to Lecture and
Discussion (ED 396 991; SO 026 559). : Information Analysis - Viewpoints
EDRS.

Bond, L., Butler, H., Thomas, L.,Carlin JH., Glover ZS., Bowes G., ( 2007) Social
and School Connectedness in Early Secondary School as Predictors of Late
Teenage Substance Use, Mental Health, and Academic Outcomes. Journal of
Adolescent Health 40 (4) (2007) Pages 357.e9-357.e18

Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction
in social psychological research: Conceptual, strategic, and statistical
considerations. Journal of Personality and Social Psychology, 51, 1173-1182.

Baumeister, R., F., Dori, G., A., & Hastings S., (1998) Belongingness and Temporal
bracketing In Personal Accounts of Changes in Self-Esteem Journal of
Research in Personality, 32. Pp.222-235.

Callahan, C., Holtman, M. C., Swanson, D. B., Ripkey, D. R., & Case, S. M. (2001).
Factors Associated With Success and Failure - Using Basic Science Subject
Tests to Identify Students at Risk for Failing Step 1. Academic Medicine:
Journal of the Association of American Medical Colleges. 76(10), S48.

Callahan C. (2004). Essential Readings in Gifted Education. Thousand Oaks, Ca.:
Corwin Press.

Callahan, E. H. (2007). The development of norms for a new measure of social
development. Thesis (M.S.)--State University of New York at Binghamton,
Psychology Dept., 2007.
http://proxy.binghamton.edu/login?url=http://wwwlib.umi.com/dissertations/f
ullcit/1459300.

Caraway, K., Tucker, C.M., Reinke, W.M., Hall, C., (2003) Self-efficacy, goal
orientation, and fear of failure as predictors of school engagement in high
school students. Psychology in the Schools, 40. Pp 417-427.

Cigman, R. (2006). The Gifted Child: A Conceptual Inquiry. Oxford Review of
Education, 32(2), 197-212.

Colangelo, N. (2002). Counseling gifted and Talented Students. The National
Research Council on the Gifted and Talented, Fall 2002, 7-10.

131
Colangelo, N., Assouline, S.G., Ihrig, D., Forstadt, L. (2006). Attributional Choices
for Academic Success and Failure by Intellectually Gifted Students. The
Gifted Child Quarterly, 50(4), 283-294,356-357.

Cook-Sather, A. (2007). What Would Happen if We Treated Students as Those with
Opinions That Matter? the Benefits of Supporting Youth Engagement (DOI:
10.1177/0192636507309872). University of California San Diego: NASSP
Bulletin 2007.

Deci, E, & Ryan, R. (1985). Intrinsic motivation and self-determination in human
behavior. New York: Plenum.

Del Court, M. A. (1998). What Parents need to know about Recognizing and
Encouraging Interests, Strengths and Talents of Young Gifted Children?
Office of Educational Research and Improvement, ED 469 853, 2-6.

Dilenbourg, P. (1996). The Evolution of Research on Collaborative Learning. In E
Spada &P Reiman (Eds.), Learning in Humans and the Machine: Towards an
Interdisciplinary Learning Science (pp. 189-211). Geneva: Switzerland.

Dillenbourg, P. (1999). What do you mean by Collaborative Learning? In
P.Dillenbourg (Ed.), Collaborative-learning: Cognitive and Computational
Approaches (pp. 1-16). Geneva: Switzerland.

Dillenbourg, P. (Ed) (1999) Collaborative Learning: Cognitive and Computational
Approaches. Advances in Learning and Instruction Series. Report:
ED437928.

Eccles, J.S., Wigfield, A., Flanagan, C., Miller, C., Reuman, D., & Yee, D. (1989).
Self- concepts, domain values, and self-esteem: Relations and changes at
early adolescence. Journal of Personality, 57, 283-310.

Eccles, J. S., & Wigfield, A. (1995). In the mind of the actor – the structure of
adolescent’s achievement task values and expectancy-related beliefs.
Personality and Social Psychology Bulletin, 21(3), 215-225.

Eccles, J. S., & Wigfield, A. (2000). Expectancy-Value Theory of Achievement
Motivation. Contemporary Educational Psychology, 25(1), 68-81.

Eccles, J. S., Vida, M. N., & Barber, B. (2004). The relation of early adolescents'
college plans and both academic ability and task-value beliefs to subsequent
college enrollment. JOURNAL OF EARLY ADOLESCENCE, 24(1), 63-77.

132
Eccles, J. S., Midgley, C., Wigfield, A., Buchanan, C. M., Reuman, D., Flanagan, C.,
& Mac Iver, D. (1993). Development during adolescence: The impact of
stage environment fit on young adolescents' experiences in schools and in
families. American Psychologist, 48(2), 90-101.

Eilers, A. M., & Camacho, A. (2007). School culture change in the making:
Leadership factors that matter. Urban Education, 42(6), 616-637.

Eklof, H. (2006). Development and validation of scores from an instrument
measuring student test-taking motivation. Educational and Psychological
Measurement, 66(4), 643-656.

Elliott, A. J., & Harackiewicz, J. M., (1996) Approach and Avoidannce Goalsand
Intrinsic Motivation: A Mediational Analysis. Journal of Personality and
Social Psychology. 70, 461-475.

Elliott, A. J., & Church, M.A., (1997) A Hierarchical Model of Approach and
Avoidance Achievement Motivation. Journal of Educational Psychology.
72, 218-232.

Fraser, B.J., & Fisher, D.L. (1982). Predicting Students' Outcomes from Their
Perceptions of Classroom Psychosocial Environment. American Educational
Research Journal, 19(4), 498-518.

Fredrick’s, J.A. (2004) School Engagement: Potential of the Concept. State of the
Evidence Review of educational Research, spring 2004 V 74 No 1 pp 59-109

Ghaith, G.M., Shaaban, K.A., & Harkous, S.A. (2007). An investigation of the
relationship between forms of positive interdependence, social support, and
selected aspects of classroom climate. System, 35(2), 229-240.

Glanville, J.L., & Wildhagen, T. (2007). The measurement of school engagement:
assessing dimensionality and measurement invariance across race and
ethnicity. Educational and Psychological Measurement, 67(6), 1019-1041.

Glanz, J. (2002). Finding Your Leadership Style: A Guide for Educators. Alexandria,
VA: Association for Supervision & Curriculum Development.

Griswold, W. G. (2006). Postsecondary Reading: What Writing Center Tutors Need
to Know. Journal of College Reading and Learning, 37(1), 61-71.

Haugen, R., Ommundsen, Y., Lund, T (2004) The Concept of Expectancy: A Central
personality Dispositions. Educational Psychology 24(1) l

133
Hendriksen, S. I., Love, B., & Hall, M. C. (2005). Assessing Academic Support: the
Effects of Tutoring on Student Learning Outcomes. Journal of College
Reading and Learning, 35(2), 56-65.

Hertzog, N., (2004) Impact of Gifted Programs from the Student’s Perspectives.
Gifted Child Quarterly, 47 (2). Pp. 131-143

Hodges, R., & White, W. G. (2001). Encouraging High-Risk Student Participation in
Tutoring and Supplemental Instruction. Journal of Developmental Education,
24(3), 2-10.

Hughs J., Luo, W., Kwok O., & Loyd, L. (2008) Teacher-Student Support. Effortful,
Engagement and Achievement: A 3-Year Longitudinal Study. Journal of
Educational Psychology, 100 (1) pp1-14.

Johnson, D. W.,,Johnson, R., & Anderson, D., (1983) Social interdependence and
classroom climate. Journal of Psychology, 114, 135-142.

Johnson, D.W, Johnson, R, Ortiz, A, & Stanne, M (1991). Impact of positive goal
and resource interdependence on achievement, interaction, and attitudes.
Journal of General Psychology, 118, 341–347

Johnson, DW, & Johnson, R. (2000). Cooperative learning, values, and culturally
plural classrooms. In Leicester, M, Modgill, C, & Modgill, S (Eds.), Values,
the classroom, and cultural diversity. (p. 15-28). London: Cassell PLC.

Johnson, D.W., Johnson, R.T., & Stanne, M.B. (2000). Cooperative Learning
Methods: A Meta-Analysis. Available in Cooperative Learning Center
website: http://www.clcrc.com/pages/clmethods.html; accessed 17 October
2009.

Johnson, R. & Johnson, D. (2001). What is Cooperative Learning? The Cooperative
Learning Center at the University of Minnesota. http://www.clcrc.com date
of access: 17 October 2009.

Johnson, D. W.; Johnson R., & Roger T. ( 1983) Social interdependence and
perceived academic and personal support in the classroom. The Journal of
Social Psychology. Vol 120(1), Jun 1983, 77-82.

Johnson, R., Johnson, D., & Stanne, M. (1985). Effects of cooperative, competitive,
and individualistic goal structures on computer-assisted instruction. Journal
of Educational Psychology, 77(6). 668-677.

134
Johnson D.W., Johnson R., T., Stanne, M.B., (2000) Cooperative Learning Methods:
A Meta-Analysis. May 2000. University Of Minnesota.

Johnson, D. W., Johnson, R. T., Tiffany, M., & Zaidman, B. (1983). Are low
achievers disliked in a cooperative situation? A test of rival theories in a
mixed ethnic situation. Contemporary Educational Psychology, 8, 189-200.

Kerr, B., Colangelo, N., & Gaeth, J. (1988). Gifted adolescents' attitudes toward their
giftedness. Gifted Child Quarterly, 32(2), 245(3).

King, B.W. & Minium, E.M, (2003). Statistical Reasoning in Psychology and
Education, John Wiley and Sons, Matrix Publishing New Jersey.

Kropotkin, P. (1902). Mutual aid a factor of evolution.

Kuh, G. D., Cruce, T. M., Shoup, R., Kinzie J., Gonyea, R. M. (2008). Unmasking
the Effects of Student Engagement on First-Year College Grades and
Persistence. Journal of Higher Education. 79(5), 540-563.

Letterman, M. R., & Dugan, K. B. (2004). Team Teaching a Cross Disciplinary
Honors Course. College Teaching, 52(2), 76-79.

Lin, Y.M., Lin, G.Y., and Laffey, J. (2008). Building a social and motivational
framework for understanding satisfaction in online learning. Journal of
Educational Computing Research, 38(1):1-27.

Long, B. T. (02, March 29). Attracting the Best: the Use of Honors Programs to
Compete for Students (ED 465 355). Chicago Illinois: Spencer Foundation.

McKean, E. (Ed.). (2008). New Oxford American Dictionary. New York: Oxford
University Press.

Mead (1934/1959) Mind Self and Society: From the Standpoint of a Social
Behaviorist. Chicago: The University of Chicago Press.

Midgley, C., Anderman, E., & Hicks, L. (1995). Differences between elementary and
middle school teachers and students - a goal theory approach. Journal of
Early Adolescence, 15(1), 90-113.

Midgley, C., & Roeser, R. W. (1997). Teachers' Views of Issues Involving Students'
Mental Health. Elementary School Journal, 98(2), 115-133.

135
Midgley, C., Ryan, A. M., & Gheen, M. H. (1998). Why do some students avoid
asking for help? An examination of the interplay among students' academic
efficacy, teachers' social-emotional role, and the classroom goal structure.
Journal of Educational Psychology, 90(3), 528-535.

Midgley, C., Maehr, M., Hicks, L., Roeser, R., Urdan, T., Anderman, E., & Kaplan,
A., Arunkumar, R. & Middleton, M. (1997). Patterns of adaptive learning
survey (PALS). Ann Arbor, MI: University of Michigan.

Midgley, C. , Maehr, M. Hruda, L.Z., Anderman E., Freeman K. E., Gheen M.,
Middleton M. J., Nelson J., Roeser, R., & Urdan, T., ( 2000) Manual for
Patterns of Adaptive Learning Scales. The University of Michigan.

Midgley, C. Kaplan, A., Middleton M., & Maehr, M., The Development and
Validation of Scales Assessing Student’s Achievement Goal Orientations.,
Contemporary Educational Psychology.23, 113-131.

Miron, N., (2008) Miron notes that, “The university has suffered from a self-
proclaimed image problem that affects recruitment of top tier students thus
making its innovative early college entrance program and Honors Program
especially significant to success” (personal communication, July 25, 2008)

Mish, F.C. (Ed.). (2008). Merriam Webster Collegiate Dictionary. New York:
Merriam Webster, Inc.

Motro, A., & Yuan, Q. (1990). Querying Database Knowledge Computer Science
Department University of Southern California.

Neihart, M., Reis, S. M., Robinson, N.M. & Moon, S.M. (2002) The Social and
Emotional Development of Gifted Children: What do we know? Washington
D.C.: National Association for Gifted Students

Noble, Kathleen D., Robert C. Vaughan, Christina Chan, Sarah Childers, Bryan
Chow, Ariel Federow, and Sean Hughes. (2007). "Love and work: the legacy
of early university entrance." Gifted Child Quarterly 51.2. 152(15).

Olsen, D. (2008) Dr. Olsen noted that, “the majority (98%) of enrolled students in
Honors Program Fall through spring class offerings is early entrance to
college students,” (personal communication, June15, 2008).

Ormrod J.E., (2004) Human Learning. Columbus: Pearson. 4th Ed.

136
Palincsar, A.S. (1998). Social constructivist perspective on teaching and learning.
Annual Review of Psychology, 49, 345.

Patrick H., Ryan, A. M (2005) Identifying Adaptive Classrooms: Dimensions of the
Classroom Social Environment. In K.A. Moore & L.H. Lippman (Eds.),
What Do Children Need to Flourish?: Conceptualizing and Measuring
Indicators of Positive Development (pp. 271-287). New York, Springer.

Patrick, H., Bengal, N., and Townsend, M. (2005) Reconsidering the Issue of
Cooperative Learning with Gifted Students. Journal for the Education of the
Gifted 29 (1) pp.90-108

Patrick, H., Ryan, A. M. & Kaplan, A.( 2007) Early Adolescent’s Perceptions of the
Classroom Social Environment, Motivational Beliefs, and Engagement
Journal of Educational Psychology v 99 no. 1pp. 83-98.

Patrick H., Ryan, A. M (2005) Identifying Adaptive Classrooms: Dimensions of the
Classroom Social Environment. In K.A. Moore & L.H. Lippman (Eds.),
What Do Children Need to Flourish?: Conceptualizing and Measuring
Indicators of Positive Development (pp. 271-287). New York, Springer.

Peterson, J.S. (2001). Successful adults who were once adolescent underachievers.
The Gifted Child Quarterly, 45(4), 236-250.

Piaget, J. (1970). Science of education and the psychology of the child. New York:
Orion Press.

Picciano, A.G. (2003). Increasing Student Learning Through Multimedia Projects.
Teachers College Record, 105(4), 690-694.

Pintrich, P.R., Smith, D., Garcia, T., & McKeachie, W.J., (1993). Reliability and
predictive validity of the motivated strategies for learning questionnaire
(MSLQ). Educational and Psychological Measurement, 53(3), 801(13).

Pollio, H. R. (1996, Spring 1996). The Two Cultures of Pedagogy: Teaching and
Learning in the Natural Sciences and the Humanities (Ed 395556, V. 75).
Washington D.C.: U.S Department of Education.

Reis, S., (1998, winter) underachieving for some: Dropping out with Dignity for
others. Communicator 29 (1) pp.19-24.

137
Renzulli, J. S., & Park, S. (2002). Giftedness and High School Drop outs: Personal,
family and School related Factors. Information Analysis Office of
Educational Research and Improvement, December 2002 RM 02168, 3-15.

Rimm, S. B. (1995). Impact of Family Patterns upon the Development of Giftedness:
From J.L. Genshaft (Ed.), Serving Gifted and Talented Students: A Resource
for School Personnel. Austin: Pro-Ed.

Roseth, C. Johnson, D., Johnson R. (2008) Promoting early Adolescent’s
Achievement and Peer Relationships: The Effects of Cooperation.
Competitive and Individualistic Goal Structures. Psychological Bulletin, 134
(2). Pp 223-246

Ruban, L., & Reis, S.M. (2006). Patterns of self-regulatory strategy use among low-
achieving and high-achieving university students. Roeper Review, 28(3),
148(9).

Ryan, A. M., Patrick, H., ( 2001) The Classroom Social Environment and Changes
in Adolescents’ Motivation and Engagement During Middle School.
American Educational Research Journal, Vol. 38, No. 2, 437-460 (2001)

Ryan, A.M., & Patrick, H. (2001). The classroom social environment and changes in
adolescents’ motivation and engagement during middle school. American
Educational Research Journal, 38(2), 437-460.

Patrick, H., Bangel, N.J., Jeon, K.N., Townsend, M.A.R., (2005) Reconsidering the
Issue of Cooperative Learning with Gifted Students. Journal for the
Education of the Gifted, 29(1) pp. 90-108

Santrock, J. W. (2004). Life-span development. Boston: McGraw-Hill Higher
Education.

Santrock, J. W. (2008) Lifespan Development. Dallas: McGraw Hill. Eds

Schunk, D. H., & Zimmerman, B. J. (Eds.). (1998). Self-regulated learning: From
teaching to self-reflective practice. New York: Guilford.

Schunk D. H., Pintrich, P. R. (2008). Motivation in Education: Theory Research and
Education. New Jersey: Pearson. 3rd Ed.

138
Sherman L.W. (1991) Cooperative Learning in Post-Secondary Education:
Implications from Social Psychology for Active Learning Experiences. April
1991. Paper Presented at the Annual Meeting of the American Educational
Research Association. Chicago IL. April 3-7

Silverthorne, U., Thorn, P. M., & Svinicki, M. D. (2006). It's Difficult to change the
way we teach: lessons from the Integrative Themes in Physiology Curriculum
module project. Advances in Physiological Education, 30(DEC), 204-214.

Snidow, P., & Flanagan, M. (1995). The Successful Interdisciplinary Class Must
secede from the Traditional (Research Brief #24). Richmond, Virginia:
Metropolitan Educational Research Consortium.

Storrs, D., & Clott, L. (2007). A Qualitative Study of Honor Students' Learning
Orientations: the Rare Liberal Scholar. College Student Journal, 42(1), 57-69.

Vygotsky, L. S. (1962). Thought and Language (E. V. Hanfmann, G., Trans.).
Cambridge, Mass.: M.I.T. Press.

Wigfield A., Eccles J.S., (2000) Expectancy-Value theory of Achievement
Motivation. Contemporary Educational Psychology, 25. PP. 68-81

Wigfield, A. (1994). The role of children’s achievement values in the self-regulation
of their learning outcomes. In D.H. Schunk & B.J. Zimmerman (Eds.), Self-
Regulation of learning and performance: Issues and educational
applications, (pp. 101-124). Mahwah, NJ: Erlbaum.

Weinsheimer, J. (1998). Providing Effective Tutorial services (Ed 420 267; HE 031
323). Washington, DC: U.S. Department of Education

Zimmerman, B. J., Kitsantas, A., & Cleary, T. (2000). The Role of Observation and
Emulation in the Development of Athletic Self-Regulation. Journal of
Educational Psychology, 92(4), 811.

Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective.
In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-
regulation (pp. 13-39). San Diego: Academic Press.

139
APPENDIX A
HONORS STUDENT STUDY 2008 INSTRUMENTATION
Construct and Items
Class environment Construct
Instructions
Please consider not any one particular class but all classes as a more generalized
response in completion of the survey questions. Choose only one response for each
question.

I. Promoting Interaction

Considering your Honors classes please select the best response 1-5 that reflects your
agreement with the following statements Where 1= not at all true and 5 - very true

1. My teacher often allows us to discuss our work with classmates.
1 2 3 4 5
2. My teacher encourages us to share ideas with one another in class.
1 2 3 4 5
3. My teacher lets us ask other students when we need help with our work.
1 2 3 4 5

Motivational Construct
II. Mastery Goals
Considering your Honors classes please select the best response 1-5 that reflects your
agreement with the following statements

Where 1= not at all true and 5 - very true

1. I like schoolwork that I’ll learn from, even if I make a lot of mistakes.
1 2 3 4 5
2. An important reason I do my schoolwork is because I like to learn
new things.
1 2 3 4 5
3. I like schoolwork work best when it really makes me think.
1 2 3 4 5

140
4. An important reason I do my schoolwork is because I want to improve
my skills.
1 2 3 4 5
5. An important reason I do my schoolwork is because I am interested in it.
1 2 3 4 5
6. An important reason I do my schoolwork is because understanding the work
we do is important to me.
1 2 3 4 5

Engagement Construct
III. Collaboration/ Task-Related Interaction
Considering your Honors classes please select the best response 1-5 that reflects your
agreement with the following statements

Where 1= not at all true and 5 - very true

1. During classes I explain how I work out problems and difficult concepts
to other students.
1 2 3 4 5
2. I help other students with class work when they don’t know what to do.
1 2 3 4 5
3. I collaborate by sharing my ideas and materials with other students in
my classes.
1 2 3 4 5
4. In classes I help other kids learn through collaboration.
1 2 3 4 5
5. I answer questions about coursework in class.
1 2 3 4 5

Demographics
Please fill in the most correct response data for the following nine questions
1. Age _______
2. Gender Male female
3. Entry year of Early Entrance to College _______
4. Total Year(s) at University _______
5. Number of Honors Classes Taken (or in the process of completing) _______
6. Units Completed _______

141
7. Cumulative GPA _______
8. Ethnicity choose the most appropriate response
Caucasian% African-American Hispanic Asian Other
9. Major _______

142
APPENDIX B
CSULA HONORS CLASSES
CSULA Honors Classes
Fall General Education classes
English 101 Composition
Math 102 College Algebra
IHE Introduction to undergraduate study
EEP I Introduction to EEP study

143
APPENDIX C
SCRIPT OF STUDY SOLICITATION
Greetings: My name is Richard S. Maddox and I am a student researcher completing
a dissertation as part of my doctoral work at the University of Southern California
(USC). Some of you who are EEP students also know that I am also a university
administrator. My research involves assessing early entrant Honors student
perceptions of classroom factors that may be associated with student engagement
and motivation. This study will only involve early entrants to college. As early
entrant Honors students I am requesting your participation in this research project.
Only early entrants will be allowed to participate interested students will complete 3
short surveys with a total of only 14 questions. Completing the survey should take
approximately 5 minutes and will be done on-line using www.qualtrics.com.
Students who complete the surveys will be entered into a raffle with one prize not to
exceed $300.00 in value awarded at the completion of the data collection phase.
Students may only participate once in the research project though many of you may
have more than one Honors course this term. Students who are under 18 must give
assent and have their parents give consent. If you are interested in participating
please send an e-mail to me (Note: E-mail address will be posted on the blackboard).
I will reply and attach assent/consent forms that are needed. Once consent is
verified, I will provide you a code and the link to the on-line survey site. When
completed, you will be entered into the raffle. We do not need to collect any ID or
other personal identifying data though you may be asked for permission to link your
identity to one variable (GPA). Participation in the project is entirely voluntary and
will have no effect or bearing on your status as an EEP or CSLA student and you
may withdraw your participation at any time. Data will not be released and will only
be used to answer research questions and meet study objectives. Participation
should be taken seriously as this research is important and meaningful.

Addendum to be sent electronically as the subject description

As a current early entrant your help is sought in completing a research project
designed to assist early entrants, the honors program and to help inform the
research literature on both. Your participation is voluntary; participants will be
included in a raffle for one prize not to exceed $300.00 in value. Participants will
complete a 14-question survey instrument using a secure on-line research service.
Participants will remain anonymous. The estimated completion time is five minutes.

Please read the script below for more details

144
APPENDIX D
CONSENT FORM - ADULT
University of Southern California
Rossier School of Education
Waite Phillips Hall
3470 Trousdale Parkway
Los Angeles, CA 90089
rsoeinfo@usc.edu

INFORMED CONSENT FOR NON-MEDICAL RESEARCH
ADULTS

*******************************************************************
CONSENT TO PARTICIPATE IN RESEARCH

An Examination of classroom Environment on Motivation and Engagement of
College Honors Students

The relationships between the environment, motivation and engagement for early
entrant College Honors students will be investigated.

You are invited to participate in a research study conducted by Richard S. Maddox
M.S. under the direction of faculty advisor Dr Robert Rueda PhD from the Rossier
School of Education at the University of Southern California because you are
currently enrolled as an early college entrant who has taken or are taking university
General Education Honors course(s). The results of this study will be used in a
doctoral dissertation project. You were selected as a possible participant in this study
because you are an early entrant Honors student. A total of 126 subjects ranging in
age from 12 to 20 enrolled in the university will be selected to participate. Your
participation is voluntary. You should read the information below, and ask questions
about anything you do not understand, before deciding whether or not to participate.
Please take as much time as you need to read the consent form. You may also decide
to discuss it with your family or friends. If you agree to participate, you will be asked
to sign this form. You should keep a copy of this form.

145
PURPOSE OF THE STUDY

To understand how the classroom environment affects student motivation and
engagement.

PROCEDURES

You previously sent an e-mail to me expressing an interest in participating. You
have received an e-mail response including a copy of three (3) consent forms with
instructions to thoroughly complete each applicable form, including signatures, and
to return the forms to me. If you volunteer to participate in this study, you will be
asked to complete an online survey. You will not be asked to identify yourself on
the survey. Code numbers will be used to access the survey site. Your email has
been assigned a code and will be retained for a raffle at the conclusion of the study
and then will be destroyed.

Volunteering

Once you have read the consent documents and have decided to participate; you will
be asked to return the applicable form(s) to my campus office (FA 219). You will
then be given the web address and access code to be used accessing a web based
survey site located at www.qualtrics.com: The code has been temporarily linked to
your initial email message for raffle purposes. You will be instructed to log onto the
survey site using the address and access code to complete the survey used in the
study. The survey will include various questions related to your demographic data,
including the following: units completed, college major and cumulative GPA. Your
identity will be anonymous to me.

The survey instruments

The survey contains 14 short questions addressing class environment (teacher
support), motivation (goal orientation) and engagement (collaboration). The three
components will have between 3 and six questions each. You will be asked to rate
your level of agreement (from “not at all true” to “very true”) with question
statements, such as,” I like work that I learn from even if I make a lot of mistakes”
and “I help other students with work when they don’t know what to do” If you have
questions about the survey or the research project, please contact me using the
information at the end of the consent form.

The estimated time for completion is 5 minutes.

146
POTENTIAL RISKS AND DISCOMFORTS

There are only minimal risks associated with completion of this survey related to
possible IT security measures. Though your name will not be collected on the
survey, your IP address may be linked to the web based survey site. The survey site
Qualtrics.com is the preferred research survey site of many U.S. research universities
including USC and is known to maintain appropriate security protections used
against hackers (firewalls, etc.).

POTENTIAL BENEFITS TO SUBJECTS AND/OR TO SOCIETY

You will not directly benefit from your participation. It is hoped that this research
will improve the educational outcomes of early entrant honors students by increasing
the probability of their success, retention and graduation.

PAYMENT/COMPENSATION FOR PARTICIPATION

You will be entered into a raffle for a prize not to exceed $300.00 in value; you will
have an equal chance to win one (1) prize with the winner selected through a random
draw. The drawing is estimated to be held in March 2009, immediately after
completion of the data collection. The winner will be notified by e-mail. The
chances of winning are dependent upon the number of entrants. If 126 subjects enter
into the study, the odds of winning are one in 126. You do not have to complete the
survey in order to be eligible for entry.

POTENTIAL CONFLICTS OF INTEREST

I am also a university administrator working for the Early Entrance Program. I have
no economic interests that would affect my professional judgment. Study results will
not be accessed by any other college administrators and will be used for the purposes
of satisfying my dissertation requirements only. Your eligibility into the honors
program, the Early Entrance Program or any benefits you are entitled to will not be
affected, whether or not you participate in the research study. Questions regarding
conflicts may be addressed to me or my faculty advisor at USC, at Rueda@usc.edu.

CONFIDENTIALITY

Any information that is obtained in connection with this study and that can be
identified with you will remain confidential to the web host and anonymous to me.
Only members of the research team will have access to the data associated with this
study. No one in the college will have access to your individual responses.

147
The data will be stored in my office in a locked file cabinet/password protected
computer. Your identity as a participant will remain confidential. Group or
aggregated data may be released to the chair of the dissertation committee reviewing
the study and to the school administrators at the completion of the study though your
identity as a participant will be anonymous.

The data will be stored for three years after the study has been completed and then
destroyed.

Consent forms will be retained in a secure location separate from the location of data
for three (3) years and thereafter destroyed.

When the results of the research are published or discussed in conferences, no
information will be included that would reveal your identity.

PARTICIPATION AND WITHDRAWAL

You can choose whether to be in this study or not. If you volunteer to be in this
study, you may withdraw at any time without consequences of any kind. You may
also refuse to answer any questions you don’t want to answer and still remain in the
study. I may also withdraw you from this research if circumstances arise which
warrant doing so.

RIGHTS OF RESEARCH SUBJECTS

You may withdraw consent at any time and discontinue participation without
penalty. You are not waiving any legal claims, rights or remedies because of
participation in this research study. If you have any questions about your rights as a
study subject or you would like to speak with someone independent of the research
team to obtain answers to questions about the research, or in the event the research
staff can not be reached, please contact the University Park USC IRB, Office of the
Vice Provost for Research Advancement, Stonier Hall, Room 224a, Los Angeles,
CA 90089-1146, (213) 821-5272 or upirb@usc.edu and or the Director of Research
Development in the Office of Research and Development at CSULA 323-343-3798.

IDENTIFICATION OF INVESTIGATORS

If you have any questions or concerns about the research, please feel free to contact
Richard S. Maddox, 323-343-2287 Early Entrance Program 5151 State University
Drive, KH 3104 Dept of Psychology Los Angeles, California, 90032 , Dr. Robert
Rueda 323-740-9323 USC 3470 Trousdale Parkway Los Angeles, CA 90089 WPH
802 Rossier School of Education, or CSULA campus sponsor Dr. Nadine Koch, 323-
343-3830.

148

SIGNATURE OF SUBJECT

I have read (or someone has read to me) the information provided above. I have
been given a chance to ask questions. My questions have been answered to my
satisfaction, and I agree to participate in this study. I have been given a copy of this
form.

Name of Subject

Signature of Subject Date

SIGNATURE OF INVESTIGATOR

I have explained the research to the subject and answered all of their questions. I
believe that the subject freely consents to participate.

Name of Investigator

Signature of Investigator Date

THIS PROJECT HAS BEEN REVIEWED BY THE CALIFORNIA STATE
UNIVERSITY, LOS ANGELES INSTITUTIONAL REVIEW BOARD FOR THE
PROTECTION OF HUMAN SUBJECTS IN RESEARCH. ADDITIONAL
CONCERNS AND COMPLAINTS, OR QUESTIONS REGARDING YOUR
RIGHTS AS A RESEARCH PARTICIPANT, SHOULD BE DIRECTED TO THE
DIRECTOR OF RESEARCH DEVELOPMENT (323-343-3798).

149
APPENDIX E
CONSENT FORM - PARENT
University of Southern California
Rossier School of Education
Waite Phillips Hall
3470 Trousdale Parkway
Los Angeles, CA 90089
rsoeinfo@usc.edu

INFORMED CONSENT FOR NON-MEDICAL RESEARCH
PARENTAL PERMISSION

*******************************************************************
CONSENT TO PARTICIPATE IN RESEARCH

An Examination of classroom Environment on Motivation and Engagement of
College Honors Students

The relationships between the environment, motivation and engagement for early
entrant College Honors students will be investigated.

Your child is invited to participate in a research study conducted by Richard S.
Maddox MS under the direction of faculty advisor Dr Robert Rueda PhD from the
Rossier School of Education at the University of Southern California because your
child is currently enrolled as an early college entrant who has taken university
General Education Honors courses. The results of this study will be used in a
doctoral dissertation project. Your child was selected as a possible participant in this
study because s/he is an early entrant Honors student. A total of 126 subjects ranging
in age from 12 to 20 enrolled in the university will be selected to participate. Your
child’s participation is voluntary. You should read the information below, and ask
questions about anything you do not understand, before deciding whether or not to
allow your child to participate. Please take as much time as you need to read the
consent form. You and/or your child may also decide to discuss it with your family
or friends. If you allow your child to participate, you will be asked to sign this form.
You should keep a copy of this form. Even if you allow your child to participate,
your child will also be asked his/her permission and be given an Assent Form to
review and sign, if s/he decides to participate. Your child can decide not to

150
participate, even if you agree to allow him/her to participate and will be provided an
Assent form for his/her approval and signature.

PURPOSE OF THE STUDY

To discover how the classroom environment may affect student motivation and
engagement.

PROCEDURES

Your child previously sent an e-mail to me expressing an interest in participating.
Your child has received an e-mail response including a copy of three (3) parent
consent forms and student assent forms, with instructions to thoroughly review and
complete each applicable form, including signatures. Students under 18 years of age
must provide their parents with a copy of the parent consent form for their review.
If you allow your child to volunteer to participate in this study, and your child agrees
to participate, he/she will be asked to complete an online survey. His/her e-mail has
been assigned a code and will be retained for a raffle at the conclusion of the study
and then will be destroyed. Your child will not be asked to identify him/herself on
the survey. Code numbers will be used to access the survey site.

Volunteering
You should review this form carefully. Once you have read the consent document,
and have given your permission to allow your child to participate, please give the
signed document to your child. If your student chooses to participate he/she will
sign the student assent form and return both the parent consent and student assent
forms to my campus office (FA 218). Upon submission of the parent consent form,
your child will be asked to submit the assent form that has been read and signed by
him/her, if s/he agrees to participate.

Your child will then be given a code and web address that will allow him/her to
access the web based survey site at www.qualtrics.com. The code has been
temporarily linked to your child’s initial email message for raffle purposes. Your
child will be instructed to log onto the survey site using the address and code and to
complete the survey used in the study. The survey will include various questions
related to student demographic data, including units completed, college major and
cumulative GPA. Your child’s identity will be anonymous to me.

The survey instruments
The survey contains 14 short questions addressing class environment (teacher
support), motivation (goal orientation) and engagement (collaboration). The three

151
components will have between 3 and six questions each. Students will be asked to
rate their level of agreement (from “not at all true” to “very true”) with question
statements, such as,” I like work that I learn from even if I make a lot of mistakes”
and “I help other students with work when they don’t know what to do.” If you
would like to see the questions asked of your child, please contact me using the
information at the end of the consent form.

The estimated time for completion is 5 minutes.

POTENTIAL RISKS AND DISCOMFORTS

There are only minimal risks associated with completion of this survey related to
website security. Though your child’s name will not be collected on the survey, your
child’s IP address may be linked to the web based survey site. The survey site
Qualtrics.com is the preferred research survey site of many U.S research universities
including USC and is known to maintain appropriate security protections used
against hackers (firewalls etc.).

POTENTIAL BENEFITS TO SUBJECTS AND/OR TO SOCIETY

Your child will not directly benefit from his/her participation. It is hoped that this
research will improve the educational outcomes of early entrant honors students by
increasing the probability of their success, retention and graduation.

PAYMENT/COMPENSATION FOR PARTICIPATION

Students will be entered into a raffle for a prize not to exceed $300.00 in value; all
participants will have an equal chance to win one (1) prize with the winner selected
through a random draw. The drawing will be made in March 2009 immediately after
the data is collected. The winners will be notified by e-mail. The chances of winning
are dependent upon the number of entrants. If 126 subjects enter into the study, the
odds of winning are one in 126. Your child does not have to complete the survey in
order to be eligible for entry.

POTENTIAL CONFLICTS OF INTEREST

I am also a University administrator working for the Early Entrance Program; I have
no economic interests that would affect my professional judgment. Study results will
not be accessed by any other college administrators without participant and parental
permission and will be used for the purposes of satisfying my dissertation
requirements only. Your student’s eligibility into the honors program, the Early
Entrance Program or any benefits he/she is entitled to will not be affected, whether
or not he/she participates in the research study.

152
CONFIDENTIALITY

Any information that is obtained in connection with this study and that can be
identified with you or your child will remain confidential to the web host and
anonymous to me.

Only members of the research team will have access to the individual data associated
with this study. You will not have access to your child’s responses.

The data will be stored in my office in a locked file cabinet/password protected
computer. Your child’s identity will remain confidential.

Consent and Assent forms will be retained in a secure location separate from the
location of data for three (3) years and thereafter destroyed.

The group or aggregated data may be released to the chair of the dissertation
committee reviewing the study and to the school administrators.

The data will be stored for three years after the study has been completed and then
destroyed.

When the results of the research are published or discussed in conferences, no
information will be included that would reveal your child’s identity.

PARTICIPATION AND WITHDRAWAL

Your child can choose whether to be in this study or not. If your child volunteers to
be in this study, s/he may withdraw at any time without consequences of any kind.
Your child may also refuse to answer any questions they don’t want to answer and
still remain in the study. I may also withdraw your child from the research if
circumstances arise which warrant doing so.

RIGHTS OF RESEARCH SUBJECTS

You or your child may withdraw assent or consent at any time and discontinue
participation without penalty. You and your child are not waiving any legal claims,
rights or remedies because of participation in this research study. If you have any
questions about your rights and/or your child’s rights as a study subject, or you
would like to speak with someone independent of the research team to obtain
answers to questions about the research, or in the event the research staff can not be
reached, please contact the University Park USC IRB, Office of the Vice Provost for
Research Advancement, Stonier Hall, Room 224a, Los Angeles, CA 90089-1146,

153
(213) 821-5272 or upirb@usc.edu and or the Director of Research Development at
CSULA 323-343-3798.

IDENTIFICATION OF INVESTIGATORS

If you have any questions or concerns about the research, please feel free to contact
Richard S. Maddox M.S, 323-343-2287 Early Entrance Program 5151 State
University Drive, KH 3104 Dept of Psychology Los Angeles, California, 90032 and
faculty advisor Dr Robert Rueda 323-740-9323 USC 3470 Trousdale Parkway Los
Angeles, CA 90089 WPH 802 Rossier School of Education, or CSULA campus
sponsor Dr. Nadine Koch, 323-343-xxxx.

SIGNATURE OF PARENT(S)

I/we have read (or someone has read to me) the information provided above. I/we
have been given a chance to ask questions. My/our questions have been answered to
my/our satisfaction, and I/we agree to have our child participate in this study. I/we
have been given a copy of this form.

Name of Subject

Name of Parent

Signature of Parent Date

SIGNATURE OF INVESTIGATOR

I have explained the research to the subject and his/her parent(s), and answered all of
their questions. I believe that the parent(s) freely consents to allow his/her child to
participate.

Name of Investigator

Signature of Investigator Date

154
THIS PROJECT HAS BEEN REVIEWED BY THE CALIFORNIA STATE
UNIVERSITY, LOS ANGELES INSTITUTIONAL REVIEW BOARD FOR THE
PROTECTION OF HUMAN SUBJECTS IN RESEARCH. ADDITIONAL
CONCERNS AND COMPLAINTS, OR QUESTIONS REGARDING YOUR
RIGHTS AS A RESEARCH PARTICIPANT, SHOULD BE DIRECTED TO THE
DIRECTOR OF RESEARCH DEVELOPMENT (323-343-3798).

155
APPENDIX F
CONSENT FORM - YOUTH
University of Southern California
Rossier School of Education
Waite Phillips Hall
3470 Trousdale Parkway
Los Angeles, CA 90089
rsoeinfo@usc.edu

INFORMED ASSENT FOR NON-MEDICAL RESEARCH
FOR YOUTH (AGES 12-17)

*******************************************************************
ASSENT TO PARTICIPATE IN RESEARCH
An Examination of classroom Environment on Motivation and Engagement of
College Honors Students

The relationships between the environment, motivation and engagement for
traditional and early entrant College Honors students.

You are asked to participate in a research study conducted by Richard S. Maddox
M.S. under the direction of faculty advisor Dr Robert Rueda PhD from the Rossier
School of Education at the University of Southern California because you are
currently enrolled as an early college entrant who is taking university General
Education Honors courses. The results of this study will be used in a doctoral
dissertation project. You were selected as a possible participant in this study because
you are an early entrant Honors student. A total of 126 subjects ranging in age from
12 to 20 enrolled in the university will be selected to participate. Your participation
is voluntary. You should read the information below, and ask questions about
anything you do not understand, before deciding whether or not to participate. Please
take as much time as you need to read the assent form. You may also decide to
discuss it with your family or friends. If you decide to participate, your parent’s
permission will also be required. However, the final decision to participate is yours;
even if your parents agree to allow you to participate, you can decide not to. You
will be asked to sign this form. You will be given a copy of this form to keep. Your
eligibility into the honors program, the Early Entrance Program or any benefits you

156
are entitled to will not be affected, whether or not you participate in the research
study.

PURPOSE OF THE STUDY

To understand how the classroom environment affects student motivation and
engagement.

PROCEDURES

You previously sent an e-mail to me expressing an interest in participating. You
have received an e-mail response including a copy of three (3) consent forms and
assent forms with instructions to thoroughly complete each applicable form,
including signatures, and to return the forms to my campus office (FA 218). If you
volunteer to participate in this study, you will be asked to complete an online survey.
Your e-mail has been assigned a code and will be retained for a raffle at the
conclusion of the study and then will be destroyed. You will not be asked to identify
yourself on the survey. Code numbers will be used to access the survey site. Your
parent consent form will be collected before your assent form.

Volunteering

Upon submission of your parent’s consent and your assent forms, you will be given
the code and web address to be used accessing a web based survey site at
www.qualtrics.com. The code has been temporarily linked to your initial email
message for raffle purposes. You will be instructed to log onto the survey site using
the address and access code, and to complete the survey used in the study. The
survey will include various questions related to student demographic data including:
units completed, college major and cumulative GPA. Your identity will be
anonymous to me.

The survey instruments

There survey contains 14 short questions addressing class environment (teacher
support), motivation (goal orientation) and engagement (collaboration). The three
components will have between 3 and six questions each. You will be asked to rate
your level of agreement (from “not at all true” to “very true”) with question
statements, such as,” I like work that I learn from even if I make a lot of mistakes”
and “I help other students with work when they don’t know what to do” If your
parents would like to see the questions asked of you, they can contact me using the
information at the end of the consent form.

The estimated time for completion is 5 minutes.

157
POTENTIAL RISKS AND DISCOMFORTS

There are only minimal risks associated with completion of this survey related to
website security. Though your name will not be collected on the survey, your IP
address may be linked to the web based survey site. The survey site Qualtrics.com is
the preferred research survey site of many U.S research universities including USC
and is known to maintain appropriate security protections used against hackers
(firewalls etc.).

POTENTIAL BENEFITS TO SUBJECTS AND/OR TO SOCIETY

You will not directly benefit from your participation. It is hoped that this research
will improve the educational outcomes of early entrant honors students by increasing
the probability of their success, retention and graduation.

PAYMENT/COMPENSATION FOR PARTICIPATION

You will be entered into a raffle for a prize not to exceed $300.00 in value; you will
have an equal chance to win one (1) prize with the winner selected through a random
draw. The drawing is estimated to be held in March 2009, immediately after
completion of the data collection. The winner will be notified by e-mail. The
chances of winning are dependent upon the number of entrants. If 126 subjects enter
into the study, the odds of winning are one in 126. You do not have to complete the
survey in order to be eligible for entry.

POTENTIAL CONFLICTS OF INTEREST

I am also a University administrator working for the Early Entrance Program; I have
no economic interests that would affect my professional judgment. Study results will
not be accessed by any other college administrators and will be used for the purposes
of satisfying my dissertation requirements only. Your eligibility into the honors
program, the Early Entrance Program or any benefits you are entitled to will not be
affected, whether or not you participate in the research study.

CONFIDENTIALITY

Any information that is obtained in connection with this study and that can be
identified with you will remain confidential to the web host and anonymous to me.

Only members of the research team will have access to the data associated with this
study. No one in the college will have access to your individual responses.

158
The data will be stored in my office in a locked file cabinet/password protected
computer. Your identity as a participant will remain confidential.

Consent and Assent forms will be retained in a secure location separate from the
location of data for three (3) years and thereafter destroyed.

The group or aggregated data may be released to the chair of the dissertation
committee reviewing the study.

The data will be stored for three years after the study has been completed and then
destroyed.

When the results of the research are published or discussed in conferences, no
information will be included that would reveal your identity.

PARTICIPATION AND WITHDRAWAL

You can choose whether to be in this study or not. If you volunteer to be in this
study, you may withdraw at any time without consequences of any kind. You may
also refuse to answer any questions you don’t want to answer and still remain in the
study. I may withdraw you from this research if circumstances arise which warrant
doing so.

RIGHTS OF RESEARCH SUBJECTS

You may withdraw your assent at any time and discontinue participation without
penalty. You are not waiving any legal claims, rights or remedies because of your
participation in this research study. If you have any questions about your rights as a
study subject or you would like to speak with someone independent of the research
team to obtain answers to questions about the research, or in the event the research
staff can not be reached, please contact the University Park USC IRB, Office of the
Vice Provost for Research Advancement, Stonier Hall, Room 224a, Los Angeles,
CA 90089-1146, (213) 821-5272 or upirb@usc.edu and/or the Director of Research
Development in the Office of Research Development at CSULA 323-343-3798.

IDENTIFICATION OF INVESTIGATORS

If you have any questions or concerns about the research, please feel free to contact
Richard S. Maddox, 323-343-2287 CSULA Early Entrance Program 5151 State
University Drive, KH 3104 Dept of Psychology Los Angeles, California, 90032 and
Dr Robert Rueda 323-740-9323 USC 3470 Trousdale Parkway Los Angeles, CA
90089 WPH 802 Rossier School of Education, or CSULA campus sponsor Dr.
Nadine Koch, 323-343-3830.

159

SIGNATURE OF RESEARCH SUBJECT

I have read (or someone has read to me) the information provided above. I have
been given a chance to ask questions. My questions have been answered to my
satisfaction, and I agree to participate in this study. I have been given a copy of this
form.

Name of Subject

Signature of Subject Date

SIGNATURE OF INVESTIGATOR

I have explained the research to the subject and answered all of his/her questions. I
believe that he/she freely consents to participate.

Name of Investigator

Signature of Investigator Date

THIS PROJECT HAS BEEN REVIEWED BY THE CALIFORNIA STATE
UNIVERSITY, LOS ANGELES INSTITUTIONAL REVIEW BOARD FOR THE
PROTECTION OF HUMAN SUBJECTS IN RESEARCH. ADDITIONAL
CONCERNS AND COMPLAINTS, OR QUESTIONS REGARDING YOUR
RIGHTS AS A RESEARCH PARTICIPANT, SHOULD BE DIRECTED TO THE
DIRECTOR OF RESEARCH DEVELOPMENT (323-343-3798).

160
APPENDIX G
ADJUSTED SURVEY INSTRUMENT
Patrick (2007) measurement of task-related interaction
Original Instrument
Task-Related Interaction
Considering your math class please select the best response1-5 that reflects your
agreement with the following statements

1. During math class I explain how I work out math problems to other kids.
2. I help other kids with math when they don’t know what to do.
3. I share my ideas and materials with other kids in math.
4. In math class I help other kids learn.
5. I answer questions about math in class. (a)
Bold terms are deleted or revised in the current study Maddox (2008)
Maddox (2008) revised measurement of task –related interaction as collaboration
Collaboration/ Task-Related Interaction

Considering your Honors classes please select the best response1-5 that reflects your
agreement with the following statements

Where 1= not at all true and 5 - very true
1. During classes I explain how I work out problems and difficult concepts
to other students.
1 2 3 4 5

2. I help other students with class work when they don’t know what to do.
1 2 3 4 5

161
3. I collaborate by sharing my ideas and materials with other students in
my Honors classes.
1 2 3 4 5

4. In classes I help other students learn through collaboration.
1 2 3 4 5

5. I answer questions about coursework in Honors classes.
1 2 3 4 5

Bold terms are additions and or revised for the current study

Abstract (if available)

Abstract This study set out to examine the relationships between the classroom social environment, motivation, engagement and achievement of a group of early entrant Honors students at a large urban university. Prior research on the classroom environment, motivation, engagement and high ability students was examined, leading to the assumption that the classroom environment was linked to student achievement. Early entrant students (n= 65) were surveyed to determine their perceptions of the classroom environment and their levels of motivation, engagement and achievement. An instructor support for engagement scale (Ryan & Patrick 2001) was used as an indicator of classroom environment. A goal orientation scale measuring mastery orientation, adapted from the Patterns of Adaptive Learning Survey (PALS

Linked assets

University of Southern California Dissertations and Theses

Conceptually similar

PDF

Exploring student motivations toward civic engagement: an application of expectancy-value theory

PDF

Exploring the promise of multicultural literature: a case study exploring the impact of the use of mulitucultural literature on the engagement of students from diverse backgrounds

PDF

Latino parental aspirations and literacy practices related to children's reading engagement

PDF

Factors influencing nursing students' motivation to succeed

PDF

Children's motivation to engage in physical activity during recess

PDF

Parental involvement and student motivation: A quantitative study of the relationship between student goal orientation and student perceptions of parental involvement among 5th grade students

PDF

Examining the relationship between Latinx community college STEM students’ self-efficacy, social capital, academic engagement and their academic success

PDF

Enacting ideology: an examination of the connections between teacher ideology, classroom climate, and teacher interpretation of student behavior

PDF

The relationship between teacher assessment practices, student goal orientation, and student engagement in elementary mathematics

PDF

A quantitative analysis on student goal orientation and student perceptions of parental involvement among 6th grade middle school students

PDF

Examining presence as an influence on learning engagement

PDF

The relationship of a culturally relevant and responsive learning environment to achievement motivation for Native Hawaiian secondary students

PDF

Problem-based learning and its influence on college preparation knowledge, motivation, & self-efficacy in high school students

PDF

Goal orientation of Latino English language learners: the relationship between students’ engagement, achievement and teachers’ instructional practices in mathematics

PDF

Familial and cultural variables as predictors of retention of Latino engineering students

PDF

Investigating how general education middle school teachers support the social inclusion of students with special needs

PDF

Improving instructor skills (IIS): a Needs analysis

PDF

The spill over effect: an examination of differentiated curriculum designs in a heterogeneous classroom

PDF

Promising practices in preventing bullying in K-12 schools: student engagement

PDF

School-wide implementation of the elements of effective classroom instruction: lesson from a high performing high poverty urban elementary school

Asset Metadata

Creator Maddox, Richard S. (author)

Core Title An examination of classroom social environment on motivation and engagement of college early entrant honors students

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 02/26/2010

Defense Date 12/11/2009

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag classroom social environment,engagement,gifted students,Motivation,OAI-PMH Harvest

Place Name California (states), Los Angeles (city or populated place)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Rueda, Robert S. (committee chair), Olsen, David (committee member), Ragusa, Gisele (committee member)

Creator Email rmaddox@cslanet.calstatela.edu,rsmaddox@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m2858

Unique identifier UC1219764

Identifier etd-Maddox-3500 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-292915 (legacy record id),usctheses-m2858 (legacy record id)

Legacy Identifier etd-Maddox-3500.pdf

Dmrecord 292915

Document Type Dissertation

Rights Maddox, Richard S.

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu