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Community college students in STEM: a quantitative study investigating the academic beliefs of students enrolled in online and on campus information technology courses

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Community college students in STEM: a quantitative study investigating the academic beliefs of students enrolled in online and on campus information technology courses

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Content Running head: COMMUNITY COLLEGE STUDENTS IN STEM 1

COMMUNITY COLLEGE STUDENTS IN STEM: A QUANTITATIVE STUDY
INVESTIGATING THE ACADEMIC BELIEFS OF STUDENTS ENROLLED IN ONLINE
AND ON CAMPUS INFORMATION TECHNOLOGY COURSES

by

Nooshin Valizadeh

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 2015

Copyright 2015 Nooshin Valizadeh
COMMUNITY COLLEGE STUDENTS IN STEM 2

Table of Contents
List of Tables 4

Abstract 5

Chapter One: Overview Of The Study 6

Introduction 6

Background of the Problem 7

Statement of the Problem 10

Purpose of the Study 10

Research Questions 10

Significance of the Study 11

Methodology 11

Definition of Terms 12

Organization of the Study 13

Chapter Two: Literature Review 14

Online Learning 15

Benefits of Online Learning 17

Challenges to Online Learning 19

Online Course Retention Strategies 20

Summary 21

Underrepresented Minority Students in STEM 22

Help-Seeking 23

Self-Efficacy 26

Intrinsic and Extrinsic Goal Orientation 32

Extrinsic Goal Orientation 33

Conclusion 34

Chapter Three: Methodology 36

Research Questions 36

Research Design 37

Population and Sample 37

Instrumentation 38

Demographic Information 38

Help-Seeking Beliefs 41

Intrinsic and Extrinsic Goal Orientation 42

Procedure and Data Collection 43

Data Analysis 43

Chapter Four: Results 46

Descriptive Statistics 46

Analysis of Results 47

Research Question 1 47

Research Question 3 49

Chapter Five: Discussion 52

Discussion of Student Demographic Composition 52

Discussion of Self-Efficacy Across Ethnicity 54

Discussion of Self-Efficacy, Goal Orientation and Help-Seeking Beliefs 56

Implications 58

COMMUNITY COLLEGE STUDENTS IN STEM 3

Recommendations for Future Research 61

Limitations 62

Conclusion 63

References 66

Appendix A: Demographic Questions 75

Appendix B: Help-Seeking Beliefs 77

Appendix C: Self-Efficacy Beliefs 78

Appendix D: Intrinsic and Extrinsic Goal Orientation 79

COMMUNITY COLLEGE STUDENTS IN STEM 4

List of Tables
Table 1: Participant Demographics: Age 39

Table 2: Participant Demographics: Ethnicity 40

Table 3: Data Analysis 45

Table 4: Means, Standard Deviations, and Pearson Product Correlations of
Measured Variables 47

COMMUNITY COLLEGE STUDENTS IN STEM 5

Abstract
In order to compete with the global economy and workforce, and to prevent the rise of
outsourcing careers in science, technology, engineering, and mathematics (STEM) to other
countries, the U.S. needs to develop professionals in STEM fields (Hurtado, Cabrera, Lin,
Arellano & Espinosa, 2009; PCAST, 2012). This study examined whether there was a difference
in academic beliefs such as self-efficacy, help-seeking and intrinsic and extrinsic goal orientation
for community college students taking an introductory information technology course in online
versus on-campus learning settings. Underrepresented Minority (URM) student self-efficacy
beliefs were also investigated and compared with those of their White and Asian counterparts.
Findings showed online students in this study to have lower levels of help-seeking, self-efficacy
and intrinsic goal orientation than those of on-campus students. This study also found URM
students to have greater intrinsic motivation than did their White and Asian counterparts and no
difference in their other academic beliefs.

COMMUNITY COLLEGE STUDENTS IN STEM 6

CHAPTER ONE: OVERVIEW OF THE STUDY
Introduction
In order to compete with the global economy and workforce, and to prevent the rise of
outsourcing careers in science, technology, engineering, and mathematics (STEM) to other
countries, the U.S. needs to develop professionals in STEM fields (Hurtado, Cabrera, Lin,
Arellano & Espinosa, 2009; President’s Council of Advisors on Science and Technology
[PCAST], 2012). Chen’s (2013) research presented disturbingly high STEM degree dropout rates
at the community college level for White students and even higher rates for underrepresented
minority (URM) students. The data showed 77.8% of Black students and 77.5% of Hispanic
students who intended to pursue a STEM degree failed to do so, compared to 66.1% of White
students. With fewer than 40% of the undergraduate student population who intended to choose a
STEM major obtaining a degree, PCAST (2012) recommends strategies to increase STEM
undergraduate degree completion by 34% to support the needed increase of 1 million STEM
professionals (Hurtado et al., 2009). Furthermore, with the significant increase in the number of
URM students entering college, it is imperative that higher education institutions recruit and
retain these students towards STEM pathways so that they may contribute to filling the need for
more STEM professionals (Hurtado et al., 2009). A STEM degree not only fulfills the nation’s
need but also opens a vast array of promising professional opportunities for URM students in the
fastest growing fields.
In addition, student enrollment in online courses steadily increased over the past decade
with a compound annual growth rate of 16.1% for online student enrollment from 1.6 million
students taking at least one online course during the fall 2002 semester to 7.1 million during the
Fall 2012 semester (Allen & Seaman, 2014). Studies assert that tight budgets led institutions to
COMMUNITY COLLEGE STUDENTS IN STEM 7

implement online learning. In fact, approximately 66% of surveyed chief academic officers
believe that a crucial element of their institution’s long-term strategy is online education (Allen
& Seaman, 2014). The strategy of increasing online education is not only beneficial for
institutions from a financial standpoint, but also for student flexibility and accessibility. Allen
and Seaman (2014) stated that, in 2012, more than one-third of all college students took online
classes, a significant percentage increase since 2002 when it was less than 10%. Brown’s (2012)
study unearthed that one key reason for the growth is the level of flexibility and accessibility
non-traditional college students have with online courses, as many face work and family
obligations that stop them from regularly attending face-to-face classes. As online learning
becomes more prevalent in higher education settings, it is important to examine the degree to
which STEM major retention and degree completion can be achieved in both online and on-
campus learning environments.
Background of the Problem
There is a plethora of studies conducted at higher education institutions with regard to
access and retention in the STEM fields (Bensimon, 2004). Many of these studies led to a
number of different strategies for STEM talent development, especially in regard to URM
students (Hurtado et al., 2009; Winston et al., 2010). In 2010, about one in three White freshmen,
one in three African American freshmen, one in three Latino freshmen, and one in two Asian
American freshmen reported plans to pursue a STEM major (National Science Board [NSB]
2012). While the percentages of first-year African American and Latino students intending to
pursue a STEM major are similar to those of Whites, only 29% of these students graduate with a
STEM degree by the 6
th
year, compared to 42% of Whites, indicating a significant gap (NSB
2006; Winston et al., 2010).
COMMUNITY COLLEGE STUDENTS IN STEM 8

Within the STEM major, the “T” for technology has represented a significant variety of
majors and careers in the last two decades. Parallel to the emergence of the Internet in the mid-
1990s, information technology-related majors (IT) such as engineering technology, computer
engineering, computer science and business information systems peaked for undergraduate
students and increased enrollments at higher education institutions (Zhang, 2007). Unfortunately,
the dotcom bubble burst caused IT enrollments to decline in the mid-2000s. This led to great
concern that the United States may lose its global superiority in the IT industry as other countries
graduate students in IT-related majors at a higher rate (Zhang, 2007). Studies asserted that, while
job availability and genuine interests in IT fields exist, student self-efficacy and overall academic
experiences and settings can be contributing factors that discourage students from choosing an
IT-related major (Zhang, 2007).
Much of the research pertaining to what may be considered a positive climate for URM
STEM students looked at self-efficacy and positive attitudes about science and technology (Ong
et al., 2011; Winston et al., 2010). Studies showed that African Americans pursuing STEM
majors at Historically Black Colleges and Universities (HBCUs) often experience positive
climates that include high expectations for academic achievement in the STEM major, openness
towards alternative directions into the major, lack of stigmas attached to remedial coursework,
and encouraging, fruitful relationships between students and faculty (Ong et al., 2011; Winston
et al., 2010). In these positive environments, there has been greater assistance in increasing
retention for URM students in STEM, where those who did not initially intend on choosing a
STEM major would consequentially have the academic confidence and encouragement to do so
(Ong et al., 2011; Winston et al., 2010).
COMMUNITY COLLEGE STUDENTS IN STEM 9

Community colleges offer a setting and environment that attracts a variety of diverse
students seeking postsecondary education (American Association of Community
Colleges, 2011). In 2001, community colleges enrolled 43% of first-time freshman
undergraduate students, 44% of African American students and 52% of Latino students in the
United States (American Association of Community Colleges, 2011). In addition, many
community colleges now offer online course delivery formats to help increase enrollments and
provide their diverse student body the flexibility and self-paced aspects of online learning (Al-
Asfour & Bryant, 2011; Griffin & Rankine, 2010). The multiple delivery formats of courses,
especially STEM and, particularly, IT courses, position community colleges to cater to a large
population of diverse students and may assist in leading them towards IT and STEM majors and
career pathways.
Along with the increase of technological advancements nationwide such as the Internet
and mobile phones, online education drastically increased as well due to its affordability and
accessibility from virtually any location. (Al-Asfour & Bryant, 2011; Pascarella & Terenzini,
1998; Tiger & Preston, 2013). In 2002, 1.6 million students reported taking at least one online
course. By 2012, 7.1 million students reported taking at least one online course, pushing the
online higher education course enrollment percentage to the highest percentage yet at 33.5%
(Allen & Seaman, 2014). As a result, higher education institutions have increased their
incorporation of online courses into their curriculum. As of 2012, over 86% of all higher
education institutions offer online courses, and 62.4% offer complete online programs (Allen &
Seaman, 2013). With the prevalence of online learning in higher education settings and the
increasing demand for STEM professionals in the U.S., it is important to examine the
COMMUNITY COLLEGE STUDENTS IN STEM 10

development of key academic student success-related beliefs such as help-seeking, self-efficacy
and intrinsic and extrinsic motivation in both online and on-campus STEM course environments.
Statement of the Problem
There is a lack of research that compares academic beliefs such as self-efficacy, help-seeking
and intrinsic and extrinsic goal orientation of students taking online and on-campus STEM
courses. Research analyzing these factors with regard to URM students is further limited. While
there are studies that examine the self-efficacy of URM students taking STEM courses, it is
important to examine information technology courses specifically, since they are rapidly growing
and include a broad spectrum of professional opportunities (Ong et al., 2011; Winston et al.,
2010).
Purpose of the Study
The purpose of this study was to determine whether there was a difference in academic
beliefs such as self-efficacy, help-seeking and intrinsic and extrinsic goal orientation for
community college students taking a STEM-track course in online versus on-campus learning
settings. Of special focus for this study were URM students taking an introductory information
technology course at a large community college in Southern California.
Research Questions
1. Is there a difference in the level of self-efficacy of URM students in comparison
to other students?
2. Is there a difference in student self-efficacy and goal orientation by course
delivery method?
3. Is there a difference in student help-seeking beliefs by course delivery method?
COMMUNITY COLLEGE STUDENTS IN STEM 11

4. Is there a relationship between self-efficacy, goal orientation and help-seeking
beliefs, controlling for course delivery method?
Significance of the Study
Since higher education institutions are crucial in recruiting and retaining STEM student
majors, efforts must be made to improve the first two years of STEM education by providing all
college students with the tools needed to develop into high-skilled STEM professionals (PCAST,
2012). With the steady increase of online courses, this study aimed to investigate whether this
delivery mode supports or compromises the development of important academic beliefs of
students taking a STEM course. In addition, this study intended to unearth the levels of STEM
course-related self-efficacy of URM students in comparison with their counterparts, so that
suggestions to improve STEM talent development for URM students can be made as appropriate.
Methodology
In order to effectively investigate relationships among academic beliefs and examine the
statistical differences of those beliefs in both online and on-campus settings, this study employed
a quantitative approach. The quantitative approach entailed administering surveys to both online
and on-campus students taking an introductory technology course at a large community college
in southern California. The valid and reliable instruments used in this study included a portion of
Karabenick’s (2003) questionnaire and several portions of the Motivated Strategies for Learning
Questionnaire (MSLQ) (Pintrich, Smith, Garcia & McKeachie, 1991). Demographic questions
were also included in the survey, and all data was analyzed through the Statistical Package for
the Social Sciences (SPSS) using appropriate statistical tests.
COMMUNITY COLLEGE STUDENTS IN STEM 12

Definition of Terms
Online courses. Online courses are courses in which there are typically no face-to-face
meetings and at least 80% of the content is delivered online (Allen & Seaman, 2014). Online
courses can be delivered in two formats: synchronous and asynchronous.
Asynchronous. The asynchronous structure allows for learners to progress at their own
pace with no set meeting time.
Synchronous. The synchronous structure requires students to virtually connect with their
instructors and classmates at scheduled meeting times (Griffin & Rankine, 2010).
Help-seeking. Academic help-seeking is an adaptive learning strategy that involves
interpersonal relationships developed through social interactions between students and their
instructors (Newman, 2000). Instrumental, executive, formal and informal help-seeking will be
specifically discussed in Chapter Two.
Self-efficacy. Self-efficacy refers to an individual’s internal beliefs in his or her ability to
complete a specific task (Bandura, 1997).
Intrinsic goal orientation. Intrinsic goal orientation in learners refers to their genuine
interest in the learning process and their desire to increase their knowledge in the course material
(Dweck & Leggett, 1988).
Extrinsic goal orientation. Extrinsic goal orientation relates to a learner’s engagement
for external reasons such as to expose his/her capabilities to others, outperform their peers, or
receive external successes such as rewards and appraisal.
STEM. The acronym for professions and areas of study in science, technology,
engineering and mathematics is “STEM” (Winston et al., 2010).
COMMUNITY COLLEGE STUDENTS IN STEM 13

Organization of the Study
Chapter One in this study provides an introduction to the topic of STEM fields, online
education and the theoretical frameworks that were analyzed in this study. In addition, an
overview of the proposed study is given along with the research questions, purpose and
significance of the study. This section also discusses potential limitations, and presents
definitions of relevant terms.
Chapter Two provides a thorough synopsis of STEM education and student retention in
STEM, especially with regard to URM students. The chapter also delivers an in-depth overview
of online education and its benefits and challenges to students and institutions. Academic beliefs
such as help-seeking, self-efficacy and intrinsic and extrinsic goal orientation are also be
examined in this chapter.
Chapter Three describes the methodology used in this study. The sample used,
instrumentation, research design, data collection and data analysis will also be offered in this
chapter.
Chapter Four is a description of the results from the data analysis. The results are further
discussed in Chapter Five along with the limitations of the study, implications and
recommendations for future research.
COMMUNITY COLLEGE STUDENTS IN STEM 14

CHAPTER TWO: LITERATURE REVIEW
The purpose of this chapter is to provide an overview of the current state of
postsecondary education in STEM fields. It also provides a comprehensive overview of the
literature concerning online education, a mode of delivery where more and more STEM
education is taking place. This chapter provides a discussion of self-efficacy and help-seeking
beliefs, and closes with a brief discussion of the concept of individual interest. It is vital to
examine these three factors that promote student academic success. Given the critical
importance of effective education in the STEM fields, and the growth of online education,
research to study the intersection of success factors in online science education is clearly needed.
In this study, levels of self-efficacy for URM students enrolled in a STEM course were
investigated and compared to those of their White and Asian peers. Furthermore, the self-
efficacy, help-seeking and intrinsic and extrinsic goal orientation factors of a 100% online STEM
course were compared to those of the exact course taught 100% on campus. This study also
investigated whether there was a relationship among self-efficacy, goal orientation and help-
seeking beliefs within the two different delivery methods.
The STEM degree completion of students who intended to major in a STEM field upon
entering a higher education institution is less than 40%, and only approximately 300,000
bachelor and associate degrees are awarded annually in STEM fields (PCAST, 2012). There are
a variety factors that contribute to the low STEM retention rates. Some students who possess the
skills and preparation needed to succeed in a STEM major report they switched majors as a result
of being uninspired by the introductory required courses (PCAST, 2012). Other students who do
not necessarily have the academic preparedness for the introductory courses may struggle with
the course content and material and report that the lack of academic support at their institution
COMMUNITY COLLEGE STUDENTS IN STEM 15

led to their withdrawal (PCAST, 2012). URM students majoring in STEM have shown
significantly lower degree completion rates and higher STEM course dropout rates in their first
and second years compared to URM non-STEM majoring students, which indicates that
introductory STEM courses are critical in URM STEM major retention and degree attainment
(Salto et al., 2014).
In February 2012, PCAST released a report to provide strategies that could help improve
the challenges and advantages students face in STEM education pathways during their initial two
years at a higher education institution. The report states that the first two years at both 2- and 4-
year higher education institutions are the most crucial in recruiting and retaining STEM student
majors, and provides detailed action plans on how to “improve the first two years of STEM
education in college, provide all students with the tools to excel, and diversify pathways to
STEM degrees” (PCAST, 2012, p. 2). PCAST’s (2012) recommendations and action plans are
intended to develop skillful students and produce STEM professionals who will be able to
contribute to America’s needed competitive workforce in the near future. With the rapid growth
of online courses at higher education institutions and the steady increase of online learners, these
action plans can be applied to a large population of diverse learners who will benefit from the
country’s efforts in STEM talent development (Al-Asfour & Bryant, 2011; PCAST, 2012;
Pascarella & Terenzini, 1998).
Online Learning
Historically, all instruction at American higher education institutions was delivered face-
to-face with instructors and students physically present in a classroom (Lucas, 1994). With
technological progressions such as visual media, many instructors began incorporating these
advancements into their educational materials by delivering their content through videos and
COMMUNITY COLLEGE STUDENTS IN STEM 16

audio recordings (Bernard, Abrami, Borokhovski, Wade, Tamim, Surkes, et al. 2009). These
advancements later led to the Internet, which is now accessible to over 30% of the world’s
population (Internet World Stats, 2014). Consequently, most of today’s students in U.S. higher
education institutions utilize technology such as mobile phones, social media and e-mail in their
everyday lives. This is one reason online education has drastically increased in taking the place
of former face-to-face interaction nationwide (Al-Asfour & Bryant, 2011; Pascarella &
Terenzini, 1998; Tiger & Preston, 2013). It is especially appealing to students due to its
affordability and accessibility from virtually any location. While Astin’s (1984) theory states that
the student’s place of residence on campus is crucial to positive student outcomes and
persistence, some researchers may argue that this is not entirely necessary or practical for online
learners (Al-Asfour & Bryant, 2011). Conversely, other research showed that student persistence
rates for online learners nationwide are significantly lower than the rates of students taught in a
traditional format (McEwen & Gueldenzoph, 2003). This section begins with a detailed
description of online learning. Next, benefits and challenges of online learning are discussed.
Finally, retention strategies that researchers have suggested with regard to online learning will be
disclosed.
Online learners are steadily increasing every year. Allen and Seaman (2014) displayed
that, during the fall term of 2012, 7.1 million students were enrolled in at least one online course.
This number exceeds the prior year by over 400,000. In addition, student enrollment in online
courses has steadily increased over the past decade with an average compound growth rate of
16.1% for online student enrollment from 2002 to 2012 (Allen & Seaman, 2014). While many
higher education institutions still deliver their course content in the traditional, oral and written
format with no online technology, others also utilize a variety of technological formats: Web-
COMMUNITY COLLEGE STUDENTS IN STEM 17

Facilitated, Hybrid and Online, with over 33% of the student population taking at least one
online course.
Web-Facilitated courses operate as face-to-face courses through a web-based technology
such as web pages or course management systems (Allen & Seaman, 2014). This format
supplements its traditional content delivery with an online component ranging from 1 to 29%.
Hybrid courses combine face-to-face content delivery with a significant online portion ranging
from 30 to 79% (Allen & Seaman, 2014). Online discussions and group forums typically take the
place of the limited face-to-face meetings. This format allows for student engagement
opportunities in multiple learning settings (Delialioğlu, 2012). Online courses are courses in
which there are typically no face-to-face meetings and at least 80% of the content is delivered
online (Allen & Seaman, 2014). Al-Asfour and Bryant (2011) define online education as “a
method of instruction that allows students to use the Internet as a means of providing education
regardless of where they are located” (p. 43). Online courses can be delivered in two formats:
synchronous and asynchronous. The asynchronous structure allows for learners to progress at
their own pace with no set meeting time, while the synchronous structure requires students to
virtually connect with their instructors and classmates at scheduled meeting times (Griffin &
Rankine, 2010). Evidence of both the benefits and challenges of online learning will be shown in
the following sections.
Benefits of Online Learning
There are several benefits to online learning for both students and institutions. Students
report satisfaction with the flexibility and self-paced aspects of online learning while institutions
benefit from an increase in enrollments and demand for online courses.
COMMUNITY COLLEGE STUDENTS IN STEM 18

Benefits to students. Studies illustrate many advantages of online learning for students
in terms of flexibility, transportation and self-paced coursework.
Studies report that flexibility in online learning is a significant predictor of student
satisfaction (Ozkan, Koseler & Baykal, 2009). Al-Asfour and Bryant’s (2011) study illustrated
high satisfaction from all of the students who expressed that online courses enabled them to
balance their responsibilities. The flexibility to be able to work full time and tend to their
children while in school also assisted in the persistence of these online learners (Al-Asfour &
Bryant, 2011; Ozkan, Koseler & Baykal, 2009).
Many students who wish to pursue higher education do not have access to a vehicle or
convenient public transportation, and are, therefore, unable to participate in the traditional format
of face-to-face education (Al-Asfour & Bryant, 2011). Online education alleviates this issue, as
the student can access his or her course remotely from any location. In addition, students who
live in areas with hostile weather conditions do not miss classes due to weather conditions
prohibiting them from safely traveling to their institution (Al-Asfour & Bryant, 2011).
Astin’s (1984) Theory of Student Involvement allows for educational leaders,
administrators and staff to measure how they motivate their students to be involved instead of
solely focusing on their own teaching techniques. It is centered on the amount of time, energy
and motivation a student invests in his or her collegiate experience. In a traditional format, the
classes revolve around the time and schedule of the instructor. With online learning, however,
students have control over where and when to study based on their own needs (Al-Asfour &
Bryant, 2011). Students often find that this advantage enables them to increase their reflective
thinking for optimal online classroom participation, resulting in a deeper learning experience and
COMMUNITY COLLEGE STUDENTS IN STEM 19

higher academic gains (Brown, 2012; Chen, Lambert & Guidry, 2010; Rabe-Hemp, Woollen &
Humiston, 2009).
Benefits to institutions. Studies show evidence that negative economic conditions can be
positive for online program enrollments in higher education institutions (Allen & Seaman, 2013).
Educational leaders at a wide variety of institutions report a growing demand for online courses
each year (Allen & Seaman, 2014). One reason may be that the decrease in employment
opportunities results in people’s pursuing higher education, and an online education is a feasible
option while they search for work. Another reason may be that current employees believe they
may increase their chances of career advancement by obtaining a degree and feel that an online
program can provide them with better work-life balance than the traditional format (Brown,
2012; Chen, Lambert & Guidry, 2010; Rabe-Hemp, Woollen & Humiston, 2009).
Challenges to Online Learning
While there are several benefits to online learning, studies demonstrate many challenges
as well. These challenges include self-regulation issues for students and retention challenges for
institutions.
Although it was discussed earlier that the flexibility of online education is beneficial to
the student learner, reports also disclose that a lack of self-regulation and increased
procrastination are prevalent for many online learners, as they may not be equipped with the
appropriate time management skills necessary to succeed in an online educational setting (Al-
Asfour & Bryant, 2011). In addition, remote access leaves many online learners feeling isolated
since they do not have the classroom environment to establish fruitful relationships with their
classmates and instructors (Ozkan, Koseler & Baykal, 2009).
COMMUNITY COLLEGE STUDENTS IN STEM 20

One major challenge for institutions that provide online courses is student persistence.
Student persistence rates for online learners nationwide are significantly lower than the rates of
students taught in a traditional format. In addition, student dropout rates in online courses far
exceed those of face-to-face courses (McEwen & Gueldenzoph, 2003). One factor may be
attributed to the negative perceptions many instructors have of online education, which can have
an impact on student learning (Chen, Lambert & Guidry, 2010). Many instructors believe that
online courses require more of their time than do traditional courses and are ineffective in
producing positive student learning outcomes (Allen & Seaman, 2014; Rabe-Hemp et al., 2009).
With the growing demand of online courses and the increase of enrollments, administrators
search for strategies to assist with these issues and assist in the retention of their online students.
Online Course Retention Strategies
Surveys have shown that in 2012, 41 percent of chief academic officers believe that it is
more difficult to retain students enrolled in online courses than those enrolled on campus (Allen
& Seaman, 2014). Researchers often point to Tinto’s (1974) and Astin’s (1984) theories when
suggesting strategies to increase student retention in online programs. Tinto’s (1975) Student
Retention Theory suggests that creating a sense of community contributes to a student’s sense of
belonging in their higher education setting. He asserts that students’ sense of academic and social
integration is established when students are committed to their educational goals and to their
institution. Without this sense of integration, students are at risk for dropping out. Astin (1984)
further states that a student’s energy must be invested in both the academic and social structures
of his or her college experience in order to be deeply involved in the learning process (Astin,
1984; Hunt, 2003). Academic and social integration of online students, along with the investment
of their energy and involvement, are discussed in relation to the results of this survey.
COMMUNITY COLLEGE STUDENTS IN STEM 21

Allen and Seaman (2014) presented reports that, in 2013, 77.3% of chief academic
officers believed that the amount of discipline needed for the success of online students is far
greater than that for on-campus students. Studies suggest that frequent and detailed instruction
from faculty about course assignments and goals is imperative for enhancing student learning
and encouraging interaction (McEwen & Gueldenzoph, 2003). Mass communication and group
e-mails are effective strategies to make general announcements of assignment details. Software
such as Blackboard and eCollege are essential for student-to-student and student-to-instructor
communication (McEwen & Gueldenzoph, 2003). Researchers (Cole & Griffin, 2013; Hunt,
2003) suggest that engaging students in and out of the virtual classroom with consistent office
hours and technological forms of communication such as e-mail and course websites can foster a
mentoring relationship with their students, encourage active participation among peers, and
motivate students to become more involved in their collegiate experience. Constructive criticism
and feedback can also motivate students to persist in their academic studies towards success.
These experiences often lead to positive outcomes such as increased student persistence and
higher grade point averages (GPAs) (Cole & Espinoza, 2008; Cole & Griffin, 2013).
Instructional content and the structure of that information are the two components that
assist in student learning (Clark, Yates, Early, & Moulton, 2008). It is suggested that the online
instructor’s perspective must shift from providing knowledge and content to facilitating learning.
This shift can challenge online learners to reflect and communicate their own thoughts rather
than what they were instructed to think (McEwen & Gueldenzoph, 2003).
Summary
There are a variety of technological formats in which higher education institutions
currently deliver their course content. Online learning enabled an increase in higher education
COMMUNITY COLLEGE STUDENTS IN STEM 22

enrollment and access for a large population of students (Brown, 2010). Benefits of online
learning include flexibility for students and an increase in enrollment for institutions (Al-Asfour
& Bryant, 2011; Ozkan, Koseler & Baykal, 2009). Challenges entail self-regulation issues and
low retention rates (Al-Asfour & Bryant, 2011; McEwen & Gueldenzoph, 2003; Ozkan, Koseler
& Baykal, 2009). Technological forms of involvement such as faculty communication and peer
interaction where students can feel connected to a learning community may help to improve
retention rates for online learners (Ozkan, Koseler & Baykal, 2009). Further research could lead
to effective practices that administrators and faculty can implement to help encourage a social
construct resulting in positive outcomes for non-traditional learners (Astin, 1984; Hunt, 2003;
McEwen & Gueldenzoph, 2003; Ozkan, Koseler & Baykal, 2009). In the next few sections,
factors that influence student success-related beliefs such as help-seeking, self-efficacy and
intrinsic and extrinsic motivation in both online and on-campus formats are examined.
Underrepresented Minority Students in STEM
URM individuals represented 31.1% of the total population of the United States in 2010.
However, they only earned 13.1% of all STEM doctorates in the same year (Salto et al., 2014).
While female students and students of color currently represent approximately 70% of the
college population, they only account for approximately 45% of undergraduate STEM degrees
awarded (annually PCAST, 2012). Chen’s (2013) research revealed that, of 13,000 students in a
six-year longitudinal study, over 65% of African American students who had originally enrolled
in a STEM major did not graduate with a STEM degree. Many URM students point to factors
such as negative racial climates and discriminatory interactions with peers and faculty members
that steered them away from their intended STEM major (Cole & Espinoza, 2008; Winston et al.,
2010).
COMMUNITY COLLEGE STUDENTS IN STEM 23

This study was conducted at a southern California community college because of the
diverse student body enrollment that exists in most community colleges (American Association
of Community Colleges, 2011). Hurtado, Milem, Clayton-Pederson, and Allen’s (1998)
breakdown of campus climate included the following four scopes: the inclusion or exclusion of
diverse racial groups as historically present at an institution; the existence of structural diversity
of diverse groups as a numerical representation; the psychological environment of perceptions
between and among racial groups; and the behavioral climate as characterized by campus
relationships within groups (Cole & Espinoza, 2008). It is expected that Hurtado et al.’s (1998)
second scope of racial climate that includes URM representation will provide insight regarding
whether differences in the academic beliefs of URM students exist in comparison to their White
and Asian counterparts when they are surrounded by a diverse student body. Studies have shown
that STEM talent development can be progressive at community colleges because of the
comfortable social interrelationships that often exist among diverse students in these settings
(Jackson, 2013). Examining the academic beliefs of both URM community college students and
their White and Asian counterparts in an introductory STEM course may lead to implications
that community college STEM faculty and administrators can use for their online and on-campus
courses to improve STEM retention and degree attainment.
Help-Seeking
Help-seeking beliefs have been studied in a variety of settings, such as cooperative-
learning groups, communities of practice, in teachers, in organizational settings and in diverse
cultures (Karabenick, 2011; Nistor, Schworm & Werner, 2012). Academic help-seeking is an
adaptive learning strategy that involves interpersonal relationships developed through social
interactions between students and their instructors (Newman, 2000). Help-seeking was initially
COMMUNITY COLLEGE STUDENTS IN STEM 24

viewed as a negative concept by both students and faculty and was often assumed to signify the
incompetence, dependence and immaturity of the learner (Newman, 2000). Current research,
however, indicates that learners who exhibit help-seeking beliefs such as tracking their academic
progress, displaying awareness that they cannot overcome a challenge, and demonstrating the
ability to conquer that challenge by seeking help from an instructor or peer, have a competent,
strategic and mature approach to their learning (Karabenick, 2003; Karabenick, 2011; Newman,
2000; Nistor, Schworm & Werner, 2012). Help-seeking beliefs can be categorized into the
following forms: instrumental, executive, formal and informal. This section defines and
discusses these varying forms along with the benefits and challenges of help-seeking beliefs.
Instrumental help-seeking beliefs refer to students pursuing their instructors and peers for
guidance, which has been noted to assist in student learning and understanding (Karabenick,
2011). Students who exhibit instrumental help-seeking beliefs may request hints or tips for their
assignments so that they may independently learn through their own efforts (Karabenick, 2003).
Substantial evidence affirmed that motivated and self-regulated learners are more likely to seek
instrumental, adaptive help as an effective learning strategy than executive help-seeking
(Karabenick, 2003; Karabenick, 2011).
Executive help-seeking refers to students who often seek direct answers to avoid doing
work or to achieve a high grade (Karabenick, 2003). Unlike instrumental help-seeking, which is
perceived by researchers to be a more autonomous strategy, executive help-seeking can be
attributed to dependency for the learner (Karabenick, 2003). While it can result in positive
performance outcomes, it does not provide the optimal strategy for learning (Cheng, Liang, &
Tsai, 2013; Karabenick, 2003).
COMMUNITY COLLEGE STUDENTS IN STEM 25

Formal help-seeking belief refers to students who pursue assistance from formal
academic sources such as their instructors, teaching assistants and course materials like articles
and websites that were required or recommended by their instructors (Karabenick, 2011).
Conversely, informal help-seeking beliefs relate to students who search for academic assistance
through sources such as their peers and non-academic individuals (Karabenick, 2003). Studies
show that formal help-seeking is closely related to instrumental help-seeking, where students
who seek help to learn and understand course material are more likely to ask their instructors
than other students (Karabenick, 2003). While formal help-seeking results in a higher probability
of accurate information, studies demonstrate that it is not as common as informal help-seeking,
especially when students face challenges in their academics (Karabenick, 2003; Karabenick,
2011).
Benefits to help-seeking. Studies assert that help-seeking is an important strategy of self-
regulated learning (Karabenick, 2003; Newman, 2000). Help-seeking benefits learners because it
encourages knowledge sharing and helps them to focus on their academic tasks at hand,
minimize their possibility of failure and maximize the chances of learners gaining mastery and
autonomy in the future (Newman, 2000; Nistor, Schworm & Werner, 2012).
Information and communication technologies (ICT) assist in the continual rise in help-
seeking beliefs (Karabenick, 2011). Karabenick (2011) argues that help-seeking, whether in a
classroom or online setting, is a social and interactive strategy. Studies showed that help
delivered by ICT systems doubled the rate of help-seeking in comparison to the same
information delivered by an instructor or peer (Karabenick, 2011). ICT has been found to be
beneficial for learning gains and can encourage students to seek help during web-based inquiry
learning, especially in structured settings (Karabenick, 2011).
COMMUNITY COLLEGE STUDENTS IN STEM 26

Challenges to help-seeking. The action of seeking help can be a challenge for a large
number of students, as studies assert that they often feel vulnerable and embarrassed at the
presence of their peers and instructors when requesting academic assistance (Cheng et al., 2013;
Karabenick 2011). These challenges can result in lower academic ambitions and a lack of
persistence, especially with regard to URM students in STEM courses (Cole & Griffin, 2013;
Kitsantas & Chow, 2007).
Large classrooms that hold hundreds of students have been shown to be a challenge for
help-seeking learners and can often affect their being proactive in seeking help (Karabenick,
2003). Formal help-seeking beliefs are specifically low when learners perceive that their
instructors are unavailable due to the size of the classroom. However, the perception that
students are anonymous in the class due to its size can also increase their chances of seeking
help, especially when instructors clearly state that they are available for help (Karabenick, 2003).
Help-seeking is critical to student success and achievement in all majors, especially STEM. It is
important to study how students seek help in STEM classes and whether there are difference in
help-seeking beliefs between online and on-campus learning settings.
Self-Efficacy
According to Albert Bandura (1995), self-efficacy is “the belief in one’s capabilities to
organize and execute the courses of action required to manage prospective situations” (Bandura,
1995, p. 2). It is the perception a person has of his or her abilities to accomplish a task
successfully and it creates a foundation for an individual’s motivation (Bandura, 1995; Pajares,
2006). This section reviews the different levels and sources of self-efficacy for learners, and the
impact they have on student performance, persistence and engagement, especially with regard to
URM students in STEM courses and majors.
COMMUNITY COLLEGE STUDENTS IN STEM 27

Academic self-efficacy. High academic self-efficacy applies to learners who have an
internal belief in their capabilities to perform and succeed in academic tasks (Bandura, 1995;
Pajares, 2006). Studies found that the self-efficacy beliefs of students contributed not only to
their academic performance but also to their engagement in non-academic activities in which
they feel competent (Pajares, 2006). Students with a high level of self-efficacy often exhibit self-
regulatory learning beliefs, and their memory performance tends to improve as their motivation
and persistence increases (Pajares, 2006). Raelin et al. (2014) assert that self-efficacy can be
assessed and enhanced during a student’s first year. With regard to online learning, students who
have high self-efficacy beliefs in their abilities to use a computer and the various technological
tools needed for academic success exhibit positive learning efforts and outcomes in their online
courses (Bates & Khasawneh, 2007; Wang, Shannon, & Ross, 2013). In pursuing STEM majors,
studies show that students with high self-efficacy display a higher level of academic persistence
and achievement in their major (Cheng & Lee, 2009; Pajares, 2006; Raelin, et al., 2014).
Students with high levels of self-efficacy display greater levels of optimism, persistence and
academic achievements and lower levels of anxiety, especially when facing adversity (Pajares,
2006). Since STEM fields experience a high rate of attrition, it is critical to study the
development of students’ self-efficacy.
Students who are not confident in their abilities to succeed academically have low levels
of self-efficacy (Bandura, 1993; Pajares, 2006). They may exhibit maladaptive academic
tendencies, avoidance of courses and careers, and a lack of academic motivation and
achievement. Some common results of these tendencies include depression, anxiety, stress and
giving up when facing adversity (Pajares, 2006). Studies assert that low levels of self-efficacy
COMMUNITY COLLEGE STUDENTS IN STEM 28

are great contributors to the disengagement and lack of persistence of URM students in STEM
courses and majors (Bandura, 1993; Pajares, 2006; Cole & Griffin, 2013).
Sources of self-efficacy. A student’s previous accomplishments, failures, observations
and forms of persuasion often determine their level of self-efficacy (Bandura, 1986; Pajares
2006). Mastery experiences, social modeling, social persuasion and psychological responses are
four major sources that develop into a learner’s self-efficacy. Mastery experiences, which refer
to the learner performing an academic task well, have the most dominant effect on self-efficacy
beliefs (Bandura, 1977, 1993, 1995; Pajares, 2006). As a result of success in a previous academic
task, learners often gain a high level of self-efficacy and are likely to approach the next task with
confidence and put forth their best efforts for success (Bandura, 1977, 1993, 1995; Pajares,
2006). As a result of success in a previous academic task, learners often gain a high level of self-
efficacy).
Social modeling can influence a student’s self-efficacy positively or negatively, as the
learner may develop beliefs about his/her own academic abilities through observing the
experiences of their peers (Bandura, 1977, 1993, 1995; Pajares, 2006). When peers successfully
complete academic tasks and perform well, learners may attribute the experience to their own
success and elevate their self-efficacy. Consequently, observing failure from their peers can also
influence a student to believe they, too, will not persevere at a similar task (Bandura, 1977, 1995;
Pajares, 2006).
Social persuasion such as verbal feedback can persuade learners to believe that they hold
the skills and capabilities needed for their academic success. Positive encouragement and
feedback from instructors and peers can help to conquer academic insecurities and shift the
student’s focus to putting forth his/her best effort (Bandura, 1977, 1995; Cole & Griffin, 2013;
COMMUNITY COLLEGE STUDENTS IN STEM 29

Pajares, 2006). Alternatively, negative persuasions and appraisals can weaken a student’s self-
efficacy, which is easier than strengthening a person’s self-efficacy with positive persuasion
(Pajares, 2006).
A learner’s health, emotional state and stress levels can also affect his or her self-efficacy
(Bandura, 1977, 1995). For example, a positive psychological, physical or emotional response
such as feeling relaxed before giving a classroom presentation can heighten the student’s self-
efficacy to give a successful presentation. Feelings of depression or anxiety can weaken their
confidence to succeed. Self-efficacy beliefs are a crucial foundation for student motivation and
academic success in STEM courses, especially with regard to URM students (Bandura, 1977,
1995; Pajares, 2006;Winston et al., 2010). Since student self-efficacy beliefs can relate to their
motivation and perseverance, it is important to examine self-efficacy through multiple lenses that
can determine whether self-efficacy beliefs predict help-seeking beliefs in STEM courses,
parallel the differences in self-efficacy levels of STEM students in on-campus and online
settings, and compare the self-efficacy belief levels of URM students with their White and Asian
counterparts (Pajares, 2006).
Self-efficacy of URM STEM students. Since this study investigated the levels of self-
efficacy for URM students enrolled in a STEM course, it is important to discuss the available
literature on this topic. Many student satisfaction surveys suggest that low levels of self-efficacy
correlate with the low persistence of URM STEM students (Gusa, 2010). With regard to the four
sources of self-efficacy listed earlier, common factors affecting the self-efficacy of these students
include negative racial climates on campus and a lack of role models and faculty of color (Gusa,
2010; Palmer, Maramba, & Dancy, 2011; Seymour & Hewitt, 1997). A national survey of
African American engineering undergraduates conducted by Brown, Morning, and Watkins in
COMMUNITY COLLEGE STUDENTS IN STEM 30

2005 (as cited by Winston et. al., 2010) correlated the decreased graduation rates with significant
racism and negative campus and classroom climates encompassed by interfaces with faculty,
staff and peers. Rankin and Reason’s (2005) study discovered that URM students reported unfair
treatment from their faculty members and peer students, and considered their campus racial
climate less favorable than did the institution’s White students. Common examples of negative
interactions include URM STEM student inputs rejected in a study group when a similar
contribution by a White or male classmate is affirmed, and professors in core courses showing a
lack of interest in and support for URM students (Cole & Griffin, 2013; Stern, 2008; Winston et
al., 2010). These interactions suggest perceptions that students of color are limited in their
intellectual competence for STEM success. The internalization of these perceptions can debilitate
URM student academic self-efficacy and can lead them to change majors or even drop out of the
institution (Winston et al., 2010).
Extensive research and laboratory experiments confirm the inverse relationship between
stereotype threat and performance of URM students, especially in the case of first-year students
(Iverson, 2007; Winston et al., 2010). According to the National Longitudinal Survey of
Freshmen (NLSF), URM students who internalized the negative stereotypes studied less and
became gradually disengaged from academics as any foundational representation of their
identity, resulting in lower grades by the end of their second year (Winston et al., 2010). A
negative racial climate and atmosphere can, consequently, contribute to a broken overall identity
image and disempowerment as a STEM student (Cheng & Lee, 2009; Connor, 2009).
Marginalization and a sense of invisibility caused by the negative racial climate can affect the
URM student’s sense of self, leading to internalized oppression and compromising his/her
COMMUNITY COLLEGE STUDENTS IN STEM 31

interests and motivations to pursue his/her academic ambitions (Blumenfield, 2006; Cheng &
Lee, 2009; Johnson, 2006; Winston et al., 2010).
Self-efficacy is a person’s perceptions about his or her abilities to think, feel and act in
order to achieve a desired outcome (Bandura, 1997). HBCUs tend to provide what are considered
supportive environments that are conducive to the self-efficacy and academic achievement of
their students (Winston et al., 2010). Palmer, Davis, Ryan, and Maramba, (2010) conducted a
study investigating the experiences and persistence to graduation of eleven Black males at a
public HBCU who were enrolled through the school’s developmental studies program. This
developmental program was not only academics-based, but also provided a variety of personal
and leadership development. Eight of the eleven participants suggested that this program
contributed to their success for a variety of reasons, including social and academic integration
and connection to university faculty and personnel. Many participants credited faculty
encouragement and motivation for their self-efficacy to persist and succeed. Another study at a
HBCU that involved Black engineering undergraduates reported greater positive math and
science-related academic and social support experiences (Lent, Brown, Sheu, Schmidt, Brenner,
Gloster, Wilkins, Schmidt, Lyons, Treistman, 2005). Cole and Espinoza’s (2008) study showed
cultural congruity and faculty support contributed positively to the academic successes of Latino
STEM students. In these affirmative environments, there has been greater assistance in
increasing retention for African Americans in STEM, where those who did not initially intend on
choosing a STEM major would consequentially have the academic self-efficacy and
encouragement to do so.
The faculty and mentors at HBCUs support Bandura’s (as cited by Smith, Allen, Johnson,
Dickson, Najee-ullah, Peters, 2008) social cognitive theory that people learn and repeat the
COMMUNITY COLLEGE STUDENTS IN STEM 32

beliefs of their role models, which can be crucial for their self-efficacy. Since the self-efficacy
levels of URM students in the STEM subjects and majors can be such a great contributor to their
STEM persistence, this study examined how their levels compared with those of their peers in an
introductory IT course. The next section analyzes the intrinsic and extrinsic goal orientation
construct as it relates to students’ success in STEM majors and fields.
Intrinsic and Extrinsic Goal Orientation
Student intentions to succeed academically are learning goals, and they help to guide and
motivate academic beliefs (Dweck, 1986; Dweck & Leggett, 1988). Among the possible goals
learners may have are subject mastery, internal satisfaction through achievement, approval and
recognition, failure avoidance, specialized skill attainment, peer outperformance and social
network negativity avoidance (Dweck, 1986; Dweck & Leggett, 1988; Pintrich, 2000a). The
motivational tendencies of learners are often referred to as intrinsic and extrinsic goal
orientation, which will be discussed in the next two sections.
Intrinsic goal orientation. Intrinsic goal orientation in learners refers to their genuine
interest in the learning process and their desire to increase their knowledge in the course material
(Dweck & Leggett, 1988). Intrinsic goal-oriented students view their learning experience as an
opportunity to increase their skills and knowledge (Dweck & Leggett, 1988). They often display
positive academic efficacy with higher levels of interest in their academics, resulting in increased
efforts and utilization of successful learning strategies (Elliot & Harackiewicz, 1996; Pintrich,
2000a). In reference to STEM courses, students who set their academic goals to actively engage
in an in-depth learning of the material, rather than simply obtaining the grade, are intrinsically
goal oriented (Yildiz-Feyzioglu, Akpinar, & Tatar; 2013). As a result, those students are likely to
engage in reflective thinking and encompass a greater understanding of the material, which can
COMMUNITY COLLEGE STUDENTS IN STEM 33

result in their persistence in STEM and possibly even lead to graduating with a STEM degree
(Yildiz-Feyzioglu, Akpinar, & Tatar; 2013).
Extrinsic Goal Orientation
Extrinsic goal orientation relates to a learner’s engagement for external reasons such as to
expose their capabilities to others, outperform their peers, or receive external successes like
rewards and appraisal. Extrinsic goal-oriented students often focus on presenting their self-worth
to others, and/or to avoid negative consequences. These students are perceived to lack self-
efficacy, pursue less challenging tasks and give up when facing adversity (Elliot &
Harackiewicz, 1996; Pintrich, 2000a). Extrinsically goal oriented students in a STEM course
may have a set extrinsic goal such as passing the course or fulfilling a general education
requirement. These students may only complete the minimum needed to reach that goal, which
may prevent them for deep engagement, resulting in lower performance in the course and lower
persistence in the STEM major (Yildiz-Feyzioglu, Akpinar, & Tatar; 2013).
Intrinsic and extrinsic goal orientation can overlap at times. A course may start out with
students who are intrinsically goal oriented and genuinely interested in understanding the
material, but later in the semester, academic pressure and stress can lead students to become
extrinsically motivated and only focus on getting a good grade (Elliot & Harackiewicz, 1996;
Lepper & Hodell, 1989; Pintrich, 2000a). Some studies show that intrinsically motivated
students display higher levels of academic success while other studies assert that extrinsically
focused students show better performance outcomes as seen in their grades (Elliot &
Harackiewicz, 1996). While the academic achievement and performance outcomes of intrinsic
versus extrinsic students is uncertain, researchers believe that intrinsically motivated students
show greater promise in persistence when facing adversity and possess more effective learning
COMMUNITY COLLEGE STUDENTS IN STEM 34

strategies for their future academic and career advancements (Elliot & Harackiewicz, 1996;
Pintrich, 2000a). Given that intrinsic and extrinsic goal orientation can lead to STEM major
persistence or withdrawal, it is important to assess these factors for students enrolled in STEM
courses in both online and on-campus settings.
Conclusion
In addition to literature related to online learning in higher education systems, this
chapter reviewed three factors that influence student success-related beliefs: help-seeking, self-
efficacy and intrinsic and extrinsic motivation. Academic help-seeking is an important strategy
of self-regulated learning, as it assists learners to focus on optimizing their learning opportunities
and developing academic autonomy, which is essential for success in online courses
(Karabenick, 2003; Newman, 2000). Seeking help can also be challenging for students in cases
where they feel vulnerable or are in a substantially large classroom, and these factors can result
in lower student persistence (Cheng et al., 2013; Karabenick, 2003). Some of these challenges
may be alleviated in online courses, as the removal of face-to-face contact allows for some
anonymity in seeking help (Kitsantas & Chow, 2007).
Self-efficacy sources influence the internal belief a learner has on his or her ability to
perform and succeed academically (Bandura, 1995; Pajares, 2006). It is important to examine
these sources in both online and traditional delivery formats of STEM courses and investigate
their influence on student self-efficacy levels. In addition, given that research pointed to self-
efficacy levels as a contributor to URM STEM student persistence, it is crucial to investigate
these levels and compare them to those of their peers in the same courses. Intrinsically goal
oriented STEM students actively participate in learning the material and are more likely to
possess a greater understanding of the course, which can assist in their interest and persistence of
COMMUNITY COLLEGE STUDENTS IN STEM 35

a STEM major (Yildiz-Feyzioglu, Akpinar, & Tatar; 2013). Extrinsically goal oriented STEM
students may disengage from the learning aspect of the course and merely focus on performance,
which could result in positive performance outcomes, but may also prevent and in-depth
understanding of the material and affect the overall persistence of the students (Elliot &
Harackiewicz, 1996; Pintrich, 2000a). Examining these three factors that promote student
academic success in a STEM course, and comparing them in online and traditional formats, was
of critical importance for the purpose of this study.

COMMUNITY COLLEGE STUDENTS IN STEM 36

CHAPTER THREE: METHODOLOGY
The PCAST (2012) strongly advises that the U.S. develop professionals in STEM fields
and suggests strategies to help increase STEM undergraduate degree completion so that students
can gain a competitive advantage in promising professional opportunities (Hurtado et al., 2009).
In particular, the IT field encompasses a wide range of employment availability. However,
studies have revealed that academic student success-related beliefs often discourage students
from pursuing an IT-related major (Zhang, 2007). This study investigated the level of self-
efficacy for URM students enrolled in a STEM course compared to their peers. In addition, the
current study compared help-seeking, self-efficacy and intrinsic and extrinsic goal orientation
factors of a 100% online introductory IT course with those of the exact same course taught 100%
on campus. Finally, the study examined whether there was a relationship among self-efficacy,
goal orientation and help-seeking beliefs within the two different delivery methods.
Provided in this chapter, are the research questions and a description of the research
methodology. The latter includes the sampling procedure and population, instrumentation, and
procedures for data collection and analysis.
Research Questions
The following proposed research questions guided the study:
1. Is there a difference in the level of self-efficacy of URM students in comparison
to other students?
2. Is there a difference in student self-efficacy and goal orientation by course
delivery method?
3. Is there a difference in student help-seeking beliefs by course delivery method?
COMMUNITY COLLEGE STUDENTS IN STEM 37

4. Is there a relationship between self-efficacy, goal orientation and help-seeking
beliefs, controlling for course delivery method?
Research Design
The proposed study was a quantitative, non-experimental design consisting of self-report
surveys. The independent variables (IV) in this study were course delivery method, self-efficacy,
goal orientation, and the self-reported ethnicity of students enrolled in online and on-campus
courses. The dependent variables (DV) in this study were goal orientation, self-efficacy beliefs
and help-seeking beliefs. In order to effectively investigate the relationships among academic
beliefs, and examine the statistical differences of those beliefs in both online and on-campus
settings, a quantitative, non-experimental design was used. This quantitative approach entailed
administering one survey to both online and on campus students taking an introductory
technology course at a large community college in southern California. Correlational data from
self-report surveys were gathered and analyzed for statistical significance with the goal of
determining whether there were differences in the academic beliefs of the surveyed students.
Population and Sample
The population for data collection was a diverse sample of 127 first- and second-year
community college students enrolled in an Introduction to Information Technology Concepts and
Applications (ITCA 101) course. The number of students enrolled in ITCA on campus and
online totaled 281 students. The survey response rate for this study was approximately 45%.
ITCA is a general education prerequisite course that meets the core lower division requirements
of a variety of STEM programs in the California State University system such as California State
Polytechnic University, Pomona’s B.S. in Engineering Technology program. Computer hardware
is introduced in this course along with the concept of a local area network, software, computer
COMMUNITY COLLEGE STUDENTS IN STEM 38

systems, and the integration of these applications in business and technology. Students also gain
knowledge and experience in high level programming using IBM-compatible microcomputers.
Instrumentation
A self-report questionnaire consisting of demographic questions (11 items), help-seeking
beliefs (7 items), self-efficacy (8 items), intrinsic (4 items) and extrinsic goal orientation (4
items) was administered via e-mail to all students enrolled in the course on campus and online.
The instruments used to answer the research questions included a portion of Karabenick’s (2003)
questionnaire and several portions of the MSLQ (Pintrich, Smith, Garcia & McKeachie’s, 1991).
These instruments, in addition to demographic questions, totaled 34 items. Respondents totaled
127, with 46 of the students enrolled in the online course and 81 in the on-campus course.
Demographic Information
The self-reported survey began with a number of demographic questions that allowed the
researcher to compare potential demographic differences between course delivery and STEM
self-efficacy beliefs (Appendix A). They included asking the participant about the following:
age, gender, ethnicity, language spoken, employment status, relationship status, current major,
intended major, level of parents’ education, number of units taken, number of previous online
courses taken, whether they were taking this course online or on campus and why they chose the
format. The southern California community college surveyed for this study had some notable
demographic information as a whole. Student enrollment reported for Fall 2013 totaled 31,563.
Sixty two percent of these students were in the traditional college-going age range of 18 to 24,
and 21% in the 25 to 34 age range. In addition, the college reported that 46% of its students were
Hispanic/Latino, 18% Black or African American, 17% White, 14% Asian and 5% unknown or
COMMUNITY COLLEGE STUDENTS IN STEM 39

unreported. As demonstrated in the following sections, these demographic percentages are
similar to those of students surveyed.
All students surveyed for this study were enrolled in ITCA 101 during the Fall 2014
semester at one particular community college in southern California. Students who enrolled in
and passed ITCA 101 fulfilled a general education prerequisite course that meets the core lower
division requirements of a variety of STEM programs in the California State University system.
There were four instructors who taught the five on campus sections of the course. Two of those
instructors also taught two of the online sections, and two different instructors taught the other
two online sections. The same syllabus was used for all sections. The online courses were all
taught in an asynchronous format, where students were not required to meet with their professors
or classmates virtually at any set time, but did have deadlines to submit assignments. The age of
the participants in this study ranged from 18 to 48, with 57.5% (n = 73) in the 18 to 22 age range
and 22% (n = 28) in the 23 to 27 age range. In addition, 81% (n = 60) of the total participants in
the 18 to 22 age range (n = 73) reported that they were enrolled in the course on campus. The
mean age was 24 years (SD = 5.589).
Table 1
Participant Demographics: Age
Course Delivery Method
Age Online % Campus % Total %
18-22 13 30 60 72 73 57.5
23-27 15 34 13 16 28 22
28-32 9 20 5 6 14 11
33-37 7 16 4 4.8 11 8.7
38-42 0 0 0 0 0 0
43-47 0 0 1 1.2 1 .8
48+ 0 0 1 1.2 1 .8
Total 44 1 83 1 127 1

COMMUNITY COLLEGE STUDENTS IN STEM 40

Fifty percent (n = 63) of the students surveyed were Hispanic/Latino, 17% (n = 22) were
White, 12% (n = 15) were Asian, and 11% (n = 14) were Black or African American. In
addition, 1% of the students surveyed were American Indian or Alaska Native (n = 1), 2% were
Native Hawaiian or other Pacific Islander (n = 2), 7% were two or more races (n = 9) and 1%
self-reported as "other" (n = 1). In this study, students who identified themselves with the
following ethnic groups were grouped as underrepresented minority students (URM): Black or
African American, Hispanic/Latino, American Indian/Alaska Native and Native
Hawaiian/Pacific. URM students totaled (n = 80) and White and Asian students totaled (n = 37).
Table 2
Participant Demographics: Ethnicity
Ethnicity Number of Students %
American Indian or Alaska Native 1 1%
Asian 15 12%
Black or African American 14 11%
Hispanic/Latino 63 50%
Native Hawaiian or other Pacific Islander 2 2%
White 22 17%
Two or more races 9 7%
Other 1 1%
Total 127 100%

In summary, the students surveyed are significantly more likely to be in the 18 to 27 age
range and of either Hispanic/Latino, White, Asian or Black/African American ethnicity.
Demographic information of the study sample was consistent with the research literature of
national community college student demographics (American Association of Community
Colleges, 2011).
COMMUNITY COLLEGE STUDENTS IN STEM 41

Help-Seeking Beliefs
For this study, the various dimensions of help-seeking beliefs were assessed at the
beginning of the class through a set of questions from two instruments. One of these instruments
was Pintrich, Smith, Garcia and McKeachie’s (1991) MSLQ (Appendix B). The MSLQ included
81 items intended to measure the motivation orientations of students and their use of learning
strategies. It was divided into two sections: a motivation section and a learning strategies section.
The help-seeking questions used for this study were those imbedded in the resource management
component of the learning strategies section of the MSLQ (Pintrich et al., 1991). The original
help-seeking beliefs component of the MSLQ had an estimated Cronbach’s alpha of .52. The
reliability analysis performed for this study reported an alpha of .703, which was greater than the
.52 reported in the literature and higher than the minimum level of acceptability of .70. A seven-
point Likert scale ranging from 1 (not at all true of me) to 7 (very true of me) was used for this
portion of the survey to analyze student help-seeking beliefs (Pintrich et al., 1991). One of the
four items from the measure was, “I ask the instructor to clarify concepts I don’t understand
well.”
Additional data on help-seeking beliefs was measured using the Karabenick (2003) scale
(Appendix B). Three items were pulled from this scale to focus specifically on formal and
informal help-seeking beliefs to determine the learner’s preferred source of help. The original
scale had a Cronbach’s alpha internal consistency estimate of .66. The reliability analysis
performed for this study reported an alpha of .614, which was below the .66 reported in the
literature and lower than the minimum level of acceptability of .70. A five-point Likert scale
ranging from 1 (not at all true) to 5 (completely true) was used for this portion of the survey
COMMUNITY COLLEGE STUDENTS IN STEM 42

(Karabenick, 2003). One of the three items that was used from the measure included was “In this
class, the teacher would be better to get help from than would a student.”
Self-Efficacy. As mentioned in the help-seeking section, the MSLQ is divided into two
sections: a motivation section and a learning strategies section. The motivation section includes
three components, one of which is an expectancy component comprised of scales for control of
learning beliefs and self-efficacy for learning and performance. The instrument that was used in
this portion of the study was the self-efficacy for learning and performance portion of the
motivation section of the MSLQ (Pintrich et al., 1991) (Appendix C). The scale measured
students’ beliefs that their individual efforts can lead to their academic success. Eight items
measured the students’ performance expectations and their evaluation of their capability to
succeed in the course (Pintrich et al., 1991). This component of the MSLQ originally had an
estimated Cronbach’s alpha of .93. The reliability analysis performed for this study reported an
alpha of .945, which was slightly higher than the .93 reported in the literature and significantly
greater than the minimum level of acceptability of .70. A seven-point Likert scale ranging from 1
(not at all true of me) to 7 (very true of me) was used for this portion of the survey (Pintrich et
al., 1991). Two items included were “I expect to do well in this class” and “I’m certain I can
master the skills being taught in this class.”
Intrinsic and Extrinsic Goal Orientation
One of three components of the motivation section of the MSLQ was discussed in the
self-efficacy section. Another component in this section is a value component, which is
comprised of scales of intrinsic goal orientation, extrinsic goal orientation, and task value. This
portion of the study solely measured the intrinsic and extrinsic value components (Appendix D).
The intrinsic and extrinsic components of the MSLQ consisted of four items each, and used a
COMMUNITY COLLEGE STUDENTS IN STEM 43

seven-point Likert scale ranging from 1 (not at all true of me) to 7 (very true of me). The
original intrinsic and extrinsic goal orientation items had an estimated Cronbach’s alpha of .74
and .62 respectively (Pintrich et al., 1991). The reliability analysis performed for this study
reported an alpha of .84 for intrinsic goal orientation, which was greater than the .74 reported in
the literature, and an alpha of .73 for extrinsic goal orientation, which was greater than the .62
reported in the literature. Both alphas were higher than the minimum level of acceptability of .70.
Two items were, “The most satisfying thing for me in this course is trying to understand the
content as thoroughly as possible” and “Getting a good grade in this class is the most satisfying
thing for me right now.”
Procedure and Data Collection
Once the university’s Institutional Review Board approved the study, the researcher
gathered quantitative data via self-report questionnaires. The questionnaires were linked to an
online Qualtrics survey and were distributed via e-mail to all students enrolled in the course on
campus and online. The researcher explained the purpose of the study and provided a link to the
survey in an e-mail. The professors then sent the e-mail on to all of their students, explaining that
the survey was voluntary and anonymous. All students in both formats were asked to take
approximately 20 minutes within one week of receiving the link and were offered the
opportunity to participate in a raffle drawing for a $25 Amazon gift card upon completing the
survey. They were also informed that they would not be penalized for not participating.
Data Analysis
The first research question in this study aimed to determine whether there was a
difference in the level of self-efficacy of URM students in comparison to other students. An
independent samples' t-test was performed for this analysis with student demographics and
COMMUNITY COLLEGE STUDENTS IN STEM 44

course delivery method as the independent variables (IV) and self-efficacy for the dependent
variable (DV). The second research question examined whether there was a difference in the
self-efficacy beliefs and goal orientation of students taking the course online versus on campus.
Two independent samples' t-tests were performed for this analysis with course delivery method
as the IV and self-efficacy and goal orientation as the DVs. The third research question
investigated whether there was a difference in the help-seeking beliefs of students taking the
course online versus on campus. An independent samples' t-test was performed for this analysis
with course delivery method as the IV and help-seeking beliefs as the DVs. The fourth research
question determined whether there was a relationship between self-efficacy, goal orientation and
help-seeking beliefs when controlling for course delivery method. A multiple linear regression
was performed with self-efficacy and goal orientation as the IVs and help-seeking beliefs as the
DV. All data was coded and entered into the SPSS 15.0 program. Scale means and Cronbach's
alphas were computed. T-tests and regression analysis were used. Table 3 specifies the
independent and dependent variables and their corresponding level of measurements for each
research question. It also provides the statistical test that was performed.

COMMUNITY COLLEGE STUDENTS IN STEM 45

Table 3
Data Analysis
Research
Question
IV(s)
Level of
Measurement
DV(s)
Level of
Measurement
Statistical
Test
Is there a
difference in
the level of
self-efficacy
of URM
students in
comparison
to other
students?
Student
Demographics
(URM vs.
White and
Asian)
Course delivery
method
Nominal

Nominal

Self-efficacy
beliefs
Interval Independent
samples' t-
test
Is there a
difference in
student self-
efficacy and
goal
orientation
by course
delivery
method?
Course
delivery
method

Nominal Self-efficacy
beliefs

Interval Independent
samples' t-
test
Goal
Orientation
Interval Independent
samples' t-
test
Is there a
difference in
student help-
seeking
beliefs by
course
delivery
method?
Course delivery
method
Nominal Help-seeking
beliefs

Interval Independent
samples' t-
test
Is there a
relationship
between self-
efficacy, goal
orientation
and help-
seeking
beliefs,
controlling
for course
delivery
method?
Self-efficacy
beliefs
Goal
orientation
Course
delivery
method
Interval

Interval

Nominal
Help-seeking
beliefs
Interval Multiple
linear
regression,
all IVs
entered as
one block

COMMUNITY COLLEGE STUDENTS IN STEM 46

CHAPTER FOUR: RESULTS
The purpose of this chapter is to report this study’s findings. Descriptive correlations are
discussed first, followed by an analysis of the results to answer each research question. All data
was analyzed in SPSS, using appropriate statistical tests.
Descriptive Statistics
Correlations of all measured variables are presented in Table 4 and three major
significant differences were found in relation to age. First, age was positively correlated with the
number of online courses taken in the past. Older students had taken a greater number of online
courses (r = .256, p < .01). Second, older students reported lower levels of self-efficacy (r = -
.251, p = < .01) and were less likely to seek help (r = -.293, p = < .01). Finally, older students
were more likely to seek help from formal sources (r = .232, p = < .01). Several additional
significant differences were found in relation to the academic constructs. The number of online
courses was negatively correlated with help-seeking beliefs, indicating that students who had
taken more online courses were less likely to seek help (r = -.202, p = < .05). Self-efficacy
beliefs were found to be positively correlated with help-seeking beliefs (r = .354, p = < .01),
intrinsic goal orientation (r = .582, p = <.01), and extrinsic goal orientation (r = .303, p = < .01).
Help-seeking beliefs were also positively correlated with intrinsic goal orientation (r = .317, p =
< .01) and extrinsic goal orientation (r = .254, p = < .01), but negatively with formal help-
seeking beliefs (r = -.225, p = <.05). Finally, there was a positive relationship between intrinsic
and extrinsic (r = .374, p = <.01).
COMMUNITY COLLEGE STUDENTS IN STEM 47

Table 4
Means, Standard Deviations, and Pearson Product Correlations of Measured Variables
Variables M SD Educ #onl SE HS FHS InGO ExGO

1. Age 23.79 5.589 .102 .256** -.251** -.293** .232** -.063 -.164
2. Parent Edu. 5.02 1.645 -- .111 -.076 -.107 .056 -.112 -.033
3. #Online Courses 1.29 2.051 -- -.076 -.107 .056 -.112 -.033
4. Efficacy 4.06 .75 -- .354** -2.51** -.08 -.02
5. Help-Seeking 3.95 .71 -- -.225* .317** .254**
6. FInf.Help 3.74 .73 -- .105 -.018
7. Int. GO 5.46 1.29 -- .374**
8. Ext. GO 5.65 1.19 --
*p<.05 **p<.01

Analysis of Results
Data was collected using self-report survey instruments and was analyzed in SPSS using
appropriate statistical tests to answer the four research questions proposed in Chapter One. This
section discusses the results and analysis of each research question separately.
Research Question 1
The first research question asked, “Is there a difference in the level of self-efficacy of
URM students in comparison to other students?” This question sought to examine whether there
are potential differences in the self-efficacy of URM students enrolled in a STEM course in
comparison to their White and Asian counterparts.
Self-efficacy. In order to determine whether differences in the self-efficacy of URM
students enrolled in ITCA 101 exists in comparison to their classmates, students were asked to
report their ethnicity in the demographic section. In addition, these students completed the
expectancy component of the motivation section in the MSLQ (Pintrich et al., 1991) (Appendix
C). The scale measured students’ beliefs that their individual efforts could lead to their academic
COMMUNITY COLLEGE STUDENTS IN STEM 48

success in the ITCA 101 course during the fall 2014 semester. Eight items measured their
performance expectations and their evaluation of their capability to succeed in the course
(Pintrich et al., 1991). The data collected from this survey was analyzed using a t-test. The
independent variable for this analysis was student ethnicity and the dependent variable was their
self-reported self-efficacy beliefs. The self-efficacy beliefs of students who identified themselves
with the following ethnic groups were grouped as underrepresented minority students (URM):
Black or African American, Hispanic/Latino, American Indian/Alaska Native and Native
Hawaiian/Pacific. URM students were compared to White and Asian students. Because the
ethnicity was not specific, students who reported themselves as “two or more races” or “other”
were disregarded in this portion of the study.
T-tests were performed to compare the academic beliefs of URM in comparison to their
White and Asian counterparts. No significance was found in the self-efficacy levels of URM
students in comparison to their White and Asian counterparts. However, URM students reported
significantly greater intrinsic goal orientation (M = 5.67, SD = 1.14) than did their White and
Asian counterparts (M = 5.11, SD = 1.42); t(109) = 2.24, p = .027.
Research Question 2
The second research question asked, “Is there a difference in student self-efficacy and
goal orientation by course delivery method?” This question sought to investigate potential
differences between course delivery methods with regard to self-efficacy beliefs and goal
orientation. Each of these academic factors was analyzed separately for this study.
Self-efficacy across course delivery method. An independent samples’ t-test was used
in order to compare the self-efficacy levels of students taking ITCA 101 100% on campus with
those taking the course 100% online. Results of this analysis showed a significant difference
COMMUNITY COLLEGE STUDENTS IN STEM 49

between groups. Students who were taking the course on campus reported greater levels of self-
efficacy beliefs (M = 4.2, SD = .55) in their performance expectations and ability to succeed in
the course than did their peers who were taking the course online (M = 3.8, SD = .97); t(123) = -
3.17, p = .002.
Goal orientation across course delivery method. In order to determine whether there
was a difference in the goal orientation of students taking the course online versus on campus,
students were asked to respond to the value component of the motivation section of the MSLQ
(Pintrich et al., 1991). The value component used for this portion of the study was comprised of
scales of intrinsic and extrinsic goal orientation (Appendix D). An independent samples’ t-test
was used to compare goal orientation across course delivery method and significant differences
were found. Students enrolled in ITCA 101 on-campus were more intrinsically goal oriented (M
= 5.76, SD = 1.08) than were students taking the course online (M = 4.9, SD = 1.45); t(121) = -
3.86, p = .00. There was no significant difference in extrinsic goal orientation between students
who enrolled in ITCA 101 on-campus (M = 5.75, SD = 1.29) and students who took the course
online (M = 5.47, SD = .96); t(121) = -1.25, p = .21.
Research Question 3
The third research question asked, “Is there a difference in student help-seeking beliefs
by course delivery method?” This question sought to examine whether differences in help-
seeking beliefs exist between students taking ITCA 101 online versus those taking the course on
campus.
Help-seeking beliefs. Help-seeking beliefs were assessed through a set of questions from
two instruments: the resource management component of the learning strategies section of the
MSLQ, and the Karabenick scale (Karabenick, 2003; Pintrich et al., 1991) (Appendix B). The
COMMUNITY COLLEGE STUDENTS IN STEM 50

data collected from these surveys was analyzed using t-tests. There was a significant difference
found with regard to help-seeking beliefs. Students taking ITCA 101 on campus reported a
higher likelihood of seeking help (M = 4.17, SD = .58) than did students taking the course online
(M = 3.54, SD = .74); t(124) = -5.33, p = .000 ).
As for formal versus informal help-seeking beliefs, the online students indicated that they
were more likely to seek help from formal sources such as instructors (M = 4.15, SD = .70) than
were the students who took the course on campus (M = 3.66, SD = .85); t(123) = 3.24, p = .002.
Research Question 4
The fourth research question asked, “Is there a relationship between self-efficacy, goal
orientation and help-seeking beliefs, controlling for course delivery method?” The final research
question examined a potential predictive relationship between constructs. Self-efficacy and goal
orientation are investigated individually as potential predictors of help-seeking beliefs.
Relationships between self-efficacy, goal orientation and help-seeking beliefs. A
linear regression was performed controlling for course delivery method to determine whether
self-efficacy beliefs predict students’ help-seeking beliefs. While regression analysis technically
establishes prediction, this study found a relationship between the constructs rather than a cause
and effect prediction. The relationship between help-seeking beliefs and course delivery format
was significant (F = 11.65, df = 4, 117, p = .00). Course delivery format explained 29% of
variance in help-seeking beliefs. However, no significance was found with regard to neither self-
efficacy nor goal orientation as predictors of help-seeking beliefs. When course delivery format
was removed as an independent variable, there was a moderate, positive correlation between
self-efficacy and help-seeking (r = .354, N = 125, p = <.01). With the removal of course delivery
COMMUNITY COLLEGE STUDENTS IN STEM 51

format as an independent variable, individual self-efficacy beliefs explained approximately 16%
of variance in participants’ help-seeking beliefs.
In summary, the research questions proposed in this study were analyzed and answered in
this chapter through appropriate statistical testing. Each research question was individually
presented and analyzed. The first research question asked about potential differences in self-
efficacy levels of URM students in comparison to their White and Asian counterparts. No
significant differences were found, supporting literature that culturally diverse colleges and
universities often provide supportive campus environments and climates that can increase the
self-efficacy of URM students (Cole & Espinoza, 2008; Cole & Griffin, 2013; Hurtado et al.,
2011; Ong et al., 2011; Winston et al., 2010). The second and third research questions
investigated potential differences in student self-efficacy, goal orientation and help-seeking
beliefs by course delivery method. Significant differences were found with on-campus students
displaying higher levels of all constructs except for formal help-seeking beliefs, in which the
online students reported greater levels. Finally, potential predictors were analyzed for the fourth
research question. No significant relationships were found for either construct as predictors of
help-seeking beliefs when controlling for course delivery method. These results are discussed in
the next chapter, along with the limitations of the study and implications for future research.

COMMUNITY COLLEGE STUDENTS IN STEM 52

CHAPTER FIVE: DISCUSSION
This final chapter opens with a brief overview of the purpose of this study. Next, each of
this study’s findings is discussed in great depth. Finally, this chapter concludes with disclosing
the study’s limitations and providing implications and recommendations for future research.
This study assessed several academic factors of students in community college settings.
Specifically, the academic factors examined were the constructs of self-efficacy, help-seeking
and intrinsic and extrinsic goal orientation that research has revealed to have a significant effect
on performance. While these constructs have been researched in the past, very few studies
analyzed them across course delivery methods as this study has done. The purpose of this study
was to investigate whether there were significant differences in the self-efficacy levels of URM
students in comparison with their counterparts. In addition, this study intended to examine
whether the rapidly growing online course delivery method supports or compromises the
development of important academic beliefs of students taking a STEM course.
The research questions developed for this study were designed to compare the academic
beliefs of students enrolled in online and on-campus formats of an information technology
course. Quantitative data was collected from the students via self-report survey instruments and
was analyzed in SPSS using appropriate statistical testing. An interpretation of the results from
this study is provided in the following sections.
Discussion of Student Demographic Composition
The self-reported survey began with a number of demographic questions to provide the
researcher with an overall student profile and composition of the individuals surveyed.
Participants were asked to report their age, gender, ethnicity, employment status, relationship
status, major, level of parents’ education, number of units taken, number of previous online
COMMUNITY COLLEGE STUDENTS IN STEM 53

courses taken, whether they are taking this course online or on campus and why they chose the
format. These questions were intended to determine potential significant differences between
learner characteristics and academic beliefs. Consistent with recent statistical research on both
community college students and online students, the majority of the individuals surveyed who
were enrolled in the online course were older, non-White, employed and reported having
dependents (Martin, Galentino, & Townsend, 2014; NCES, 2011).
Since the majority of students surveyed were in the 18 to 27 age range, most of the
individuals surveyed who are considered “older students” are likely to be in the upper range of
that scale with a small portion in the 27 to 52 age range. This study found that older students
took a greater number of courses in the online format, which could be due to the professional
responsibilities and family obligations that non-traditional students are more likely to have
(Allen & Seaman, 2013; Brown, 2012). These obligations may also prevent these students from
taking the time to seek help, which could explain the finding that students who had taken a larger
number of online courses had lower help-seeking beliefs (Al-Asfour & Bryant, 2011). It is
important to note that students who had a lot of experience taking online courses and who
reported lower help-seeking beliefs may not have been enrolled in the online format of this
particular course. Finally, older students were found to have lower levels of self-efficacy than did
younger students. It is possible that the older students had previous experiences of academic
shortcomings, which could have resulted in a lower level of self-efficacy (Bandura, 1986; Cheng
& Lee, 2009; Pajares 2006). In addition, older students’ being in the minority of the student
profile may leave them feeling isolated and apprehensive to seek help in the course as well
(Ozkan, Koseler & Baykal, 2009).
COMMUNITY COLLEGE STUDENTS IN STEM 54

Discussion of Self-Efficacy Across Ethnicity
Seminal research asserts that the academic self-efficacy levels of URM students have a
strong effect on their academic performance in prerequisite college courses (Bandura, 1993; Cole
& Griffin, 2013; Wernersbach et al., 2014). URM students receive less than 5% of the STEM
bachelor’s degrees awarded, leading to low preliminary STEM course enrollment (Moakler &
Kim, 2014, Winston et al., 2010). While studies have shown the rates of URM student interest in
STEM courses and majors to be similar to those of their peers, low levels of self-efficacy have
been found to correlate with the low persistence of URM STEM students, which may explain the
low percentage of URM STEM degree attainment (Gusa, 2010; Palmer, Maramba, & Dancy,
2011; Seymour & Hewitt, 1997). This study examined the self-reported self-efficacy levels of
URM students in ITCA 101 and compared them to their counterparts.
The ITCA 101 students from this study sample, who reported themselves as a URM,
accounted for 64% of the total participants, and the White and Asian students were 29% of the
total participants. The results of this study yielded no significant differences in the level of self-
efficacy of URM students in comparison to their non-URM peers in the same course. These
results are consistent with the literature, as studies have shown that colleges with a diverse
student body tend to foster positive environments where URM students demonstrate confidence
and persistence in STEM courses and majors (Cole & Espinoza, 2008; Cole & Griffin, 2013;
Hurtado et al., 2011; Ong et al., 2011; Winston et al., 2010). In these previous studies,
researchers pointed to HBCUs as examples of positive environments that encourage engaging
interactions in and out of the classroom between students and STEM faculty (Cole & Griffin,
2013; Ong et al., 2011; Winston et al., 2010). These interactions are often credited as
contributing positively to the academic self-efficacy levels of URM students. Hurtado et al.’s
COMMUNITY COLLEGE STUDENTS IN STEM 55

(1998) scope of structural diversity as a numerical representation supports this study, as the only
significant difference that was shown was positive for URM STEM students. The diverse student
body of the community college sampled for this study may have a classroom and campus
environment similar to HBCUs, explaining the lack of disparity among student self-efficacy
levels across ethnicity (American Association of Community Colleges, 2011).
Data analysis for this research question did reveal a significant difference in one of the
academic constructs. URM students displayed significantly greater intrinsic goal orientations
than did their White and Asian counterparts. This means that URM students in this study sample
were more likely to display a genuine interest in the learning process, embracing the course
challenges and showing a desire to increase their knowledge in the course material (Dweck &
Leggett, 1988, Pintrich, 2000a). It must also be noted that, while studies show an existence of
negative relationships between STEM faculty members and URM students, this study showed no
significant differences in formal or informal help-seeking beliefs of URM students in comparison
to their White and Asian peers (Driscoll, 2004, Palmer, Maramba, & Dancy, 2011; Seymour &
Hewitt, 1997). When URM students seek help from their STEM professors and classmates,
mentoring relationships between the faculty member and student can be fostered along with a
sense of belonging on campus. These experiences can encourage active participation among
peers, and motivate URM STEM students to become more involved in their collegiate
experience (Cole & Espinoza, 2008; Cole & Griffin, 2013; Hunt, 2003).
The URM students in this study displayed greater intrinsic goal orientation and no
difference in help-seeking or self-efficacy beliefs than their White or Asian counterparts. These
findings draw to the possibility that the community college in which the study took place
provided a learning environment structured to encourage active participation for its students
COMMUNITY COLLEGE STUDENTS IN STEM 56

(Astin, 1984; Gasiewski et al., 2012; Rosenshine, 1982). A positive learning environment such as
this supports effective learning strategies for URM students. URM students in this study were
likely to engage in reflective thinking, encompass a greater understanding of the material and
may have high educational and career aspirations in STEM, which could result in choosing more
STEM courses and possibly even lead to graduating with a STEM degree (Cole & Espinoza,
2008; Cole & Griffin, 2010; Pascarella, 1980; Yildiz-Feyzioglu, Akpinar, & Tatar; 2013).
Discussion of Self-Efficacy, Goal Orientation and Help-Seeking Beliefs
Across Course Delivery Method
The online students displayed significantly lower help-seeking beliefs, supporting studies
asserting that the absence of a physical classroom environment can also cause a lack of
collaboration and interaction with instructors and peers, leaving online learners to feel isolated
from their classmates (Al-Asfour & Bryant, 2011; Ozkan, Koseler & Baykal, 2009). It is possible
that the online environment of this course did not provide its students with a sense of community
where social integration is encouraged, hence students may not have built strong enough
relationships with their instructors or classmates to seek help from them (Tinto, 1975; Astin,
1984). However, results from this study also showed that the online ITCA 101 students were
more likely to seek help from formal sources such as their instructors than were their on-campus
peers. Although some research indicates that many professors have negative perceptions about
teaching online courses, a considerable amount of recent research points to instructors supporting
online education, which is in alignment with the findings of this study (Allen & Seaman, 2014;
Chen, Lambert & Guidry, 2010; Rabe-Hemp et al., 2009). While there seems to be a relationship
between the online students and age, self-efficacy and help-seeking beliefs, further study of these
variables are warranted.
COMMUNITY COLLEGE STUDENTS IN STEM 57

The students taking ITCA 101 online also reported lower intrinsic goal orientation along
with lower levels of self-efficacy than did the students taking the course on campus. This means
that with regard to motivation, the online students did not display as much of a genuine interest
in increasing their knowledge on the course material, nor were they as focused on exposing their
capabilities to others than were the students taking the course on campus (Dweck & Leggett,
1988; Yildiz-Feyzioglu, Akpinar, & Tatar; 2013).
Self-efficacy affects intellectual reasoning and personal feelings towards a subject and
major (deNoyelles, Hornik & Johnson, 2014). The ITCA 101 students in this study who took the
course on campus reported higher levels of self-efficacy than did their online peers. This means
they were less likely to feel threatened but were rather challenged by obstacles during the course,
which could encourage them to persist in similar courses in the future. The less efficacious
students, however, reported lacking confidence in understanding the course material and in
obtaining mastery skills in the course content. These students could become less engaged in the
learning process of the course and could lose interest or have negative feelings about the subject
as a whole (deNoyelles, Hornik & Johnson, 2014).
Studies found self-efficacy beliefs to be among one of the most significant predictors of
self-regulatory learning and performance outcomes (Pajares, 2006). In addition, self-regulation
and discipline have been found to be crucial for the success of online learners (Allen & Seaman,
2014; Al-Asfour & Bryant, 2011). Therefore, it is concerning to see the online learners in this
study reporting such lower self-efficacy levels than the on-campus learners do in a preliminary
STEM course, as it puts them at risk for decreased levels of motivation and low persistence in
the course and in STEM major retention and degree attainment (Al-Asfour & Bryant, 2011;
Allen & Seaman, 2014; Pajares, 2006; Raelin et al., 2014). Since the correlational data showed
COMMUNITY COLLEGE STUDENTS IN STEM 58

that the students in this study who took more online courses tended to be older, it is possible that
they had negative or failed experiences with STEM course content in the past (Bandura, 1986;
Pajares 2006). This could explain the differences in the various constructs and learning efforts
compared to the students taking the course on campus who had face-to-face interactions (Bates
& Khasawneh, 2007; Wang, Shannon, & Ross, 2013). These results and recent literature suggest
that lower levels of these academic constructs can lead to lower levels of academic success and
negative performance outcomes for the online ITCA 101 students (Cole & Griffin, 2013; Elliot
& Harackiewicz, 1996; Wernersbach et al., 2014).
With regard to help-seeking predictors when controlling for course delivery method, goal
orientation was not found to be a potential predictor of help-seeking beliefs, meaning that
students’ interest and engagement in the learning process did not influence their beliefs about
seeking help from their instructors or peers. While self-efficacy was also not a predictor of help-
seeking beliefs, it was suppressed by course delivery as an independent variable in the full model
of the analysis, resulting in participants’ help-seeking beliefs to be explained by the level of that
individual’s self-efficacy beliefs. This is likely because self-efficacy and course delivery are
correlated. This supports the literature that students with high levels of self-efficacy often display
self-regulatory learning beliefs such as seeking help from instructors or peers to conquer future
academic tasks and challenges (Pajares, 2006; Wernersbach et al., 2014).
Implications
Implications from this study can inform community college STEM instructors and
administrators on best practices to improve the academic beliefs of their students, which can lead
to a significant growth in students enrolling and majoring in STEM subjects. Of particular
concern was finding that online learners exhibited lower self-efficacy beliefs when compared to
COMMUNITY COLLEGE STUDENTS IN STEM 59

their on-campus counterparts. Studies pointed to a number of interventions that institutions and
administrators can implement to help improve student self-efficacy beliefs, but robust literature
and research points to positive peer-to-peer and student-faculty interaction as having some of the
greatest influence on increasing student self-efficacy beliefs (Cole & Espinoza, 2008; Cole &
Griffin, 2013; Pajares, 2006).
Creating an online educational community and environment for students that encourages
student involvement in a collaborative classroom can generate personal bonds and intellectual
discourse between STEM students and their faculty (Astin, 1984; Cole & Griffin, 2013; Hunt,
2003; Tinto, 1987; Tinto, 1997). Student-faculty and peer-to-peer interactions can lead to
positive social modeling and social persuasion, which are two of the four sources of self-efficacy
that were discussed in Chapter Two (Bandura, 1986; Pajares 2006). 2013). Hunt (2003)
discussed knowing each online learner individually by first name, and enthusiastically engaging
them in and out of the classroom with consistent office hours and technological forms of
communication such as e-mail and course websites. Instructors can support their students
through scaffolding by setting short-term goals for their students and privately providing them
with frequent feedback balancing out their strengths and challenges (Pajares, 2009). One-on-one
opportunities and positive feedback can create a sense of validation for students, enabling them
to believe they can conquer and master academic tasks, and fostering their academic
development and success (Hurtado et al., 2009). Such interactions can nurture a mentoring
relationship between the faculty member and online learner, encourage active participation
among peers, and motivate the online STEM students to become more involved in the course and
overall collegiate experience (Cole & Griffin, 2013; Hunt, 2003). These efforts often lead to
COMMUNITY COLLEGE STUDENTS IN STEM 60

positive student experiences that will improve their self-efficacy beliefs and result in increased
student persistence and GPAs (Cole & Espinoza, 2008; Cole & Griffin, 2013).
The study’s finding that URM students did not display lower levels of any constructs in
comparison to their White and Asian counterparts is notable as it reinforces the theory that
diverse settings can offer positive campus climates for URM students. A diverse student body is
not enough, but the existence and growth of campus initiatives and the recruitment of diverse
STEM faculty, staff, and administrators can be a very effective way to maintain and increase the
academic constructs of URM students who are enrolled in STEM courses. Positive URM student
experiences with their classmate and faculty members can significantly increase their STEM
degree achievement and pursuit of STEM careers (Cole & Espinoza, 2008; Cole & Griffin, 2013;
Gasiewski et al., 2012; Moakler & Kim, 2014; Ong et al., 2011; Winston et al., 2010).
Online ITCA 101 students reported lower levels of all major academic constructs than
those of the students taking the course on campus. Since the online ITCA 101 students reported
significantly lower levels of academic beliefs than did the on-campus students, they are at a
higher risk for STEM course and major withdrawal than were students taking STEM courses on
campus (McEwen & Gueldenzoph, 2003; PCAST, 2012). With the rapid growth of both
information technology and online education, these findings may encourage community college
instructors and administrators to examine multiple facets of the online course, and adapt its
curriculum and format continuously to its changing environment and audience (Khan, 2011). It is
possible that the online ITCA 101 students were not equipped with the appropriate technological
skills needed to succeed in an online course (Al-Asfour & Bryant, 2011). Computer skill
identification at the initial phase of the enrollment period could help to provide those students
with more support (Ragin, 2013). Academic support services such as online tutoring, study skills
COMMUNITY COLLEGE STUDENTS IN STEM 61

workshops and new student orientations can enable academic and social integration and increase
the vested energy of online students, which is crucial for their confidence and involvement in the
learning process (Astin, 1984; Ragin, 2013; Tinto, 1975; Wernersbach et al., 2014).
Howard University developed Faculty Learning Communities (FLCs), in which a diverse
group of STEM faculty participates in teaching and learning through learning about teaching
(Smith et al., 2008). Through seminars, courses, meetings and teaching experiments, the FLCs
could reflect, discuss and demonstrate capabilities of effectively teaching their online students
(Smith et al., 2008). Some of these advances may include frequent instruction and feedback to
their online students about course assignments and consistent office hours through the online
portal (Cole & Griffin, 2013; McEwen & Gueldenzoph, 2003). These efforts can create a
positive and engaging virtual environment where faculty and administrators strategize pathways
to nurturing the help-seeking, self-efficacy and goal orientations of their STEM online students,
and can help to improve their academic achievement in STEM courses (Cole & Espinoza, 2008;
Cole & Griffin, 2013).
Recommendations for Future Research
Data from this study pointed to interesting findings that could be investigated for future
research. For example, URM students’ beliefs were compared to those of their White and Asian
counterparts as a whole by combining the on-campus and online student results. Some studies
have shown Whites and Asians use electronic mail and the Internet more than URM students do;
it would be interesting to compare their academic constructs in just the online format (Ragin,
2013). A qualitative study could be conducted, interviewing the URM STEM students in both
formats to reveal their experiences with STEM faculty and peers. These interviews could
examine whether mentorships were constructed with faculty, if there were experiences with
COMMUNITY COLLEGE STUDENTS IN STEM 62

discrimination or marginalization from their non-URM classmates, and their overall perceptions
of STEM major and degree attainment from their experiences in the course. In addition, a
quantitative study could also examine whether these students pursued additional STEM courses
with open-ended questions asking why or why not.
With regard to the online and on-campus academic beliefs, a post-test could be conducted
examining whether the academic constructs of online students changed over time to align with
those of their on-campus counterparts or if they remained significantly lower. These additional
examinations can inform educational leaders on better practices for STEM talent development,
especially in the growing online program community.
Limitations
This study encountered several limitations. One distinct limitation of this study was that
the sample consisted of students taking one specific course, which may restrict the
generalizability of the findings to apply to a larger population of students taking various
technology courses. The findings about online courses are also not generalizable, as they were
contextualized for this particularly type of online delivery. The second limitation of this study
was that all findings were correlational and any statistical differences the researcher discovered
when comparing the beliefs of students in online setting with those in on-campus settings cannot
be interpreted to have a causal relationship. The third limitation to this study was social
desirability bias, which could have taken place if participants did not respond honestly, but,
rather, with answers they believed were preferred and acceptable. The fourth limitation of these
findings is that there was only one survey administered at the beginning of the course. Within
goal orientation, at times, students are intrinsically goal oriented in the beginning of the course
but become extrinsically goal oriented later on due to academic and personal pressure and stress
COMMUNITY COLLEGE STUDENTS IN STEM 63

(Elliot & Harackiewicz, 1996; Lepper & Hodell, 1989; Pintrich, 2000a). It is unknown if the
intrinsic goal orientation of students would have changed during the course of the semester and,
perhaps resulted in no significant difference between the two course delivery methods. It is also
possible that the other academic constructs could have changed in levels over time. The fifth
limitation was the reported alpha of .61 for the formal and informal help-seeking portion of the
survey instrument falling below the original alpha of .66, and below the minimum level of
acceptability of .70. This low alpha affects the quality of this portion of the study. The sixth
limitation to this study was that multicollinearity was found in several constructs, which may
impact the extent to which this model can be replicated. Future research needs a larger sample
and to consider this issue. These six limitations could have resulted in an inconclusive study with
inaccurate results and inferences.

Conclusion
The United States is falling far behind in the production of STEM college graduates.
Based on economic forecasts, in order for the U.S. to maintain its superiority in science and
technology, approximately 1 million more professionals in STEM fields are needed than what is
projected (PCAST, 2012). Therefore, STEM undergraduate degree completion needs to be
increased by about 34% each year for this goal to be reached (PCAST, 2012). In addition,
population projections predict that by 2050, minorities will grow to be the majority population in
the U.S., but their underrepresentation in STEM will continually decline unless substantial
measures are taken to improve URM talent development in STEM fields (Salto et al., 2014).
This study’s findings reveal that URM STEM student academic beliefs do not differ
much from their White and Asian peers, which can contribute to their academic success in the
course. In fact, URM STEM students in this study proved to be more intrinsically motivated to
COMMUNITY COLLEGE STUDENTS IN STEM 64

grasp an understanding of complex material and embrace their learning than were their White
and Asian counterparts, a belief that can lead to URM students choosing and graduating with a
STEM major and pursuing a promising career in the field. Educational leaders can look to this
study as an example of how culturally diverse colleges and universities can positively influence
URM student beliefs, and develop strategies that will nurture diversity among students and
faculty (Cole & Espinoza, 2008; Cole & Griffin, 2013; Hurtado et al., 2011; Ong et al., 2011;
Winston et al., 2010). It is imperative that educational leaders create positive racial climates that
foster academic and social integration, motivate students to engage in the learning experience
and encourages them to be involved and seek help from their faculty and peers (Astin, 1984;
Pintrich, 2000; Tinto, 1975; Yildiz-Feyzioglu, Akpinar, & Tatar; 2013).
Online education is rapidly growing and has been exposed to be beneficial for institutions
financially and for students in terms of flexibility (Allen & Seaman, 2014). However, this study
showed online students in a STEM course to have significantly lower academic beliefs in all
major constructs, and greater formal help-seeking beliefs than their on-campus counterparts did.
These differences pose a threat to online student retention, especially in STEM subjects and
majors. Nurturing students in all formats of STEM courses so that they may choose a STEM
major is crucial for America’s growth in the global marketplace (Moakler & Kim, 2014; PCAST,
2012). In doing so, the U.S. will position itself as a strict competitor in the global economy and
workforce, preventing the rise of outsourcing STEM professionals (Hurtado et al., 2009; PCAST,
2012). The growing number of URM individuals in the U.S. and, specifically, in URM students
entering college, combined with the rapid growth of online courses, calls for higher education
institutions to place special emphasis on strategies to recruit and retain online and URM students
COMMUNITY COLLEGE STUDENTS IN STEM 65

towards STEM pathways so that they may contribute to the national need of STEM professionals
(Hurtado et al., 2009).
COMMUNITY COLLEGE STUDENTS IN STEM 66

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Appendix A
Demographic Questions
1. What is your gender?
a. Male
b. Female
c. Transgender

2. What is your age in years?

3. What is your current employment status?
a. Not currently working
b. Working part-time
c. Working full-time

4. Please choose indicate your ethnicity.
a. American Indian or Alaska Native
b. Asian
c. Black or African American
d. Hispanic/Latino
e. Native Hawaiian or other Pacific Islander
f. White
g. Two or more races
h. Other (Please specify)

5. Please indicate your relationship status
a. Single
b. Married/Domestic Partner
c. Separated/Divorced
d. Widowed

6. What is the highest level of education completed by either of your parents and guardians?
a. Primary school or less
b. Middle school
c. Some high school
d. High school
e. Associate Degree/Certificate
f. Some college
g. Bachelor’s Degree
h. Master’s Degree
i. Doctoral Degree

7. What is your major?

8. How many units are you currently enrolled in?
COMMUNITY COLLEGE STUDENTS IN STEM 76

9. How many diversity or multicultural classes you have taken in higher education?
a. 0
b. 1
c. 2
d. 3+

10. Do you have a previous graduate degree?
a. Yes
b. No

11. How many online courses have you taken for college credit prior to this course?

COMMUNITY COLLEGE STUDENTS IN STEM 77

Appendix B
Help-Seeking Beliefs
Beliefs: MSLQ Subsection (Pintrich et al., 1991)

• Even if I have trouble learning the material for this class, I try to do the work on my own,
without help from anyone (REVERSED);
• I ask the instructor to clarify concepts I don’t understand well;
• When I can’t understand the material in this course, I ask another student in this class for
help; and
• I try to identify students in this class whom I can ask for help if necessary.
Formal Versus Informal Beliefs: Questionnaire Subsection (Karabenick, 2003)
• If I were to seek help in this class I would ask the teacher rather than another
student;
• I would prefer asking another student for help in this class rather than the
instructor (REVERSED); and
• In this class, the teacher would be better to get help from than would a
student.

COMMUNITY COLLEGE STUDENTS IN STEM 78

Appendix C
Self-Efficacy Beliefs
MSLQ Subsection (Pintrich et al; 1991)

• I believe I will receive an excellent grade in this class;
• I’m certain I can understand the most difficult course material presented in the readings
for this course;
• I’m confident I can understand the basic concepts taught in this course;
• I’m confident I can understand the most complex material presented by the instructor in
this course;
• I’m confident I can do an excellent job on the assignments and tests in this course;
• I expect to do well in this class.
• I’m certain I can master the skills being taught in this class; and
• Considering the difficulty of this course, the teacher, and my skills, I think I will do well
in this class.
COMMUNITY COLLEGE STUDENTS IN STEM 79

Appendix D
Intrinsic and Extrinsic Goal Orientation
MSLQ Subsection (Pintrich et al., 1991)

Value Component: Intrinsic Goal Orientation:
• In a class like this, I prefer course material that really challenges me so I can learn new
things;
• In a class like this, I prefer course material that arouses my curiosity, even if it is difficult
to learn;
• The most satisfying thing for me in this course is trying to understand the content as
thoroughly as possible; and
• When I have the opportunity in this class, I choose course assignments that I can learn
Value Component: Extrinsic Goal Orientation:
• Getting a good grade in this class is the most satisfying thing for me right now;
• The most important thing for me right now is improving my overall grade point average,
so my main concern in this class is getting a good grade;
• If I can, I want to get better grades in this class than most of the other students; and
• I want to do well in this class because it is important to show my ability to my family,
friends, employer, or others

Abstract (if available)

Abstract In order to compete with the global economy and workforce, and to prevent the rise of outsourcing careers in science, technology, engineering, and mathematics (STEM) to other countries, the U.S. needs to develop professionals in STEM fields (Hurtado, Cabrera, Lin, Arellano & Espinosa, 2009

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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

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Validation matters - student experiences in online courses: a mixed method study

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

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Mathematics, Engineering, Science, Achievement (MESA) and student persistence in science, technology, engineering, and mathematics (STEM) activities and courses: the perceptions of MESA teacher a...

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An examination of factors that affect post-traditional undergraduate student persistence

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Faculty development curriculum to facilitate discourse in the online space

Asset Metadata

Creator Valizadeh, Nooshin (author)

Core Title Community college students in STEM: a quantitative study investigating the academic beliefs of students enrolled in online and on campus information technology courses

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 04/08/2015

Defense Date 03/24/2015

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

Tag academic beliefs,community college,extrinsic,goal orientation,help‐seeking,Higher education,information technology,intrinsic,OAI-PMH Harvest,online education,self‐efficacy,STEM,underrepresented minority students

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Hirabayashi, Kimberly (committee chair), Seli, Helena (committee chair), Cole, Darnell G. (committee member)

Creator Email nooshinv3@gmail.com,valizade@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-543177

Unique identifier UC11297897

Identifier etd-ValizadehN-3254.pdf (filename),usctheses-c3-543177 (legacy record id)

Legacy Identifier etd-ValizadehN-3254.pdf

Dmrecord 543177

Document Type Dissertation

Format application/pdf (imt)

Rights Valizadeh, Nooshin

Type texts

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

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA