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Student academic self‐efficacy, help seeking and goal orientation beliefs and behaviors in distance education and on-campus community college sociology courses

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Student academic self‐efficacy, help seeking and goal orientation beliefs and behaviors in distance education and on-campus community college sociology courses

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Content Running head: SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 1 STUDENT ACADEMIC SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION BELIEFS AND BEHAVIORS IN DISTANCE EDUCATION AND ON-CAMPUS COMMUNITY COLLEGE SOCIOLOGY COURSES. by Hollie Luttrell 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 August 2015 Copyright 2015 Hollie Luttrell SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 2 Acknowledgements I would like to express my sincere gratitude to those who generously gave their time in order to support me in this endeavor. To my chairperson, Dr. Kimberly Hirabayashi and to Dr. Helena Seli my committee co-chair who generously gave their time, great advice, support, insight, scaffolding and guidance. To Dr. Lesilie Tirapelle, an invaluable member of my committee, who encouraged me to begin the program in the first place, and saw me through to the conclusion. I would also like to extend a special thanks to family and friends. I am especially humbled by the love, support, understanding, and encouragement extended to me by my amazing husband and daughter during this process. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 3 Table of Contents Acknowledgements 2 Abstract 6 CHAPTER ONE: INTRODUCTION 7 Background of the Problem 8 Statement of the Problem 12 Purpose of the Study 12 Research Questions 12 Significance of the Study 13 Methodology 13 Definition of Terms 14 Organization of the Study 15 CHAPTER TWO: LITERATURE REVIEW 16 Description and History of Distance and Online Education 16 The Community College and the Flexibility of Online Education 17 Retention and Learning Outcomes in Online Education 19 Academic Self-Efficacy 20 Importance of Self-Efficacy 21 Sources of Self-Efficacy 23 Measurement of Self-Efficacy 24 Challenges to Self-Efficacy 26 Help Seeking 28 Importance of Help Seeking 28 Help Seeking Categories 29 Help Seeking Threat and the Impact of Technology on Help Seeking 30 Measurement of Help Seeking 32 Goal Orientation 32 Intrinsic and Extrinsic Goal Orientation 33 Approach and Avoidance Goal Orientations 34 Importance of Goal Orientation 35 Measurement of Goal Orientation 36 Conclusion 37 CHAPTER THREE: METHODS 39 Research Questions 39 Research Design 40 Population and Sample 40 Instrumentation 41 Demographic Questions 41 Help Seeking 42 Goal Orientation 44 Procedure and Data Collection 45 Data Analysis 45 CHAPTER FOUR: RESULTS 47 Descriptive Characteristics of Respondents 48 Demographic Information 48 SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 4 Analysis of Results 53 Conclusion 62 CHAPTER FIVE: DISCUSSION 64 Student Characteristics and the Learning Context 65 Discussion of Motivational Factors Across Course Delivery Modes 66 Implications 70 Recommendations for Future Research 73 Limitations 73 Conclusions 76 References 78 Appendix A Letter of Informed Consent 89 Appendix B Recruitment Script 91 Appendix C Demographic Questions 92 Appendix D Summary of Research questions, Variables and Analysis 103 SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 5 List of Tables Table 1 Participant Demographics: Age 49 Table 2 Differences in Enrollment in Units Between Modes of Course Delivery 49 Table 3 Participant Demographics: Gender 50 Table 4 Participant Demographics: Number of Online Courses Taken Previously 51 Table 5 Participant Demographics: Employment Status 51 Table 6 Participant Demographics: Reasons for Selecting Course Delivery Mode 52 Table 7 Participant Demographics: Ethnicity 53 Table 8 Pearson Product Correlations of Measured Variables 55 Table 9 t-Test Comparing Mean Help Seeking Between Course Delivery Modes 56 Table 10 t-Test Formal and Informal Help Seeking Between Course Delivery Modes 57 Table 11 t-Test Comparing Help Seeking Frequency Between Course Delivery Modes 57 Table 12 t-Test Intrinsic Goal Orientation Between Course Delivery Modes 58 Table 13 t-Test Extrinsic Goal Orientation Between Course Delivery Modes 59 Table 14 t-Test Academic Self-Efficacy Between Course Delivery Modes 59 Table 16 Multiple Regression: Self-Efficacy, Help Seeking, Goal Orientation 61 Table 17 Multiple Regression: Effect of Goal Orientation on Help Seeking 62 SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 6 Abstract The purpose of this study was to investigate academic self-efficacy, help seeking and goal orientation beliefs and behaviors in online versus on-campus learning settings among a community college student population enrolled in a first-year, college-level introductory sociology course. Gateway courses such as introductory sociology are a requirement for a great number of undergraduate students who wish to take more advanced courses, earn a degree or transfer to a four-year university. Due to the demand for both online courses and gateway courses such as introductory sociology at the community college level, it is of particular interest to study the differences in student academic motivational constructs in online and traditional course formats. The findings indicate that there are no statistically significant differences between students’ academic self-efficacy, help seeking, or goal orientation across course delivery methods. The study did find relationships between students’ academic motivational factors such as goal orientation and help seeking. The study also found correlations between student characteristics. For example, most students who were enrolled in an online course had previously taken at least one online course, and as the number of units in which students were enrolled increased, their reported employment status, academic self-efficacy, intrinsic goal orientation and satisfaction decreased. The implications of this study can serve to inform instructors, professional development and instructional designers as to students’ needs and how to best design support and interventions that foster academic motivation, which can positively affect student learning and success. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 7 CHAPTER ONE: INTRODUCTION Advancements, increased availability, and decreased cost of technology all led to the proliferation of and increased demand for online courses in recent years (Castle & McGuire, 2010; Lou, Bernard, & Abrami, 2006; Tamim et al., 2011). These effects are more pronounced at the community college level than they are at universities (Hachey, Wladis, & Conway, 2014; Taver, Volchok, Bidjerano, & Shea, 2014; Xu & Jaggars, 2011). This is due, in part, to the fact that, when compared with the number of students in attendance, community colleges offer a disproportionately larger amount of all online education courses. Nearly 97% of community colleges offer courses online compared with 66% of all colleges and universities (Hachey et al., 2014; Parsad & Lewis, 2008; Xu & Jaggars, 2011). While approximately 30% of all post- secondary students attend community colleges (Allen & Seaman, 2013; American Association of Community Colleges, 2014; National Student Clearinghouse Research Center, 2013), nearly 50%, of all online education courses are offered through community colleges (Hachey et al., 2014; Parsad & Lewis, 2008; Taver et al., 2014; Xu & Jaggars, 2011). Introductory sociology is one of the options students can select in partial fulfillment of the nine units of the Social and Behavioral Science (IGETC Subject Area 4) courses required of college students across all majors and fields of study (California Community Colleges Student Success Task Force, 2012). This beginning college-level course is usually taken during the first year of college and serves as a prerequisite for other courses within the curriculum. A significant number of post-secondary students begin their college careers with courses at community colleges (Bers, 1994; Delveccio, 2001; Jenkins, Speroni, Belfield, Jaggars, & Edgecombe, 2010), and many take the course in an online format (Xu & Jaggars, 2013). Having established that most first year college students are required to take certain entry-level courses (Bers, 1994; Del SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 8 Veccio, 2001; California Community Colleges Student Success Task Force, 2012; Jenkins et al., 2010; Volpe, 2011), and that many elect to take online courses at community colleges (Hachey et al., 2014; Parsad & Lewis, 2008; Xu & Jaggars, 2011, 2013; Taver et al., 2014), it bears noting the factors that can have an impact on this student population’s success. Students’ learning, satisfaction and performance in both online and traditional courses is affected by motivational beliefs (Karabenick, 2011; Puzziferro, 2008) and self-regulatory behaviors, (Cheng, Liang, & Tsai, 2013; Dabbagh & Kitsantas, 2013) students’ academic self-efficacy (Bates & Khasawneh, 2007; Hodges & Murphy, 2009; Puzziferro, 2008; Smith, 2002), help seeking behaviors (Cheng et al., 2013; Karabenick, 2003, 2011; Kitsantas & Chow, 2007) and goal orientation (Dabbagh & Kitsantas, 2013). It is, therefore, important to examine community college students’ beliefs and behaviors in online introductory sociology courses. Background of the Problem Due to its proliferation in the educational landscape, online education is an important topic, which warrants study. In the decade between 2002 and 2012 alone, there was an increase of almost 22% in online programs at post-secondary institutions (Allen & Seaman, 2013). As of 2012, almost seven million college students were taking at least one course online (Allen & Seaman, 2013; Hachey et al., 2014). As noteworthy as online education is, it is especially significant at the community college level. Community college students are more likely to be nontraditional, low income, and of a minority background than are students attending four-year colleges and universities (Provasnik & Planty, 2008), and, as such, community college students are more likely to take online courses due to the ease of access and flexibility of scheduling (Capra, 2014; Chen, Lambert, & Guidry, 2010; Hachey et al., 2014). Many studies focused on low retention rates in online courses (Chen, SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 9 2013; Clay, Rowland, & Packard, 2009; Hachey et al., 2014; Volpe, 2011). Low retention rates are also of concern among the nontraditional, low income students, of minority backgrounds, who make up much of the community college population and the online student population (Grimes, 1997; Hawley, & Harris, 2005). There are longstanding concerns regarding quality control in online education (Lorenzo & Moore, 2002; Schweizer, Whipp, & Hayslett, 2003). Numerous studies produced evidence that modes of online education are just as good as traditional modes of education (Clark & Feldon, 2005; Clark, Yates, Early, Moulton, Silber, & Foshay, 2010; Rabe-Hemp, Woollen, & Humiston Sears, 2009; Robinson & Hullinger, 2008; Tamim et al., 2011; Xu & Jaggars, 2011). In spite of the research in support of online education, there continues to be concerns over a lack of consistency, assessment, and quality control where online courses are concerned (Boston, Ice, & Gibson, 2011; Lorenzo & Moore, 2002; Parker, 2011; Schweizer et al., 2003). One factor that raises the question of quality in online education is the move from synchronous to asynchronous methods of delivery (Lorenzo & Moore, 2002). Proximity to the instructor and small student to teacher ratios historically meant that the student had more access to the instructor and, therefore, long served as a measure of educational quality (Chen et al., 2010; Clark & Feldon, 2005; Lorenzo & Moore, 2002). The more contact a student has with an instructor, the better the chance of learning (Cheng et al., 2013; Lorenzo & Moore, 2002). Synchronous modes of delivery allow for student and teacher to interact in real time (Campbell, Gibson, Hall, Richards, Callery, 2008; Chen et al., 2010; Lou et al., 2006). With asynchronous modes of delivery, there is spatial and temporal distance between teacher and student (Campbell et al., 2008; Chen et al., 2010; Lou et al., 2006). This distance implies that there may be a loss of SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 10 interaction between student and teacher, and therefore a degradation of the quality of education in online courses (Chen et al., 2010; Clark & Feldon, 2005; Lorenzo & Moore, 2002). Mitigating factors that reduce the affects of distance between student and teacher in online courses, are students’ own motivational and self-regulatory strategies (Chen et al., 2010; Clark & Feldon, 2005). For example, when students have questions or encounter difficulties with academic work, those who have positive academic self-efficacy beliefs tend to set goals and exhibit help seeking behaviors that lead to deeper learning and can lead to improved performance when compared to students who do not exhibit positive beliefs and behaviors (Chen et al., 2010; Clark & Feldon, 2005). Much attention focused on comparing quality of online education (Brown, 2013), learning (Muilenburg & Berge, 2005; Rabe-Hemp, Woollen & Humiston, 2009), achievement outcomes such as grades (Bernard, Abrami, Borokhovski, Wade, Tamim, Surkes, & Bethel 2009; Campbell et al., 2008; Castle & McGuire, 2010;), satisfaction (Picciano, Seaman & Allan, 2010; Rabe-Hemp et al., 2009) and retention (Xu & Jaggars, 2011) in online versus traditional learning contexts (Clay & Packard, 2009). Research and analysis of aspects of student learning in online contexts includes student engagement (Rabe-Hemp et al., 2009; Robinson & Hullinger, 2008), impact (Tamim et al., 2011) and effectiveness of technology (Clark & Feldon, 2005; Clark et al., 2010; Xu & Jaggars, 2011). Several researchers investigated online learning at the community college level specifically (Hachey et al., 2014; Taver et al., 2014; Xu & Jaggars, 2011). Some studies focus on the community college population (Chen, 2013) with respect to math (Xu & Jaggars, 2011) and learning English in online contexts (Bers, 1994; Chen, 2013; Del Veccio, 2001) and remediation or learning English as a Second Language (Bers, 1994; Jenkins et al., 2010). The bulk of the research comparing online and traditional classroom settings focused SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 11 on outcomes rather than motivational constructs such as academic self-efficacy, help seeking and goal orientation in online contexts (Del Veccio, 2001; Homan, 2003; Montagne, 2012). Researchers also explored motivational issues such as self-efficacy (DeTure, 2004; Hodges & Murphy, 2009; Lee & Ching, 2014; Lee & Mendlinger, 2011; Orzan, Gundogdu, Bay, & Celkan, 2012; Puzziferro, 2008; Savoji, 2013; Wang, Shannon, & Ross, 2013; Zhan & Mei, 2013), help seeking behaviors (Stahl & Bromme, 2009; Taplin, Yum, Fan, & Chan, 2001) and goal orientation (Remedios & Richardson, 2013) in online learning contexts. A paucity of research exists when it comes to the consideration of the differences in motivational beliefs and behaviors of community college students in different learning environments (Aragon & Johnson, 2008; Hachey et al., 2014; Halsne, 2002; Savoji, 2013; Wang et al., 2013; Xu & Jaggars, 2011). Many studies note the need for more research that explores motivational beliefs (Savoji, 2013; Stahl & Bromme 2009) and self-efficacy (Bates, 2007; Hodges, 2009; Wang et al., 2009) of college students in online learning contexts (Aragon & Johnson, 2008; Hachey et al., 2014; Halsne, 2002; Savoji, 2013; Wang et al., 2013; Xu & Jaggars, 2011). Still others called for further investigation of help seeking behaviors to enhance the quality of the distance education experience for college students (Kitsantas & Chow, 2007; Nistor, Schwormd, & Werner, 2012; Stahl & Bromme 2009; Taplin et al., 2001). There has also been a call for additional inquiry into the role that goal orientation plays in college students’ learning in online and traditional classroom settings (Bernacki, Byrnes, & Cromley, 2011). Positive motivational beliefs and behaviors can lead to deeper learning, improved outcomes, greater satisfaction and higher retention among community college students in online and traditional learning contexts (Cho & Shen, 2013; Harackiewicz, Barron, Pintrich, Elliot, & Thrash, 2002; Remedios & Richardson, 2013). Due to the impact that academic self-efficacy, SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 12 help seeking, and goal orientation can have on student success, it is important to study motivational beliefs and behaviors of community college students in online and traditional learning contexts. Statement of the Problem There is a significant amount of research pertaining to retention rates in online courses and comparisons of learning via outcomes in online versus traditional learning environments. Research that focuses on motivational beliefs and behaviors such as academic self-efficacy, help seeking and goal orientation serves to illuminate reasons for low retention rates and may lead to solutions. However, there is a lack of understanding of motivational factors in distance education owing to a scarcity of research pertaining to beliefs and behaviors such as development of academic self-efficacy, academic help seeking, and goal orientation by mode of delivery among community college students. Purpose of the Study The purpose of this study was to assess academic self-efficacy, help seeking and goal orientation beliefs and behaviors in online versus on-campus learning settings among the community college student population. This research examined motivational beliefs and behaviors of students enrolled in a first-year, college-level introductory sociology course. The study was conducted in a community college setting. Research Questions Within this study, the following research questions were examined and answered: 1. Is there is a difference in student help seeking by course delivery method among community college students? SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 13 2. Is there is a difference in student goal orientation by course delivery method among community college students? 3. Is there is a difference in student academic self-efficacy by course delivery method among community college students? 4. Do academic self-efficacy, intrinsic and extrinsic goal orientations predict help-seeking, controlling for course delivery method? Significance of the Study The answers to the research questions are relevant to the field of online education in that examination of motivational beliefs and behaviors may determine influences in student persistence, learning and performance in learning contexts. By understanding the potential impact of motivational beliefs and behaviors on student learning, educators can ensure these components are designed into courses to improve course quality as well as student learning, retention and performance. Answers to the research questions are of particular significance in the context of community colleges due to the fact that almost 50% of all online education courses are offered through community colleges (Hachey et al., 2014; Parsad & Lewis, 2008; Xu & Jaggars, 2011; Taver et al., 2014). Methodology Since the research questions sought to compare learning and motivation in two different settings, online and on-campus, the researcher adopted a quantitative approach. The quantitative approach was used determine whether statistical differences or predictive relationships exist. Data was gathered via surveys that include valid and reliable instruments such as the Motivated Strategies Learning Questionnaire (MSLQ) and demographic questions. Surveys were SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 14 administered online. All data was analyzed in SPSS using statistical tests including t-test, and correlation. Definition of Terms Asynchronous. Mode of delivery in which participants are not required to be available at a specified time (Campbell et al., 2008). Distance education. A broad term used to describe a structured educational process where student and teacher are not in the same place at the same time (Bernard et al., 2009). Goal orientation. Refers to students’ intentions, by choosing to engage in a learning activity (Pintrich, 2003). Extrinsic goal orientation or performance goal orientation. Describes when a student is motivated to engage in an academic task in order to earn a reward, such as a good grade or to avoid penalty (Pintrich, 2004). Intrinsic goal orientation or mastery goal orientation. Describes when a student is internally motivated to engage in an academic task for the sake of learning, mastery, challenge, curiosity or satisfaction of accomplishing the task (Pintrich, 2004). Help seeking. In academic settings, help seeking is the term used to describe students’ actions when they pursue assistance or support and put into action approaches to accomplish academic tasks (Karabenick, 2003). Online education. A specific subset of distance education, referring to courses where the content is delivered via the Internet, and all interaction between students and teacher is done online, rather than face-to-face (Chen et al., 2010). SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 15 Academic self-efficacy. An individual’s belief in his/her own academic competencies to form and implement the sequence of events necessary to handle future circumstances (Bandura, 1993,1995). Synchronous. Mode of delivery in which students interact in real time (Campbell et al., 2008). Organization of the Study Chapter One in this study provides an overview of the proposed study as well as an introduction to the topic of distance education and motivational factors such as academic self- efficacy, help seeking, and goal orientation. Factors that may influence motivation are discussed, as are the theoretical frameworks that will be analyzed later in this study. This section also discusses the importance of the study, potential limitations, and gives definitions of relevant terms. Chapter Two provides an in-depth look at distance education, including a history of distance education with a focus on community college students. This chapter also examines and compares components found to influence motivational indices between traditional and online contexts. These factors include academic self-efficacy, academic help seeking and goal orientation. Chapter Three describes the methodology used in this study. This chapter discusses the sample used, instrumentation, research design, and data collection process. Also described are data analysis and as well as the strengths and weaknesses of this study. Chapter Four is a description of the results from the data analysis. Chapter Five is a discussion of these results, in addition to the limitations of the study and suggestions for future research. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 16 CHAPTER TWO: LITERATURE REVIEW This literature review examines several constructs related to learning in online contexts. Research reviewed focuses on undergraduate and community college students, with a particular emphasis on academic self-efficacy, help seeking and goal orientation. Description and History of Distance and Online Education Distance education refers to formal learning contexts where instructor and student are not in the same place. There is also a temporal distance between teacher and student in distance education. Online education is a specific branch of distance education where the Internet serves as a mode of delivery and communication (Campbell et al., 2008; Chen et al., 2010; Holmberg, 2005, Lou et al., 2006). Early versions of correspondence school included only asynchronous communication through the mail (Bernard et al., 2009; Lou et al., 2006). In 1913, Thomas Edison recognized the potential to deliver educational content through motion pictures and famously predicted that books would be soon obsolete and that education would be changed forever (Tamim, Bernard, Borokhovski, Abrami, & Schmid, 2011). While the changes were not as dramatic as Edison predicted, visual media did have an impact on education (Bernard et al., 2009; Lou et al., 2006; Tamim et al., 2011). In addition to traditional asynchronous delivery methods for educational materials, audio, video and television allowed students to see instructors speak and demonstrate content (Bernard et al., 2009; Lou et al., 2006). Through video and audio, students could hear voice inflections and see facial expressions, making content more engaging (Bernard et al., 2009; Campbell et. al., 2008; Lou et al., 2006). Rapid technological advancement gave way to online education and made distance education progressively more accessible to a wider audience while lowering the cost, increasing SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 17 efficiency and effectiveness (Bernard et al., 2009; Lou et al., 2006; Tamim et al., 2011). More recently, Internet access is available to over three billion people worldwide, which translates to more than 40% of the world population, with a 741% growth of Internet access between 2000 and 2014 (Internet World Stats, 2014). Even in locales where the infrastructure for land telephone lines and electricity are scarce and outmoded, multi-purpose web enabled devices and satellite technology make it possible for students to engage with content where they are, not solely when they are in a physical classroom (Robinson & Hullinger, 2008). Online course offerings at post-secondary institutions are standard as demand for distance education steadily increases (Allen & Seaman, 2013), and “distance education” is a broad term used to describe a structured educational process where student and teacher are not in the same place at the same time (Bernard et al., 2009; Clark & Feldon, 2005; Lou et al., 2006; Parsad & Lewis, 2008). Online education, a specific subset of distance education, refers to courses where the content is delivered via the Internet and all interaction between students and teacher is done online, rather than face-to-face (Chen et al., 2010). Between 2002 and 2012, there was an increase of almost 22% in online programs at post-secondary institutions. In 2012, almost 7 million college students were taking at least one course online (Allen & Seaman, 2013; Hachey et al., 2014). The Community College and the Flexibility of Online Education The increased demand for online education at community colleges is more pronounced than it is at universities (Hachey et al., 2014; Taver et al., 2014; Xu & Jaggars, 2011). While community colleges serve 30% of the post-secondary student population (Allen & Seaman, 2013; American Association of Community Colleges, 2014; National Student Clearinghouse Research Center, 2013), approximately half of all online education courses are offered through SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 18 community colleges, and approximately 97% of community colleges offer courses online compared with 66% of all colleges and universities that offer online courses (Hachey et al., 2014; Parsad & Lewis, 2008; Xu & Jaggars, 2011). The demand for online education can be attributed to several factors including advancements in technology, increased availability of technology, decreased cost of technology, improved perceptions of the overall quality of distance education (Castle & McGuire, 2010; Lou et al., 2006; Tamim et al., 2011). Above all, the flexibility that distance education offers to students is chief among the reasons for the increase in demand for distance education courses and programs (Castle & McGuire, 2010; Lou et al., 2006; Tamim et al., 2011). From early correspondence courses to current web-based courses, the most significant advantage of distance education is that there is no longer the need to be physically present at the institution offering the course, and participation in online courses is not predicated on physical presence in a specified location (Bagayoko, Perrin, Gagnon, & Geissbuhler, 2013; Brown, 2012; Campbell et al., 2008; Castle & McGuire, 2010; Clark & Feldon, 2005; Lou et al., 2006; Picciano, Seaman, & Allen, 2010). In the case of asynchronous courses, participants are not required to be available at a specified time (Campbell et al., 2008; Chen et al., 2010; Lou et al., 2006). By allowing students the flexibility to decide the days and times they will dedicate to coursework, participants are better able to accommodate family, work and other educational responsibilities, as well as participate from remote time zones (Bagayoko et al., 2013; Brown, 2012; Picciano et al., 2010). While at least a third of all college students take an online class, the flexibility of online education is especially attractive to the non-traditional student who tends to have work and family responsibilities and is older than the traditional student (Capra, 2014). As compared to SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 19 face-to-face courses, a higher ratio of underprepared, at-risk, part-time and minority students enroll in online education courses (Chen et al., 2010; Hachey et al., 2014). Consequently, the typical profile of students taking online courses also implies lower retention rates than face-to- face courses (Picciano et al., 2010; Clay et al., 2009; Taver et al., 2014). The following section will review literature related to retention in online education. Retention and Learning Outcomes in Online Education Retention rates for online courses are reported to be 20% to 80% lower than traditional courses, and researchers posited that reasons for low retention in online courses might include students’ lack of academic preparedness and greater need for support (Clay et al., 2009; Taver et al., 2014; Xu & Jaggars, 2011; Brown, 2012). High attrition rates in online courses may also be due to students’ lack of self-regulatory skills (Rabe-Hemp et al., 2009; Allen & Seaman, 2013). Students may put forth less mental effort due to the perception that media enhanced courses such as online courses are less demanding, which may contribute to high drop out rates (Clark & Feldon, 2005). One measure of the quality of education is the amount of interaction between student and teacher; increased interaction in the form of close proximity and small class size has traditionally been an indication of high quality (Chen et al., 2010; Clark & Feldon, 2005). By definition, online education is a structured educational process where student and teacher are not in the same place at the same time (Bernard et al., 2009; Clark & Feldon, 2005; Lou et al., 2006; Parsad & Lewis, 2008). The convenience and flexibility of online education comes at the cost of the perceived quality of the education received (Brown, 2012; Campbell et al., 2008; Castle & McGuire, 2010; Clark & Feldon, 2005; Lou et al., 2006; Picciano et al., 2010). Online education has historically taken advantage of advances in technology to increase interaction between SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 20 teacher and student, and thereby improved the perceived quality of online education (Bernard et al., 2009; Campbell et al., 2008; Lou et al., 2006). Evidence shows there is no significant difference in learning outcomes between regular, face-to-face instruction and online instruction (Clark & Feldon, 2005; Clark et al., 2010; Rabe- Hemp et al., 2009; Robinson & Hullinger, 2008; Tamim et al., 2011; Xu & Jaggars, 2011). Some researchers suggested that, with proper instructional design, student engagement increases in online education courses (Castle & McGuire, 2010; Chen et al., 2010). Many who investigated the topic of learning in online contexts suggest that improved outcomes and learning are not explained by media, but, rather, by sound instructional design (Bernard et al., 2009; Castle & McGuire, 2010; Clark & Feldon, 2005; Clark et al., 2010; Lou et al., 2006; Tamim et al., 2011). In summary, online course offerings at post-secondary institutions are standard as demand for distance education steadily increases, and participation in online courses is not predicated on physical presence in a specified location, which is well suited to the predominantly nontraditional student population at community colleges. The increased demand for online education at community colleges is more pronounced than at universities. Online education evolved with technology to improve and meet the demands of a diverse, growing population of college students. Still, there are other considerations with respect to students’ success in online learning contexts. Academic Self-Efficacy The section that follows describes and discusses academic self-efficacy in terms of influences, importance, measurement and challenges. Self-efficacy is a construct that falls under the umbrella of social cognitive theory (Bandura, 1993, 2006, 2012; Ozan, 2012; Pajares, 1996, 1997; Zimmerman, 2000). Bandura (1995) describes self-efficacy as an individual’s belief in SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 21 his/her own competencies to form and implement the sequence of events necessary to handle future circumstances. Self-efficacy influences the choices learners make, the effort they put forth and how long they will persist when confronted with obstacles or even failure (Bandura, 1993, 2012; Pajares & Schunk, 2001; Zimmerman, 2000). Importance of Self-Efficacy Academic self-efficacy proved to be an extremely successful predictor of learning (Bandura, 1993, 2006, 2012; Pajares 1996, 1997; Zimmerman, 2000). As such, academic self- efficacy is affected by students’ performance context, is related to self-regulated learning processes, and mediates students’ academic achievement (Bandura, 1993, 2006, 2012; Pajares 1996, 1997; Zimmerman, 2000). Self-efficacy speaks to a person’s belief in his/her capability to perform a task (Bandura, 1993, 2006, 2012; Choi, 2005; Pajares, 1996, 1997; Zimmerman, 2000). Learners who believe in their ability to successfully perform a task are likely to choose to engage in that task and to persist in the face of obstacles or even failure (Bandura, 1993, 2006; Pajares, 1996, 1997). Conversely, learners who do not believe in their ability to succeed at a task are less likely to choose to engage in the task and less likely to persist (Bandura, 1993, 2006; Pajares, 1996, 1997). Without positive academic self-efficacy, an individual is unlikely to engage in the academic process, and, therefore, neither learning nor achievement of academic attainment can result (Bandura, 1993, 2006; Pajares, 1996, 1997). Self-efficacy influences feelings, and speaks to what an individual believes s/he can accomplish in a given context and domain (Bandura, 2006). As a context-specific assessment of competence to perform a specific task in a given domain, self-efficacy is a judgment of confidence (Bandura, 2012; Choi, 2005; Zimmerman, 2000). Self-efficacy is context sensitive, SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 22 task specific, domain specific, and has to do with a person’s beliefs regarding whether or not they can do something (Bandura, 2012; Choi, 2005). Outcome expectations and self-efficacy differ in that the former speak to what an individual believes will be the result of his/her actions (Pajares, 2009). Self-efficacy is what an individual believes s/he can do with respect to a particular task (Bandura, 1995; Choi, 2005; Pajares, 2009). Outcome expectations can be cultivated by self-efficacy in that individuals who are assured in their skills will anticipate positive outcomes, and those who do not have confidence in their skills will expect negative outcomes (Pajares 1996). When there is a discrepancy between an individual’s outcome expectations and self-efficacy, the latter is a better predictor of behavior (Pajares, 1996). Students’ learning in both traditional courses as well as online courses can be explained in part by their motivational beliefs in that task value and academic self-efficacy are predictors of academic achievement in online leaning (Savoji, 2013). Students with high academic self- efficacy are more prone to feel that online learning is effortless and more worthwhile than are students with low self-efficacy (Lee & Mendlinger, 2011). While students’ learning in both online and traditional courses is affected by academic self-efficacy, beliefs pertaining to online technologies or computer self-efficacy can also affect students’ learning, satisfaction and performance (Bates & Khasawneh, 2007; Hodges & Murphy, 2009; Puzziferro, 2008; Smith, 2002). Computer self-efficacy is a student’s belief in his/her ability to use a computer (Smith, 2002). Online technologies self-efficacy pertains to a student’s judgment of his/her capability to use not only a computer, but also the learning management system and tools necessary to succeed in an online course (Lee & Mendlinger, 2011; Puzziferro, 2008; Wang et al., 2013). Students with high online technologies self-efficacy tend to have SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 23 higher task value for online learning, put more time and effort into learning in online contexts, and have higher satisfaction in online courses (Bates & Khasawneh, 2007; Lee & Mendlinger, 2011; Puzziferro, 2008; Wang et al., 2013). Sources of Self-Efficacy There are several influences that affect the development of self-efficacy. Self-efficacy can be developed from mastery experiences, vicarious experiences, verbal persuasion and physiological states (Bandura, 1993, 2006, 2012; Pajares, 1996, 1997). The following few paragraphs discuss each of these influences and their impact on an individual’s cultivation of self-efficacy. The strongest influences on self-efficacy are mastery experiences, where an individual experiences success in a task. When an individual succeeds at a task in a particular domain, belief in his/her own ability develops in such a way that s/he is more likely to engage in the task again, approach the task with tranquility and composure, and work harder, rather than retreat when a hurdle, obstacle or even failure is encountered (Bandura, 1993, 2006, 2012; Pajares, 1996, 1997). While less effective than mastery experiences, peer modeling has a powerful effect on the formation of self-efficacy, and when individuals observe a peer engaged in a task, they associate their peer’s performance with their own success or failure. Through vicarious experience of others, individuals formulate beliefs regarding their own capabilities; therefore, peer modeling is an effective means for developing self-efficacy (Bandura, 1993, 2006, 2012; Pajares, 1996, 1997). Verbal persuasion in the form of feedback, for example, can influence self-efficacy, as such feedback can come from family, peers, instructors, grades, or cultural influences. The type, SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 24 content and quality of feedback as well as the age of the individual are all factors that determine the impact of the verbal persuasion on an individual’s self-efficacy. Individuals tend to be more susceptible to and more heavily influenced by negative verbal persuasion that negatively affects self-efficacy than positive verbal persuasion and attempts to positively affect self-efficacy. It is less difficult to produce negative beliefs about ability to perform a task and more difficult to convince an individual that they can perform a task (Bandura, 1993, 2006, 2012; Pajares, 1996, 1997). Affect, mood, and feelings about one’s physiological state are also strong influences on self-efficacy. In addition, feelings of good health, good mood, and optimistic feelings are affiliated with positive self-efficacy, and negative affect, feelings of poor health, sadness, depression, despair, anxiety and stress are associated with negative self-efficacy (Bandura, 1993, 2006, 2012; Pajares, 1996, 1997). Students who believe the ability to learn online is malleable, can be changed, and it is a skill that can be learned and developed have higher self-efficacy related to learning in online contexts. Conversely, students who believe the ability to learn online is static, cannot be changed, learned or developed, have more anxiety about learning online, less previous success, and low self-efficacy related to learning in online contexts (Bates & Khasawneh, 2007). Measurement of Self-Efficacy Due to the important role that self-efficacy plays in learning in both traditional and online contexts, many researchers sought to identify effective measures of self-efficacy in an effort to better understand self-efficacy beliefs (Bandura, 2006). Researchers found that the measure to be used depends on the context in which self-efficacy is being studied (Bandura, 2006; Pajares, SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 25 1996). The following section reviews literature pertaining to widely used measures of self- efficacy. There is no single measure of self-efficacy that is applicable to all forms of self-efficacy research (Bandura, 2006; Pajares, 1996; Zimmerman et al., 1992). Self-efficacy is context- specific; therefore the measures used must also be context-specific (Bandura, 2006; Pajares, 1996). Measures of self- efficacy should be designed to gauge what and individual believes s/he can do, not what s/he will do, how s/he feels or what outcome the expected outcome may be (Bandura, 2006). Self-efficacy measures that use response scales with larger response ranges are more sensitive and provide a stronger predictor of performance than do scales with narrower response ranges (Bandura, 2006; Pajares, 1996; Zimmerman, 1992). Self-efficacy refers to one’s own beliefs, and, therefore, is assessed through the use of self-report measures (Bandura, 2006; Pajares, 1996; Zimmerman, 1992). Self- efficacy measures must also be domain-specific and context specific, as self-efficacy beliefs are subject to change as the individual and his/her environment changes (Bandura, 2006; Pajares, 1996). One example of a domain and context-specific measure of self-efficacy is the Self-efficacy for Regulated Learning measure, which assesses high school students’ perceived capability to achieve in nine domains: mathematics, algebra, science, biology, reading and writing language skills, computer use, foreign language proficiency, social studies, and English grammar (Zimmerman et al., 1992). Another example of a specialized self-efficacy measure is the Mathematics Self-Efficacy Scale (MSES), which assesses self-efficacy of high school students about math (Pajares, 1996). The College Academic Self-Efficacy Scale (CASES) is an example of a measure designed to assess the academic self-efficacy of college students (Choi, 2005). Another example of a specifically designed measure of self-efficacy is the Online Technologies Self-Efficacy Scale, SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 26 which is used to determine community college students’ confidence with computer skills necessary for online learning (DeTure, 2004). The Motivated Strategies for Learning Questionnaire (MSLQ) is among the more popular measures for college student populations (Ozan, 2012; Pintrich, 2004; Puzziferro, 2008; Savoji, 2013; Wang et al., 2013; Zimmerman, 2008). The MSLQ was developed over the course of approximately a decade and completed in 1991(Pintrich, 2004). Since that time, the MSLQ is used to assess motivated learning strategies, including self-efficacy, by a number of researchers in a variety of settings (Ozan, 2012; Pintrich, 2004; Puzziferro, 2008; Savoji, 2013; Zimmerman, 2008). Challenges to Self-Efficacy There are several challenges related to the measurement and development of self-efficacy (Bandura, 1993, 2006, 2012; Pajares, 1996, 1997), and concerns over self-efficacy also extends to learners in online learning contexts (DeTure, 2004; Lee & Ching, 2014; Lee & Mendlinger, 2011; Orzan et al., 2012; Puzziferro, 2008; Savoji, 2013; Wang et al., 2013; Zhan & Mei, 2013). As discussed in the section on the measurement of self-efficacy, the only way to measure an individual’s beliefs is through self-report measures (Bandura, 2006; Pajares, 1996; Zimmerman, 1992), yet self-report measures are inherently subject to respondents’ misrepresentations of themselves (Bernaki et al., 2012). Researchers and experts in the field also expressed concern over the validity of some self-efficacy measures due to poor wording of questions, inadequate scales, and a lack of instrument context and domain specificity (Bandura, 2006; Pajares, 1997; Zimmerman, 2008). One of the challenges of measuring self-efficacy is that there are many aspects that can be measured in a given context. In traditional academic settings, self-efficacy can pertain to the SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 27 content, the type of assessment (test, presentation, or written assignment) as well as physiological or mood-related factors (Bandura, 1993, 2006, 2012; Pajares, 1996, 1997). In online learning contexts, all the same concerns and factors related to self-efficacy apply, with the addition of beliefs about one’s ability to successfully navigate technology such as computers and learning management systems (DeTure, 2004; Lee & Ching, 2014; Lee & Mendlinger, 2011; Orzan et al., 2012; Puzziferro, 2008; Savoji, 2013; Wang et al., 2013; Zhan & Mei, 2013). The perceived distance between instructor and learner, as well as the means of communication in online leaning, may also present a challenge to self-efficacy (Puzziferro, 2008; Wang et al., 2013; Zhan & Mei, 2013) because instructors’ instructional efficacy has an influence on the learning environment and students’ self-efficacy (Bandura, 1993, 2006, 2012; Pajares, 1996, 1997). If an instructor believes in his/her ability to teach, s/he is likely to direct more time and effort towards student learning (Bandura, 1993, 2006, 2012; Pajares, 1996, 1997). A lack of attendance or participation can limit the instructor’s ability to affect students’ self- efficacy. Individuals function as individuals as well as in groups. Therefore, self-efficacy is both a personal and a social construct (Bandura, 1993; Pajares 1996). Groups such as a class or a school will cultivate collective efficacy, where the entire group will share a belief in the group’s ability to complete a task or achieve an objective (Bandura, 1993; Pajares 1996). This collective self-efficacy filters down, to some extent, to individual’s self-efficacy. Whereas individuals can see each others’ expressions and hear the tone in other’s voices in a social setting such as a classroom, creating a sense of collective self-efficacy in an online learning environment may present challenges (Cho & Shen, 2013). SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 28 In summary, academic self-efficacy describes a student’s belief in his/her ability to accomplish an academic task. Academic self-efficacy is sensitive to learning contexts, such as online versus on traditional settings and are the most reliable predictor of academic behaviors (Bandura, 2012; Pajares, 1996; Zimmerman, 2000). While experience has the most impact on the development of self-efficacy, self-regulatory behaviors, performance, experience and self- efficacy have a reciprocal relationship. Ultimately, self-efficacy can be seen as prerequisite to goal setting and self-regulatory strategies such as academic help seeking behaviors (DeTure, 2004; Ozan et al., 2012; Pajares, 1996; Puzziferro, 2008). Help Seeking Students with high self-efficacy are more likely to seek help because they do not associate the need for help with the inability to perform a task (Kitsantas & Chow, 2007). This section discusses help seeking behaviors in academic settings. In academic settings, help seeking is the term used to describe students’ actions when they pursue assistance or support and put into action approaches to accomplish academic tasks, and help seeking behaviors come in several forms including: formal, informal, instrumental, and executive (Cheng et al., 2013; Karabenick, 2003; Kitsantas & Chow, 2007). This section covers the aforementioned help seeking behaviors, as well as the importance of help seeking, measurement and challenges to help seeking. Importance of Help Seeking Help seeking is an important self-regulatory behavior that is positively correlated with learning and academic performance (Cheng et al., 2013; Dabbagh & Kitsantas, 2013; Karabenick, 2003, 2011; Kitsantas & Chow, 2007). Help seeking in online contexts is of interest due to the fact that a change in the delivery method for a course may result in a change in help seeking behaviors. In traditional classroom settings, physical proximity to the instructor and the SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 29 teaching assistant, as well as visual and auditory cues, may create an environment that is conducive to help seeking behavior. Furthermore, online course delivery methods may create a feeling of distance, and therefore, lessen students’ propensity to seek help from formal sources (Cheng et al., 2013; Dabbagh & Kitsantas, 2013; Karabenick, 2011). Conversely, electronic means of communication such as discussion boards and email in online environments may lower perceived barriers to formal help seeking (Cheng et al., 2013; Dabbagh & Kitsantas, 2013; Karabenick, 2011; Kitsantas & Chow, 2007). Students prefer to seek help using an electronic means such as email, discussion board, and chat sessions over talking to an instructor or teaching assistant in person or over the phone (Cheng et al., 2013; Karabenick, 2011; Kitsantas & Chow, 2007). Help Seeking Categories Help seeking behaviors are organized into several categories: formal, informal, instrumental, and executive (Cheng et al., 2013; Karabenick, 2003; Kitsantas & Chow, 2007). The act of reaching out for assistance from conventionally recognized sources such as teachers and teaching assistants, or recourses recommended by or prepared by the instructor such as textbooks and websites, is referred to as formal help seeking (Kitsantas & Chow, 2007; Karabenick, 2011). Even though conventional wisdom dictates that formal help seeking results in the most accurate information, evidence indicates that most college students do not seek help from formal sources (Cheng et al., 2013; Karabenick, 2003; Karabenick, 2011). Informal help seeking is when students seek help from unofficial sources such as peers, unknown experts, or Internet searches (Cheng et al., 2013; Dabbagh & Kitsantas, 2013; Karabenick, 2003, 2011; Kitsantas & Chow, 2007). Research shows that, when students confront challenges related to academics, one of the last places they turn to for help is a formal source SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 30 (Kitsantas & Chow, 2007). Students who seek help are likely to engage in instrumental activities first, even more so than seeking help from informal sources (Kitsantas & Chow, 2007). Instrumental help seeking behaviors are those wherein students reach out for tips or guidance that will lead to learning, and Instrumental help seeking is likely to be exhibited by those with a mastery goal orientation. In addition, instrumental help seeking is more likely to result in learning relative to executive help seeking (Cheng et al., 2013; Dabbagh & Kitsantas, 2013; Karabenick, 2003; Karabenick, 2011; Kitsantas & Chow, 2007). Executive help seeking is used to describe help seeking actions that aim to secure answers, rather than guidance, toward the development of a solution (Cheng et al., 2013; Dabbagh & Kitsantas, 2013; Karabenick, 2003, 2011; Kitsantas & Chow, 2007). Executive help seeking is a behavior that is likely to be exhibited by those with a performance goal orientation (Cheng et al., 2013; Dabbagh & Kitsantas, 2013; Karabenick, 2003; Kitsantas & Chow, 2007). Executive help seeking can improve performance, but it is less likely to result in learning when compared to instrumental help seeking (Cheng et al., 2013; Dabbagh & Kitsantas, 2013; Karabenick, 2003; Kitsantas & Chow, 2007). Help Seeking Threat and the Impact of Technology on Help Seeking For many students, the admission that one requires assistance evokes feelings of anxiety, stress, and humiliation at the thought of other’s discovery of one’s need for help, and researchers posited that this help seeking threat is the cause of low rates of help seeking behaviors among students (Cheng et al., 2013; Karabenick, 2011; Kitsantas & Chow, 2007). Help seeking threat may also cause students to change their objectives or decrease their ambitions rather than seek any sort of help (Kitsantas & Chow, 2007). SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 31 Instructional design, the classroom environment, and affect pertaining to peers, more than the content, have an impact on self-regulatory behaviors such as help seeking (Bandura, 1993, 2006, 2012; Cho & Shen, 2013; Kitsantas & Chow, 2007; Pajares, 1996, 1997). Researchers suggested that instructors assess students’ beliefs early in an online course and use the results to design courses that focus on content and support for developing positive motivational beliefs in students (Hodges & Murphy, 2009; Lee & Mendlinger, 2011; Savoji, 2013; Smith, 2002). Instructional design that supports development of positive motivational beliefs in students, such as self-efficacy and help seeking, can improve students’ learning, performance and satisfaction in an online course (Cho & Shen, 2013; Hodges & Murphy, 2009; Kitsantas & Chow, 2007; Lee & Mendlinger, 2011; Savoji, 2013; Smith, 2002). Researchers found that students feel less threatened when using electronic forms of communication, such as discussion boards, when compared to interactions in person (Cheng et al., 2013; Kitsantas & Chow, 2007; Karabenick, 2011). Kitsantas and Chow (2007) suggest that students find it easier to take risks that may result in failure due to the relative anonymity that electronic forms of communication afford. Electronic forms of communication lift the burden of time and distance constraints, which also contribute to students’ preference for formal help seeking though these modes (Kitsantas & Chow, 2007). Proliferation of communication technologies, increased access and ease of use contributed to an increase in help seeking behaviors among college students. (Kitsantas & Chow, 2007; Karabenick, 2011). SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 32 Measurement of Help Seeking Help seeking behaviors pertain to actions taken; therefore, measurement of some aspects, such as help seeking from formal sources, may be collected from observations of students’ behaviors (Cheng et al., 2013). Still, there are challenges to measuring other help seeking behaviors such as informal help seeking and whether the intentions behind the help seeking behaviors were instrumental or executive, for example (Cheng et al., 2013). Therefore, the only measure through which to gauge informal help seeking is through the use of self-report measures such as ones developed by Karabenick (2011), the Motivated Strategies for Learning Questionnaire (Cho & Shen, 2013; Duncan & McKeachie, 2005; Pintrich, 2004), or Online Academic Help Seeking (OAHS) questionnaire (Cheng et al., 2013). While help seeking does pertain to actions which should be measureable through observation, the measure of the intention behind the help seeking behavior, executive or instrumental, must be measured through self- report instruments which ask students to report where they seek help when they have academic problems (Cheng et al., 2013). In summary, help seeking refers to a student’s beliefs and behaviors relating to seeking assistance with academic tasks. Help seeking can be organized according to sources from which students seek help and their reasons for seeking help. Measurement of help seeking behaviors can be done through observation, whereas help seeking beliefs and the intentions behind behaviors are measured through self-report instruments. Help seeking is important in that it is positively correlated with student learning. Goal Orientation Academic and self-regulatory beliefs and behaviors such as self-efficacy and help seeking are linked to goal orientations (Harackiewicz et al., 2002; Remedios & Richardson, SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 33 2013). Goal orientation refers to students’ intentions, by electing to engage in a learning activity (Cho & Shen, 2013; Pintrich & De Groot, 1990; Wolters, 2004). The use of self-regulating strategies, such as goal setting, is essential for academic performance on academic tasks (Corno, 1986; Zimmerman & Pons, 1986, 1988). Intrinsic and Extrinsic Goal Orientation Intrinsic goal orientation describes when a student is internally motivated to engage in an academic task for the satisfaction of accomplishing the task (Cho & Shen, 2013). Intrinsic goal orientation has a positive influence on performance (Cho & Shen, 2013). Due to the internal, personal value in the nature of intrinsic goal orientation, direct instruction that imparts the value of the learning task to the individual can help to increase intrinsic goal orientation (Cho & Shen, 2013). Extrinsic goal orientation describes when a student is motivated to engage in an academic task in order to earn a reward, such as a good grade or to avoid penalty (Cho & Shen, 2013). Higher levels of motivation and self-regulated learning behaviors are associated with students who are presented content with an intrinsic goal rationale over students presented content with extrinsic goal rationale (Cho & Shen, 2013). Mastery and Performance Goal Orientation Mastery goal orientation describes a student’s sincere motivation to master a task (Cho & Shen, 2013). Mastery orientation is similar to intrinsic goal orientation in that the motivation to choose and persist in a task is internal (Cho & Shen, 2013; Harackiewicz et al., 2002; Remedios & Richardson, 2013), and mastery orientation leads to deeper learning. There is, however, evidence to suggest that a mastery goal orientation can result in lower performance, as the focus SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 34 is on the learning, and not on the demonstration of learning that allows for assessment of performance (Cho & Shen, 2013; Harackiewicz et al., 2002; Remedios & Richardson, 2013). Students are said to have a performance goal orientation when their aim is to display their ability relative to others. While deep learning may not occur as in mastery goal orientation, performance goal orientation can have a positive impact on performance (Cho & Shen, 2013; Harackiewicz et al., 2002; Remedios & Richardson, 2013). Similar to other orientations, performance goal orientation can be measured through self-report measures, which are discussed later in this review of the literature. Approach and Avoidance Goal Orientations Goal orientation can also be categorized into approach and avoidance goal orientations (Remedios & Richardson, 2013). Approach goal orientations speak to when a learner intends to advance toward a goal such as to learn or to demonstrate ability (Wolters, 2004). Avoidance goal orientations describe when learners aim to escape failure or being perceived as less than their peers (Wolters, 2004). Performance avoidance. Performance avoidance goal orientation is when students’ objective is to escape appearing inept or dumb (Remedios & Richardson, 2013; Wolters, 2004). There is evidence of a connection between low confidence and the espousal of performance- avoidance goals, as performance avoidance goal orientation is negatively related to performance. It is not associated with deep learning, but, rather, with cursory study. Furthermore, performance avoidance goal orientation tends to have a negative impact on academic attainment, but it does not affect propensity to withdraw from courses (Remedios & Richardson, 2013). Mastery avoidance. The objective of mastery avoidance goal orientation is to avoid misunderstanding or not completing a task (Remedios & Richardson, 2013). Mastery goal SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 35 orientation is associated with metacognitive activity, and promoting intrinsic motivation, but mastery-avoidance orientation is not necessarily related to attainment (Pintrich & DeGroot, 1990; Remedios & Richardson, 2013). Mastery- avoidance goal orientation has negative implications for a student’s enjoyment of a course (Remedios & Richardson, 2013). Performance approach. Students whose goal is to appear more knowledgeable than other students can be described as having a performance approach goal orientation (Remedios & Richardson, 2013). Performance approach goals are positively related to students’ performance (Remedios & Richardson, 2013). Given that students in in online learning contexts have less opportunity to observe others’ performance or have their performance observed by peers, these students should be less likely to espouse performance-approach goals. (Remedios & Richardson, 2013) Mastery approach. Students who wish to truly understand a task have a mastery approach goal orientation (Remedios & Richardson, 2013). While there is no evidence that mastery-approach goal orientation is related to performance, it is positively related to both their interest and enjoyment. In addition, there is evidence of strong relationships between goals and outcomes, at least in the case of mastery approach, performance approach, and performance avoidance (Remedios & Richardson, 2013). Importance of Goal Orientation Goal orientation plays an important role in the self-regulated learning process. Some evidence shows that in online learning settings, goal orientation is positively related to metacognitive regulation, but extrinsic goal orientation is not associated with self-regulatory behaviors (Cho & Shen, 2013). SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 36 As mentioned earlier in the discussions of self-efficacy and help seeking, instructional design, the classroom environment, and affect pertaining to peers, more than the content, affect self-regulatory behaviors (Bandura, 1993, 2006, 2012; Cho & Shen, 2013; Kitsantas & Chow, 2007; Pajares, 1996, 1997). In online learning environments, it is also true that instructional design, the classroom environment, and affect pertaining to peers, have more of an impact than does the content on self-regulatory behaviors (Cho & Shen, 2013). When students receive direct instruction to assist them in setting their own achievable goals, and experience success in attaining those goals, students’ beliefs in their ability to learn are positively affected (Cho & Shen, 2013). Measurement of Goal Orientation Goal orientation can be measured subjectively by assessing enjoyment of a task, by observation of behavior, and by quantifying time spent on a task (Remedios & Richardson, 2013). Behaviors such as a student’s choice to increase time spent on a task can be used as an indication of that student’s goal orientation (Remedios & Richardson, 2013). Grades are a widely accepted measure of academic performance (Harackiewicz et al., 2002). Grades in a variety of college courses are best predicted by performance-approach goals (Harackiewicz et al., 2002). Goal orientation is also measured with a variety of self-report instruments, depending on context and the type of goal orientation being measured. Self-report measures of goal orientation include The Achievement Goals Questionnaire, also known as AGQ, and Patterns of Adaptive Learning Styles, or PALS (Remedios & Richardson, 2013). Another widely used self report measure, the MSLQ, an 81-item, consists of six motivation subscales and nine learning strategies scales, including a measure of intrinsic and extrinsic goal orientation (Cho & Shen, 2013; Duncan & McKeachie, 2005; Pintrich, 2004). SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 37 In summary, goal orientation refers to a student’s intentions when electing to engage in an academic activity. Students are as likely to be motivated to avoid a consequence, or achieve a goal, as they are to be motivated to learn. Goal orientation can be measured by observation or by self-report instruments. Goal setting is essential to performance of academic tasks. Conclusion This literature review examined research related to learning in online contexts in terms of undergraduate and community college students. Focus was also placed on research pertaining to concepts that affect learning including; self-efficacy, help seeking and goal orientation. While the history of distance education began more than a century ago, the increasingly rapid pace at which online education proliferates formal education closely follows the rates of advancement in technology. The increase in demand for online education also experienced brisk growth in recent years as the increased availability of technology make it more attractive to students and institutions because it offers efficient, flexible, convenient low-cost course content delivery options. Community colleges serve nearly half of all eleven million students in the U.S. (NSRC, 2014). The flexibility offered by online course formats is particularly attractive to nontraditional community college students who must often juggle work, family and academic commitments. Nontraditional students, with demands on their time that distract from academic endeavors, tend to benefit from social support to maintain the motivation to succeed in a course. While the flexibility of online courses attracts community college students, online courses require more self-regulation and tend to have higher attrition rates than traditional courses. Gateway courses such as introductory sociology are a requirement for a great number of these undergraduate students who wish to take advanced courses, earn a degree or transfer to a SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 38 four-year university. Due to the demand for both online courses and introductory sociology at the community college level, it is of particular interest to study the differences in student motivational constructs such as academic self-efficacy, help seeking, and goal orientation, in online and traditional sections of this course. Researchers found that goal orientation plays an important role in the self-regulatory process (Corno, 1986; Zimmerman & Pons, 1986, 1988). Evidence suggests that positive self- efficacy can lead to development of the self-regulatory strategies such as such as help seeking and goal setting, which are instrumental for learning, satisfaction and success in online learning environments (Harackiewicz et al., 2002; Remedios & Richardson, 2013). A paucity of research concerning the comparison of motivational constructs such as academic self-efficacy, help seeking and goal orientation in online contexts versus traditional classroom settings exists in current research (Aragon & Johnson, 2008; Hachey et al., 2014; Halsne, 2002; Savoji, 2013; Wang et al, 2013; Xu & Jaggars, 2011). An understanding of community college students’ self-regulatory and motivational (Savoji, 2013; Stahl & Bromme 2009) differences in gateway courses such as introductory sociology will allow educators to in improve course quality, as well as student learning, retention and performance. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 39 CHAPTER THREE: METHODS The purpose of this study was to assess self-efficacy, help seeking and goal orientation beliefs and behaviors in online versus on-campus learning settings among one community college student population in an introductory sociology course that fulfills a general education requirement for attainment of a two-year degree or transfer to a four-year university. This chapter includes the research questions, the hypotheses, 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 This study examined motivational beliefs and behaviors of community college students such as academic self-efficacy, help seeking and goal orientation of college students in online and traditional learning contexts. The following proposed research questions guided the study: 1. Is there is a difference in student help seeking by course delivery method among community college students? 2. Is there is a difference in student goal orientation by course delivery method among community college students? 3. Is there is a difference in student academic self-efficacy by course delivery method among community college students? 4. Do academic self-efficacy, intrinsic and extrinsic goal orientations predict help seeking, controlling for course delivery method? SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 40 Research Design The main purpose of this study was to assess academic self-efficacy, help seeking and goal orientation beliefs and behaviors in online versus on-campus learning settings among a community college student population. This research examined motivational beliefs and behaviors of students enrolled in a first-year, college-level introductory sociology course. The study design was quantitative, non-experimental research. Data was collected via online self- report surveys, which were delivered to community college students in online and on-campus sections of introductory sociology. The independent variable in the study was the mode of delivery: online versus on campus. The dependent variables in this study were help seeking beliefs and behaviors, academic self-efficacy beliefs, and goal orientation. Data was analyzed for statistical significance. Population and Sample Introductory sociology is a course taken by students during their first year of college and serves as one of the requirements for many undergraduate college degree and transfer programs. More than 30 sections of introductory sociology are offered at Southern California Community College (SCCC) each semester, with approximately 40 students enrolling in each section. In the fall of 2014, there were 36 sections of introductory sociology, with an enrollment of approximately 1,490 students at the start of the term, approximately 480 of whom were enrolled in one of the 12 sections offered in an online format (SCCC, 2014). The online sections of introductory sociology were asynchronous, with no face-to-face meetings or real-time video conferencing over the course of an eight-week term. The on-campus sections of introductory sociology had regular, face-to-face meetings, in the classroom over the course of a sixteen week term. For the purpose of this study, data was collected from the population of 1,279 students who SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 41 were still enrolled in introductory sociology courses after the last date to drop from a course with a refund, at SCCC in the fall of 2014. The sample was collected from 420 online, 158 telecourse, and 701 on-campus introductory sociology students. At the beginning of the term, approximately 810 students were enrolled in on-campus sections held on the main campus, and approximately 120 students were enrolled in on-campus sections held on a satellite campus, located six miles from the main campus. Instrumentation Participants completed a self-report questionnaire consisting of a number of demographic questions, and four subscales aimed to measure the constructs of academic self-efficacy, academic help seeking, goal-orientation and satisfaction (Appendix A). Students within the sample enrolled in introductory sociology at SCCC received an email asking them to participate in the study. The invitation sent after midterm examinations, and after the last date to drop from a course with a refund, to 420 online students, 158 telecourse students and 701 on-campus students for a total of 1,279 introductory sociology students. Of the 1,279 invitations to participate in the study sent, there were 196 responses, of those, 166 surveys were filled out completely, for a response rate of approximately 13%. Forty-seven of the respondents were enrolled in asynchronous, online sections of an eight-week duration, and 119 were from on- campus sections of introductory sociology with regular face-to-face meetings over the course of a sixteen-week term. Demographic Questions Demographic questions were included on the questionnaire in an effort to tease out possible influences on the motivational constructs measured. The demographic portion was designed to gather information regarding gender, delivery method for the course in which they SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 42 enrolled, and demands on time outside of course work, such as family and work obligations. Participants were asked about prior experiences with online courses. These questions allowed comparison of potential demographic differences between course delivery methods and may be relevant to future results. Academic Self-Efficacy Academic self-efficacy describes one’s beliefs about one’s ability to complete an academic task. Tested in many contexts with many populations, the MSLQ, an 81-item scale developed by Pintrich (1991), is one of the most widely used self-report measures for assessing students’ use of motivational strategies such as academic self-efficacy. Academic self-efficacy was measured with all eight of the items from the self-efficacy section of the MSLQ using a five point Likert scale, with 1 being Strongly Disagree, and 4 being Strongly Agree. The Cronbach’s alpha for the original MSLQ self-efficacy scale was .93. A reliability analysis conducted for this study found an alpha of .95 for the self-efficacy scale. As in the original study, the alpha for self-efficacy measured was high, indicating a strong level of reliability. Sample items from the MSLQ self-efficacy scale are “I expect to do well in this course” and “I’m certain I can master the skills being taught in this course.” Help Seeking Help seeking beliefs and behaviors are motivational and self-regulatory strategies students employ to improve learning and outcomes by asking others for assistance with academic tasks. Beliefs. In addition to a help seeking measure developed by Karabenick (2003), help seeking beliefs were measured with the four items from the help seeking section of the MSLQ. Cronbach’s alpha for the original MSLQ help seeking scale was .52. A reliability analysis SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 43 conducted for this study found an alpha of .8 for the help-seeking scale. The alpha for the help seeking scale measured was high, indicating a strong level of reliability. Samples items from the MSLQ help seeking scale are “If I don't understand the material in this course, it is important that I ask another student in this class for help” and “It is important to identify students in this course whom I can ask for help if necessary.” Behavior. The scale developed by Karabenick (2003) was designed to measure formal and informal help seeking behaviors. Three questions were answered using a five point Likert scale, with 1 being Strongly Disagree, and 4 being Strongly Agree. The Cronbach’s alpha for Karabenick’s informal versus formal help seeking scale was .66. A reliability analysis conducted for this study found and alpha of .7 for the help-seeking scale. The alpha for this help seeking scale measured was high, indicating a strong level of reliability. One of the three items used to tease out formal versus informal help seeking behaviors is “If I were to seek help in this course I would ask the teacher rather than another student.” Frequency. Students’ frequency of help seeking behavior was measured using the Help Seeking Assessment, instructing students indicate the frequency in which they sought help during the academic semester ranging from “Not at all” to “More than once a week.” The Help Seeking Assessment was collaboratively developed by a thematic dissertation group under the supervision of two faculty members at the USC Rossier School of Education. The instrument was designed using concepts of formal versus informal help seeking from Karabenick (2003). A reliability analysis conducted for this study found an alpha of .5 for the help-seeking scale. The alpha for this help seeking scale indicates that it is a reliable scale. A sample question from the frequency portion of Help Seeking Assessment is “During this course, how often would you seek help from an instructor/ teaching assistant?” SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 44 Goal Orientation The MSLQ was designed to measure goal orientation as one of the motivational strategies that have an impact on student learning and performance. Goal orientation was measured by all four items from the goal orientation section of the MSLQ using a five point Likert scale, with 1 being Strongly Disagree, and 4 being Strongly Agree. Intrinsic. Intrinsic goal orientation describes when a student is internally motivated to engage in an academic task for the satisfaction of accomplishing the task (Cho & Shen, 2013). The Cronbach’s alpha for the MSLQ intrinsic goal orientation scale was .74. A reliability analysis conducted for this study found an alpha of .79 for the intrinsic goal orientation scale. As in the original study, the alpha for intrinsic goal orientation measured was high, indicating a strong level of reliability. Two sample items of the four items from the MSLQ scale for intrinsic motivation are “In a class like this course, I prefer course material that really challenges me so I can learn new things” and “In a class like this course, I prefer course material that arouses my curiosity, even if it is difficult to learn.” Extrinsic. Extrinsic goal orientation describes when a student is motivated to engage in an academic task in order to earn a reward, such as a good grade or to avoid penalty (Cho & Shen, 2013). The Cronbach’s alpha for the MSLQ extrinsic goal orientation scale was .62. A reliability analysis conducted for this study found an alpha of .86 for the extrinsic goal orientation scale. The alpha for extrinsic goal orientation measured was high, indicating a strong level of reliability. Two sample items of the four items from the MSLQ scale for extrinsic motivation are “Getting a good grade in this course is the most satisfying thing for me right now” and “The most important thing for me right now is improving my overall grade point average, so my main concern in this course is getting a good grade.” SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 45 Student satisfaction. The student satisfaction subscale consisted of eight items. A reliability analysis conducted for this study found an alpha of .87 for the satisfaction scale. The alpha for the satisfaction scale measured was high, indicating a strong level of reliability. Sample items from the student satisfaction scale are “I am satisfied with my decision to take this course in this format” and “If I had an opportunity to take another course in this format, I would do so.” Procedure and Data Collection The Office of Institutional Effectiveness at SCCC granted permission for data collection once proof of approval from USC’s IRB board was provided. Data was collected via self-report questionnaires. Questionnaires were created with Qualtrics Survey Tool (Qualtrics, 2015) and administered online. Invitations to the survey were sent electronically to those who were registered in introductory sociology to coincide with the middle of the term. SCCC email addresses for registered students were obtained from SCCC’s office of institutional planning and research. Faculty were provided information regarding the survey sent to their students in a letter from the Dean of Social Sciences placed in faculty mailboxes at the beginning of the semester and in an email two weeks before their students were invited to participate. Students were offered a chance to enter a drawing as incentive to complete the survey. Data Analysis The independent variable in this study was program delivery method. The dependent variables were help seeking, academic self-efficacy, and goal orientation. Data was downloaded from Qualtrics Survey Tool (Qualtrics, 2015), coded, and input into the Statistical Package for the Social Sciences (SPSS) program, version 22. Cronbach’s alpha was also computed to ensure the reliability of the scales. Descriptive statistics such as the Pearson product coefficient were performed to analyze demographic information. To answer the research questions one, two and SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 46 three. Independent samples t-tests were performed to compare whether groups of online and on- campus students showed differences help seeking beliefs, behaviors and frequencies, goal orientation, and academic self-efficacy. A multiple regression was performed, controlling for delivery method while testing for relationships between academic self-efficacy, help seeking, intrinsic and extrinsic goal orientations for research question four. Appendix D provides a summary of information regarding research questions, variables and types of analysis performed. The results and implications of this analysis are discussed in Chapters Four and Five. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 47 CHAPTER FOUR: RESULTS The purpose of this study was to examine the motivational beliefs and behaviors of community college students across instructional delivery methods. The research questions developed were based on three specific constructs: academic self-efficacy, goal orientation, and help seeking. Specifically, the study was designed to answer the following research questions: 1. Is there is a difference in student help seeking by course delivery method among community college students? 2. Is there is a difference in student goal orientation by course delivery method among community college students? 3. Is there is a difference in student academic self-efficacy by course delivery method among community college students? 4. Do academic self-efficacy, intrinsic and extrinsic goal orientations predict help seeking, controlling for course delivery method? These research questions were answered by the use of a 48-item metric composed of three instruments and several demographic questions. Scales from the MSLQ survey instrument were used to measure the constructs of goal orientation and self-efficacy (Pintrich, 1991). The construct of help seeking was measured by the help seeking scale from the MSLQ as well as by an instrument developed by Karabenick (2003). A total of 1,279 surveys were distributed to students enrolled in an introductory sociology course at a community college. Respondents totaled N=166, with 47 participants from online sections, and 119 from on-campus sections. This chapter provides information regarding the findings of this study. The first section provides an overview of the descriptive characteristics of the respondents including demographic SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 48 data and information regarding instructional delivery format. The section that follows contains various statistical analyses of these results organized by research question. Descriptive Characteristics of Respondents In order to answer the research questions, online surveys were distributed to students who were registered in introductory sociology at SCCC in the fall 2014 term. Postcards announcing the survey were manually distributed in courses with face-to-face classroom meetings. Digital announcements were sent though the learning management system to online classes with no face-to-face meetings. Demographic Information Demographic information was collected about students who were enrolled in online, and on-campus sections of introductory sociology, and nonparametric analysis of the data was conducted. Table 1 illustrates that the majority of the participants in the study, regardless of delivery method, reported being between the ages of 18 and 23 (n=121, 73%). The mean age of all participants, regardless of course delivery mode, was 23.03 years. Seventy-six percent (n=119) of the respondents enrolled in the on-campus format were aged 18 to 23 as compared to 64% in the online (n=30) delivery format. Data collected from this survey was also analyzed using an independent-samples t-test to compare mean age in online and on-campus course delivery methods. Results of the t-test indicated that there were no significant differences in mean age between students enrolled in online (M=24.17, SD=7.83) and on-campus (M=22.58, SD=6.9) modes of delivery conditions t(164)=1.29, p=0.2. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 49 Table 1 Participant Demographics: Age Course Delivery Mode Age Online On-campus Total 18-23 30 (64%) 91 (76%) 121 (73%) 24-30 11 (23%) 18 (15%) 29 (17%) 31-36 1 (2%) 3 (3%) 4 (2%) 37-40 2 (4%) 2 (2%) 4 (2%) 41-49 2 (4%) 4 (3%) 6 (4%) 50-56 1 (2%) 1 (1%) 2 (1%) Total 47 119 166 Table 2 contains the results of an independent-samples t-test conducted to compare the number of units in which students were enrolled during the semester between students in online (n=47) and on-campus courses (n=119). There were no statistically significant differences in the number of units in which students were enrolled during the semester between online (M=11.75, SD=3.52) and on-campus (M=11.86, SD=3.4) students at the time of the survey t (158)=-.19, p = .85. Table 2 Differences in Enrollment in Units Between Modes of Course Delivery Enrollment in units Course delivery mode M SD df t p Online 11.75 3.5 158 -.19 .85 On-campus 11.86 3.44 Sixty-eight percent of the participants female, which reflects a slightly higher percentage of female students than the population described in SCCC’s 2012 report (51.2% female). As shown in Table 3, 78% (n=36) of female participants enrolled in online course delivery modes, compared with 63% (n=74,) in on-campus delivery modes. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 50 Table 3 Participant Demographics: Gender Course Delivery Mode Gender Online On-campus Total Male 10 (22%) 43 (37%) 53 (33%) Female 36 (78%) 74 (63%) 110 (68%) Total 46 117 163 Sixty-six percent (n=77) of students enrolled in the on-campus delivery method did not previously take a class online, compared to 36% (n=17) of students who were enrolled in online course delivery modes. Sixty-four percent (n=30) of students who previously took at least one course online enrolled in an online course delivery mode compared to 34% of students who previously took at least one course online enrolled in on-campus course delivery modes. Table 4 presents information pertaining to the quantity of online courses taken previously by survey participants. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 51 Table 4 Participant Demographics: Number of Online Courses Taken Previously Course Delivery Mode Number of Online Courses Taken Previously Online On- Campus Total 0 17 (36%) 77 (66%) 94 (57%) 1 13 (28%) 22 (19%) 35 (21%) 2 7 (15%) 10 (9%) 17 (10%) 3 5 (11%) 3 (3%) 8 (5%) 4 1 (2%) 0 1 (1%) 5 1 (2%) 1 (1%) 2 (1%) 6 1 (2%) 1 (1%) 2 (1%) 9 1 (2%) 0 1 (1%) 10 1 (2%) 2 (2%) 3 (2%) 51 0 1 (1%) 1 (1%) 47 117 164 Fifty-four percent of the respondents reported they were not working at the time of the survey. Fifty-eight (n=27) of students enrolled in the online course delivery mode were working at least part-time as compared with 50% (n=50) of students enrolled in the on-campus course delivery modes. Table 5 provides information pertaining to employment status. Table 5 Participant Demographics: Employment Status Course Delivery Mode Employment Status Online On-campus Total Not Currently Working 20 (43%) 69 (58%) 89 (54%) Working Part-Time 14 (30%) 34 (29%) 48 (30%) Working Full-Time 13 (28%) 16 (13%) 29 (18%) Total 47 119 166 SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 52 Forty-five percent (n=41) of students enrolled in the online and 48% (n=87) of students enrolled in on-campus course delivery modes reported that scheduling influenced the decision to select a course delivery mode. Thirty percent (n=54) of students enrolled in on-campus formats cited instructional considerations as the reason for selecting that particular course delivery mode, as compared with 9 % (n=8) of those enrolled in online delivery format. Table 6 presents information relating to participants’ reasons for selecting a particular course delivery mode. Table 6 Participant Demographics: Reasons for Selecting Course Delivery Mode Course Delivery Mode Reason Online On-campus Total Schedule 41 (45%) 87 (48%) 128 (47%) Instructional 8 (9%) 54 (30%) 62 (23%) Geographic 6 (7%) 13 (7%) 19 (7%) Family 17 (19%) 6 (3%) 23 (8%) Professional 12 (13%) 14 (8%) 26 (10%) Other 7 (8%) 6 (3%) 13 (5%) Total 91 180 271 Table 7 contains data pertaining to ethnicity collected in this study. Forty-one percent (n=67) of respondents identified as Hispanic or Latino. Thirty-nine percent (n=46) of students enrolled in the on-campus delivery method identified as being of Asian descent. Fifty-three percent (n=25) of students enrolled in the online delivery method were of Hispanic/Latino descent. By comparison, SCCC’s reported student population ethnicity of 36.9% Hispanic/Latino and 25.3% Asian (SCCC, 2012). In summary, the majority of the student population consisted of single, female, full-time students who are not working and who are enrolled in on-campus courses. Over 70% of the student population was under the age of 24. Students enrolled in online classes reported being SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 53 more likely to have taken at least one online class before, be married, and work at least part-time. Scheduling influenced most students’ decisions when selecting a course delivery mode. Table 7 Participant Demographics: Ethnicity Analysis of Results In order to answer research questions, self-report instruments were used to collect data, which was then analyzed. Results of the analysis of each question is organized by question and presented in this chapter. The mean, standard deviations and correlations of measured variables are presented in Table 8. An analysis of students’ reported ages at the time of the study show that age (M = 23.03, SD = 7.19) was significantly correlated with employment r = .26, p < .001, academic self- efficacy r = .19, p < .05, satisfaction r = .33, p < .001 and number of units r = -.41, p < .001. These results indicate that as students’ reported age increased, students’ reported academic self- efficacy and satisfaction increased. A positive relationship between age and employment was also revealed, as was an inverse relationship between age and the number of units. Course Delivery Mode Ethnicity Online On-campus Total American Indian or Alaska Native 2 (4%) 0 2 (1%) Asian 8 (17%) 46 (39%) 54 (33%) Black or African American 2 (4%) 2 (2%) 4 (2%) Hispanic/Latino 25 (53%) 42 (36%) 67 (41%) Native Hawaiian or Other Pacific Islander 0 2 (2%) 2 (1%) White 6 (13%) 10 (9%) 16 (10%) Two or More Races 2 (4%) 7 (6%) 9 (6%) Other 2 (4%) 9 (8%) 11 (6%) Total 47 118 165 SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 54 An analysis of the data also revealed a significant correlation between employment (M = 1.64, SD =.76), the number of units in which the students were enrolled at the time of the study r = -.30, p < .001, formal and informal help seeking behaviors r = .21, p < .01, and academic self- efficacy r = .22, p < .01. A negative correlation between intrinsic goal orientation r=-.18, p < .01, and the number of units in which students were enrolled was also found, indicating that, as students’ intrinsic goal orientation increased, the number of units that a student enrolled in decreased. The output from the Pearson’s r data analysis revealed an inverse relationship between the number of hours students worked and the number of units they enrolled in during the semester in which the data was collected. The results also indicate a positive relationship between students’ reported employment status and help seeking behaviors, academic self- efficacy, as well as students’ reported extrinsic and intrinsic goal orientations. Academic self-efficacy (M = 3.96, SD =.77) was significantly correlated with community college students’ satisfaction r = .54, p < .001 with their introductory sociology course, intrinsic goal orientation r = .46, p < .001, and extrinsic goal orientation r = .37, p < .001. Community college students’ general help seeking behaviors (M = 4.02, SD =.73) were also significantly correlated with both intrinsic r =.29, p < .001 and extrinsic r =.29, p < .001 goal orientation. These results, shown in Table 8, indicate that students who reported high academic self-efficacy also reported satisfaction with their experience in their introductory sociology course, as well as intrinsic and extrinsic goal orientations. These results also suggest that students who reported high academic self-efficacy, intrinsic and extrinsic goal orientations also reported that they were more likely to seek help. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 55 Table 8 Means, Standard Deviations, and Pearson Product Correlations of Measured Variables Variables M SD 2 3 4 5 6 7 8 9 1. Age 23.03 7.2 .26** - .41** .01 .15 .19* .08 -.15 .33** 2. Employment 1.64 .76 -- -.3** .09 .21** .23** .10 .04 .29** 3. Enrollment in Units 11.83 3.4 -- .05 -.04 -.17* -.18* .002 - .22** 4. Help Seeking General 4.02 .73 -- .26** .23 .29** .29** .03 5. Help Seeking Formal Informal 3.88 .93 -- .09 .08 .08 .17* 6. Academic Self-Efficacy 4.0 .73 -- .46** .27** .54** 7. Goal Orientation Intrinsic 3.63 .74 -- .37** .43** 8. Goal Orientation Extrinsic 4.0 .89 -- .30** 9. Satisfaction 4.0 .8 -- p< 0.05 ** p< 0.01 In addition to the inverse relationship between the number of units in which students enrolled (M = 11.83, SD = 3.42), reported age r = -.41, p < .001, analysis also revealed negative relationships between enrollment units and employment r = -.30, p < .001, academic self- efficacy r = -.17, p < .05, intrinsic goal orientation r = -.18, p < .05, and satisfaction r = -.22, p < .01. These findings indicate that, as the number of units in which students were enrolled increased, their reported employment status, academic self-efficacy, intrinsic goal orientation and satisfaction decreased. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 56 Research Question 1: Is there is a difference in student help seeking by course delivery method among community college students? This question sought to investigate potential differences in the motivational construct of help seeking between instructional delivery modes. Help seeking beliefs and behaviors. To determine whether there was a significant difference in help seeking beliefs and behaviors across course delivery modes, students enrolled in online and on-campus courses were asked to complete help seeking scales from Karabenick (2003) and the MSLQ (Pintrich, 1991). Data collected from this survey was then analyzed using an independent-samples t-test to compare mean help seeking in online and on-campus course delivery methods, the resulting information is displayed in Table 9. There was no significant difference in mean help seeking beliefs and behaviors t(84)=0.33, p=0.74 between students enrolled in online (M=4.05, SD=0.73) and on-campus (M=4.01, SD=0.73) modes of delivery conditions. In other words, there were no differences in the students’ beliefs about seeking helping between online and on-campus course delivery modes. Table 9 t-Test Comparing Mean Help Seeking Between Course Delivery Modes Course Delivery Mode n Mean SD t df p Online 47 4.05 0.73 0.33 84 0.74 On-campus 119 4.01 0.73 Formal and informal help seeking. In an effort to determine whether there was a significant difference in formal and informal help seeking across course delivery modes, students enrolled in online and on-campus courses were asked to complete the help seeking scale from Karabenick (2003). Data collected from this survey was then analyzed using an independent- samples t-test to compare formal and informal help seeking in online and on-campus course SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 57 delivery methods. The results of the analysis displayed in Table 10 indicate that there was no difference in the forms of help sought out by students enrolled in online (M=3.98, SD=0.96) and on-campus (M=3.84, SD=0.92) modes of delivery conditions t(81)=0.85, p=0.30. Table 10 t-Test Results Comparing Formal and Informal Help Seeking Between Course Delivery Modes Course Delivery Mode n M SD t df p Online 47 3.98 0.96 0.85 81 0.30 On-campus 119 3.84 0.92 Help seeking frequency. In order to determine whether there was a significant difference in help seeking beliefs and behaviors across course delivery modes, students enrolled in online and on-campus courses were asked to complete the help seeking scale from Karabenick (2003). Data collected from this survey was analyzed using an independent-samples t-test to compare help seeking frequency in online and on-campus course delivery methods and displayed in Table 11. There was no significant difference in help seeking frequency between students enrolled in online (M=1.91, SD=0.79) and on-campus (M=2.15, SD=0.82) modes of delivery conditions t(87)=-1.73, p=0.09. Simply stated, these results suggest that there were no differences between students on-campus and online in terms of how often they sought help. Table 11 t-Test Comparing Help Seeking Frequency Between Course Delivery Modes Course Delivery Mode n Mean SD t df p Online 47 1.91 .79 -1.73 87 .09 On-campus 119 2.15 .87 Research Question 2: Is there is a difference in student goal orientation by course delivery method among community college students? This research question sought to SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 58 investigate potential differences of goal orientation between course delivery modes. The two independent variables, online and on-campus delivery modes were examined along with the latent construct of goal orientation. Table 12 t-Test Results Comparing Intrinsic Goal Orientation Between Course Delivery Modes Course Delivery Mode N M SD t df p Online 47 3.59 .98 -0.44 164 0.56 On-campus 119 3.64 0.62 Intrinsic goal orientation. To determine whether there is a significant difference in intrinsic goal orientation across course delivery modes, students enrolled in online and on- campus courses were asked to complete an intrinsic goal orientation scale from the MSLQ (Pintrich, 1991). Data collected from this survey was then analyzed using an independent- samples t-test to compare intrinsic goal orientation between online and on-campus course delivery methods. The results of this analysis displayed in Table 12 shows that there were no significant differences in intrinsic goal orientation between students enrolled in online (M=3.59, SD=.98) and on-campus (M=3.64, SD=0.62) modes of delivery conditions t(164)=-0.66, p=0.56 was found. These results suggest that there were no differences in intrinsic goal orientation between students online and students on campus. Extrinsic goal orientation. To determine whether there is a significant difference in extrinsic goal orientation across course delivery modes, students enrolled in online and on- campus courses were asked to complete an extrinsic goal orientation scale adopted from the MSLQ (Pintrich, 1991). Data collected from this survey was then analyzed using an independent-samples t-test to compare extrinsic goal orientation in online and on-campus course delivery methods. The results of this analysis displayed in Table 13 show that there were no SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 59 differences in extrinsic goal orientation between students enrolled in online (M=3.99, SD=.93) and on-campus (M=4.0, SD=0.88) modes of delivery conditions t(80)=-0.02, p=0.98. Table 13 t-Test Results Comparing Extrinsic Goal Orientation Between Course Delivery Modes Course Delivery Mode n M SD t df p Online 47 3.99 .93 -0.02 80 0.98 On-campus 119 4.0 0.88 Research Question 3: Is there is a difference in student academic self-efficacy by course delivery method among community college students? In an effort to determine whether there is a significant difference in academic self-efficacy across course delivery modes, students enrolled in online and on-campus courses were asked to complete a self-efficacy scale adopted from the MSLQ (Pintrich, 1991). Data collected from this survey was then analyzed using an independent-samples t-test to compare academic self-efficacy in online and on-campus course delivery methods. The results of the analysis reported in Table 14 show that there were no significant differences in academic self-efficacy between students enrolled in online (M=4.03, SD=1.02) and on-campus (M=3.93, SD=0.65) modes of delivery conditions t(164)= 0.46, p=0.1. That is to say, regardless of the method of course delivery, online and on-campus students have the same level of belief in their abilities to perform academic tasks. Table 14 t-Test Results Comparing Academic Self-Efficacy Between Course Delivery Modes Course Delivery Mode n M SD t df p Online 47 4.03 1.02 0.46 164 0.1 On-campus 119 3.93 0.65 SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 60 Research Question 4: Do academic self-efficacy, intrinsic and extrinsic goal orientations predict help-seeking, controlling for course delivery method? In the correlation analysis discussed earlier in this chapter, a relationship between both extrinsic and intrinsic goal orientation was found with general help seeking. A multiple regression was conducted to examine the relationship between academic help seeking beliefs and various potential predictors, controlling for course delivery mode. Table 16 summarizes the descriptive statistics and analysis results. The results of the analysis show that intrinsic goal orientation and extrinsic goal orientation are positively and significantly related with the criterion, indicating that those with higher intrinsic and extrinsic goal orientation tend to have higher help seeking beliefs. Academic self-efficacy negatively predicted academic help seeking beliefs, indicating that as students’ academic self-efficacy increased, their academic help seeking beliefs decreased and vice versa. The multiple regression model with all four predictors produced R² = .015, F(4, 169) = 7.362, p < .001. As can be seen in Table16, intrinsic goal orientation and extrinsic goal orientation had significant positive regression weights, indicating students with higher scores on these scales were expected to have higher help seeking beliefs, after controlling for the other variables in the model. Academic self-efficacy had a significant negative weight (opposite in sign from its correlation with the criterion), indicating that after accounting for intrinsic goal orientation and extrinsic goal orientation, those students with higher academic self-efficacy were expected to have lower help seeking beliefs (a suppressor effect). Course delivery mode did not contribute to the multiple regression model. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 61 Table 16 Multiple Regression: Academic Self-Efficacy, Help Seeking Beliefs, Intrinsic and Extrinsic Goal Orientation Controlling for Course Delivery Mode Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 3.3 .37 8.56 .000 Course Delivery Mode .09 .11 .06 .83 .41 2 Academic Self- Efficacy .20 .08 -.21 -2.59 .01 3 Intrinsic Goal Orientation .24 .09 .24 2.77 .01 4 Extrinsic Goal Orientation .23 .07 .28 3.5 .001 a. Dependent Variable: Help Seeking Beliefs A multiple regression conducted in order to examine the relationship of frequency of students’ academic help seeking behavior to academic self-efficacy, intrinsic and extrinsic goal orientation did not reveal statistically significant results. The multiple regression model with all four predictors produced R² = .014, F(4, 168) = .59, p < .670. Course delivery mode did not contribute to the multiple regression model. See Table 17 below for details regarding the multiple regression of academic self-efficacy, intrinsic and extrinsic goal orientation as predictors of help seeking frequency, controlling for course delivery mode. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 62 Table 17 Multiple Regression: Effect of Goal Orientation on Help Seeking Frequency, Controlling for Course Delivery Mode Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 1.69 .42 3.99 .000 Course Delivery Mode .1 .12 .06 .78 .44 2 Self-Efficacy .01 .09 .01 .15 .88 3 Intrinsic Goal Orientation -.06 .1 -.06 -.63 .53 4 Extrinsic Goal Orientation .1 .07 .11 1.29 .2 a. Dependent Variable: Help Seeking Frequency Conclusion Identified in this chapter are the quantitative statistical findings from the analysis of the data collected in order to answer the research questions posed in this study. The results of the analysis pertaining to the first three research questions indicated that there were no significant differences in help seeking, goal orientation, or self-efficacy between students enrolled in online and on-campus modes of delivery. The results of the regression analysis pertaining to the fourth research question indicated that there was a relationship between help seeking and goal orientation, controlling for modes of delivery and no relationship between self-efficacy and help seeking, controlling for modes of delivery. The implications of these results are discussed in the next chapter. Sections in Chapter Five carry the statistical observations from this chapter into a discussion about how the results may inform current instructional design and possibly guide further studies on the interplay SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 63 between these motivational constructs and their implied effects on community college student behavior. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 64 CHAPTER FIVE: DISCUSSION This chapter begins with a brief overview of findings, which will provide the setting for a discussion of student academic motivation in distance and traditional learning environments. Differences and similarities in the learners and learning environments for both online and traditional community college courses will be examined through the framework motivational theory. This chapter concludes with implications, limitations, and potential directions for future research. Given the spatial and temporal distance in asynchronous online courses (Campbell et al., 2008; Chen et al., 2010; Lou et al., 2006), and the commonly held notion of student-teacher proximity as a measure of quality of education (Chen et al., 2010; Clark & Feldon, 2005), one may have predicted that there were differences in motivational dispositions held by online and on-campus students. Differences in self-efficacy (Bates, 2007; Hodges, 2009; Savoji, 2013, Wang et al., 2013), goal orientation (Bernacki, Byrnes, & Cromley, 2011) and help seeking beliefs and behaviors (Kitsantas & Chow, 2007; Nistor, Schwormd, & Werner, 2012; Stahl & Bromme 2009; Taplin et al., 2001) of community college students (Aragon & Johnson, 2008), and how motivational factors (Hachey, et al., 2014, Halsne, 2002; Xu & Jaggers, 2011) can enhance the quality of online and on-campus education experience for community college students have not been widely investigated. The relative proximity of on-campus students to faculty and libraries may lead to the assumption that differences in formal help seeking exist as compared to online students (Kitsantas & Chow, 2007). Spatial and temporal distance from a physical campus could also lead to the notion that online students would report increased self- efficacy, compared to on-campus students (Chen et al., 2010; Clark & Feldon, 2005; Lorenzo & Moore, 2002). A lack of evidence supporting motivational differences between on campus and SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 65 online students at the outset of this study suggested that there was an opportunity to contribute to the body of research and possibly fill a gap in the research. Student Characteristics and the Learning Context This study examined certain key characteristics pertinent to academic settings including demographic information and motivational factors, which were then compared across online and on campus delivery modes. Researchers who explore the topic of education found that community college students are more likely to be nontraditional, low income, and of a minority background than students attending four-year colleges and universities (Provasnik & Planty, 2008), and, as such, researchers found that community college students are more likely to take online courses due to the ease of access and flexibility of scheduling (Brown, 2012; Capra, 2014; Hachey et al., 2014). The community college student population in this study was consistent with existing research in many ways. The majority of the participants in this study were under twenty-four years of age, single, female, full-time students who are not working and who are enrolled in on- campus courses. However, there was also a contingent of the population of online students in this study, who also had nontraditional characteristics such as part-time enrollment status and at least part-time employment. Consistent with existing research (Brown, 2012; Capra, 2014), the findings of this study indicated that a majority of participants cited scheduling concerns as having played a prominent role in the decision to enroll in a particular course delivery mode. Results of previous studies examined as part of the current study suggest that, when compared to face-to-face courses, a higher ratio of underprepared, at-risk, part-time and minority students enroll in online education courses (Chen et al., 2010; Hachey et al., 2014). Consequently, the typical profile of students taking online courses also implies lower retention SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 66 rates than face-to-face courses (Picciano et al., 2010; Clay et al., 2009; Taver et al., 2014). The flexibility afforded by online course delivery modes is particularly attractive to nontraditional community college students with increased demands of work and family responsibilities competing for their time and attention (Brown, 2012; Picciano et al., 2010). Community colleges find it difficult to retain these nontraditional students so that they might persist and succeed (Brown, 2012; Clay et al., 2009; Picciano et al., 2010; Taver et al., 2014). Discussion of Motivational Factors Across Course Delivery Modes Researchers compared student learning outcomes and performance across course delivery modes and concluded that there are no differences between regular, face-to-face instruction and online instruction (Clark & Feldon, 2005; Clark et al., 2010; Rabe-Hemp et al., 2009; Robinson & Hullinger, 2008; Tamim et al., 2011; Xu & Jaggars, 2011). The most significant predictors of students’ learning, satisfaction and performance, in both online and traditional courses, are motivational beliefs such as academic self-efficacy (Bandura, 2012; Bates & Khasawneh, 2007; Puzziferro, 2008; Smith, 2002), goal orientation (Bernacki et al., 2011; Klein et al., 2006) and help seeking (Cheng et al., 2013; Karabenick, 2003, 2011; Kitsantas & Chow, 2007). Therefore, motivational factors are of interest to educators who aim to positively influence learning, retention, success and ultimately the success of the educational institution. Self-efficacy and the interrelatedness of motivational factors. Academic self-efficacy describes a student’s belief in their ability to accomplish an academic task. Academic self- efficacy is sensitive to learning contexts, such as online versus on traditional settings, and is the most reliable predictor of academic behaviors (Bandura, 2012; Pajares, 1996; Zimmerman, 2000). Researchers found self-efficacy to be prerequisite to goal setting and self-regulatory SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 67 strategies such as academic help seeking behaviors (Bandura, 2012; DeTure, 2004; Ozan et al., 2012; Pajares, 1996; Puzziferro, 2008). The results of the analysis in this study show that, while self-efficacy did not differ between online and on-campus settings, it was significantly correlated with community college students’ age, satisfaction, as well as their intrinsic and extrinsic goal orientation. These results indicate students’ self-efficacy increases with age, and those who reported positive self-efficacy also reported satisfaction with their learning experience, as well as reporting both high intrinsic and extrinsic goal orientations. The findings in this study pertaining to self-efficacy are consistent with researchers who found that self-efficacy has the most effect on students’ satisfaction (Bates & Khasawneh, 2007; Hodges & Murphy, 2009; Kitsantas & Chow, 2007; Puzziferro, 2008; Smith, 2002) and that positive student self-efficacy promotes academic achievement directly and indirectly by raising goals and stimulating self-regulatory behaviors (Bandura, 1993, 2006, 2012; Pajares 1996, 1997; Zimmerman, 2000). The correlation between self-efficacy and goal orientation found in this study is also suggestive of the results of findings of other researchers that showed that self-efficacy is a determinant for other motivational factors (Bandura, 2012; Kitsantas & Chow, 2007). Through the framework of social cognitive theory, Bandura (2012) proposed a structural model of the paths of influence where perceived self-efficacy plays a role as the impetus that drives motivational factors such as goal orientation. The findings of this study regarding self-efficacy align with other researchers’ findings (Gist & Mitchell, 1992; Multon, Brown, & Lent, 1991; Plotnikoff, Lippke, Courneya, Birkett, & Sigal, 2008), which confirm self-efficacy as the strongest influence with respect to motivational factors including goal orientation. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 68 Help seeking beliefs and behaviors. Help seeking describes students’ actions when they pursue assistance or support and apply approaches to accomplish academic tasks (Cheng et al., 2013; Karabenick, 2003; Kitsantas & Chow, 2007). The findings of previous studies (Bandura, 2012), discussed earlier in this study and earlier in this chapter show that students with positive self-efficacy do not attach any negative connotations to help seeking, but, rather, view it as an effective strategies for acquiring knowledge necessary in order to complete an academic task (Kitsantas & Chow, 2007). While the findings of this study, as they relate to help seeking beliefs and behaviors, revealed no significant differences in help seeking between students enrolled in online or on- campus courses, a correlation was found between help seeking and satisfaction. The correlation between help seeking and satisfaction is likely related to results of previous research indicating that help seeking is also correlated with the most efficient and effective approaches to learning strategy (Karabenick, 2003), effective learning is linked with academic performance (Chen et al., 2010; Clark & Feldon, 2005), and performance is associated with satisfaction (Puzziferro, 2008; Rabe-Hemp et al., 2009; Zhan, & Mei, 2013). A positive correlation between informal help seeking and employment was found, indicating that those who were employed seek from informal sources or unofficial sources such as; peers, unknown experts, or Internet searches, rather than formal sources such as teachers, teaching assistants, recourses recommended or prepared by the instructor such as textbooks and websites (Kitsantas & Chow, 2007; Karabenick, 2011). While research suggests that, when facing academic challenges, students are not likely to seek help from formal sources (Kitsantas & Chow, 2007), the demands of employment on a student’s schedule can also be an obstacle to seeking help from many traditional forms of formal sources during typical office hours. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 69 The results of this study showed that students’ help seeking beliefs were higher than the frequency at which they actually sought help. Students were asked to indicate their help seeking beliefs on a five point scale ranging from Strongly Agree (1) to Strongly Disagree (5) and the frequency of help seeking on a five-item scale; Not at all, 1-2 times per semester, 1-2 times per month, 1-2 times per week, More than twice per week. The mean for help seeking beliefs shown in Table 15 for online and on-campus students indicates that students agree or believe that help seeking is of value. The mean for help seeking frequency shown in Table 15 indicates that students sought help approximately once per semester. For the purposes of this study, the duration of the term in which introductory sociology courses were offered may be seen a potentially influential factor in students’ help seeking behavior. With the duration of the term being brief, eight weeks in the case of the asynchronous online courses, the term only lasts two months. Students may have only had time or opportunity to seek help once or twice per term. Alternatively, students may have felt embarrassed to seek help if the need for help was recognized at a point that seemed relatively late in the term. Goal orientation. Academic and self-regulatory beliefs and behaviors such as self- efficacy and help seeking are linked to goal orientations (Bandura, 2012; Harackiewicz et al., 2002; Karabenick 2003; Remedios & Richardson, 2013). In academic settings, goal orientation is a self-regulatory strategy referring to students’ intentions when electing to engage in a learning activity (Cho & Shen, 2013; Pintrich & De Groot, 1990; Wolters, 2004). Goal setting is essential for academic performance on academic tasks (Corno, 1986; Zimmerman & Pons, 1986, 1988). Correlations found in this study align with the findings from additional research studies, which found relationships between self-efficacy and goal orientation (Bandura, 2012; Zimmerman, 2000; Zimmerman, Bandura, & Martinez-Pons, 1992), and between goal orientation help SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 70 seeking, (Cheng & Tsai, 2011;Karabenick, 2003; Zhu, Chen, Chen, & Chern, 2011). In this study, general help seeking behaviors were significantly correlated with both intrinsic and extrinsic goal orientation. These results are consistent with research that suggests that help seeking is a behavior that is likely to be exhibited by those who are intrinsically motivated to engage in an academic task for the satisfaction of accomplishing the task as well as by those who are extrinsically motivated to engage in an academic task in order to earn a reward, such as a good grade or to avoid penalty (Cheng et al., 2013; Dabbagh & Kitsantas, 2013; Karabenick, 2003; Karabenick, 2011; Kitsantas & Chow, 2007). A negative correlation between intrinsic goal orientation and the number of units in which students were enrolled was also found, indicating that, as students’ intrinsic goal orientation increased, the number of units that a student enrolled in decreased. Students who are intrinsically motivated and want to engage in an academic task for the satisfaction of accomplishing the task are likely to be less concerned with accumulating units towards completion of a degree, certificate or transfer goal and more concerned with taking on less which allows for more focus, less distraction, more learning. Another finding showed a correlation between satisfaction and intrinsic as well as extrinsic goal orientations, indicating that, as students reported stronger intrinsic and extrinsic goal orientation, their reported levels of satisfaction also increased. The findings in this study are commensurate with findings from other researchers suggesting a relationship between students’ satisfaction and goal orientation (Cho & Shen, 2013; Puzziferro, 2008). Implications This study yields implications for professional development, faculty, course designers, and administrators at the post-secondary level. In recognizing the effectiveness of incorporating sound instructional design in promoting positive motivational beliefs and behaviors in any and SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 71 all course delivery modes (Bernard et al., 2009; Castle & McGuire, 2010; Clark & Feldon, 2005; Clark et al., 2010; Lou et al., 2006; Tamim et al., 2011) suggestions are made for development of curriculum that can favorably affect students’ retention, success, learning and satisfaction. The following five recommendations are directed toward professional development, faculty, course designers, and administrators at the post-secondary level from the perspective of sociocultural theory. First, the strongest contributor to self-efficacy is mastery experience. This study found that most students who were enrolled in an online class had previously taken an online course. An implication of this finding is that prerequisite orientation to college course with an online component is recommended for new students. This hybrid orientation course would acclimate first-time college students to the college experience, associated expectations, and strategies for success. The hybrid format of the course, designed as a mastery experience to both inform and prepare students, would also foster academic self-efficacy in online and on campus college courses. Secondly, the results of this study indicated an inverse relationship between the number of units in which a student was enrolled and goal orientation. In other words, students enrolled in fewer units during a given term had stronger, positive goal orientations. In order to improve for students enrolled in a greater number of units, assignments should be designed with clear instructions and goals. Assignments designed to capitalize on students’ interests, and that allow for students to exercise some choice while attaining student learning outcomes can positively affect students’ academic motivation. Designing assignments or portfolios where students create products that can be exhibited for friends or family can serve as an inherent reward, without negative impact that external rewards can have on student motivation. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 72 Thirdly, in order to further foster positive goal orientation in students enrolled in a greater number of units, it is important to discuss self-reflection and the role it plays in self-regulation. Instructors should encourage or require documentation of study strategies over time and have students note effectiveness to support their discovery of effective strategies in attaining specific, clearly defined academic goals. They should teach students specific strategies to set proximal goals that are challenging but reachable, and help them develop a systematic approach to assessment, to create a blueprint for a specific strategy, verbalize their plan, create checklists, note progress, and verbalize next steps. Fourth, demands of employment on a student’s schedule can be an obstacle to seeking help from many traditional forms of formal sources during typical office hours. Students may benefit from sources of help with flexible scheduling. In order to improve help seeking in this population, campus leaders should make students aware of, and encourage them to avail themselves of, resources such as tutoring services. Fifth, the results of this study indicated that the majority of students were under the age of twenty-four, and that self-efficacy was inversely related to age. To improve the self-efficacy in this young population, instructors describe the process of mastering a new skill to students in terms that they can relate to. They might provide testimony or evidence of real students with similar backgrounds who overcame obstacles. Additionally, providing consistent, credible, specific feedback for students is an effective tool to promote development of positive self- efficacy. Instructors should encourage accurate attributions in students fostering adaptability, explaining that a lack of success is not due to ability, but is controllable and that taking steps such as following instructions, allowing a reasonable amount of time for tasks, and following through on learning strategies will lead to increased success. For example, they can provide SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 73 statements such as, “If you follow the plan, you will succeed”. When providing feedback, make comparisons to a student’s own past performance rather than a comparison to others. Recommendations for Future Research The purpose of this study was to elucidate differences and similarities in self-efficacy, goal orientation and help seeking belief and behaviors of community college students across course delivery modes. Recommendations for further research include collection of data from a larger sample and from more than one institution. Another recommendation to add to the results of the current study is to collect responses from a more balanced sample in terms of course duration and number of respondents from each course delivery mode. In light of the importance of scheduling in students’ choice of course delivery mode, a comparison of student motivation and satisfaction in short-term courses across delivery modes may reveal significant findings, as could a comparison of student motivation between regular and short-term courses in the same delivery mode. Pre-test posttest design that compares students’ motivation at the beginning and again at the end of the term may uncover significant changes in student motivation. Such discoveries could improve implementation of sound instructional design to more effectively and positively affect student motivation, learning, retention and success. The collection of qualitative data may also serve to enhance the findings of qualitative data by providing a deeper, more developed understating of students’ responses. Limitations A limitation of this study is that it was correlational; therefore, no causal relationships can be determined. Only relationships between the independent and dependent variables could be determined. Due to the correlational nature of the study, it was not possible to conclude SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 74 whether the changes in the dependent variables are a result of the independent variables. The inherent interrelatedness of motivational factors presents challenges in the assessment of self- efficacy, goal orientation and help seeking beliefs and behaviors of community college students across delivery methods. In this correlational study, it could only be determined that the independent variables of course delivery modes and dependent variables of self-efficacy, goal orientation and help seeking were related, but no causal relationships could be determined nor could it be determined that the changes in the independent variables were a result of changes in the dependent variables. One of the limitations of this study was that responses were only collected from a single institution. Additionally, the sizes of the groups by course delivery mode were disproportionate. More courses were offered in an on-campus delivery mode than any other format. Additionally, online students could only be contacted through email addresses that were administered by the college and through the learning management system (LMS). While the college zealously encourages the use of the LMS and recommends that college-issued email addresses be checked regularly, these regulations cannot be enforced. In an effort to balance sample sizes from each group, the survey was administered online to all students, regardless of course delivery mode. As a consequence, another major challenge to the study became securing an adequate sample size, particularly from the smaller population of online students. Courses are typically delivered in sixteen-week term at the college that served as the setting for this study. The on-campus sections of the introductory sociology course adhered to the sixteen-week format, while the online sections of the same course, content and unit value were in a short-term format, which consisted of eight weeks. Differences in the duration of the term between the course delivery modes may have an effect on the data collected. Also included SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 75 among the limitations of the study was that the population that was examined was neither exclusively online or exclusively on-campus, rather the students enrolled in any or all course formats during the same term, depending on availability. Responses from a population that is neither exclusively online nor exclusively on-campus may have had the affect of yielding responses that are representative of the general student population, rather than teasing out the differences in characteristics between two distinctive groups of online and on-campus students. While attempts were made to ensure the validity and reliability of the survey, the study is wholly dependent self-report data and what students report they would do in a hypothetical situation. Students’ actual behavior could not be measured. Administering surveys after the last date to drop with a refund, coupled with short-term classes may have had the affect of limiting the amount of time students had to find out about and take the survey, which further reduced the potential sample size. Data was collected after the last day to drop a class without a tuition refund in an attempt to collect the responses of only those students with academic motivations to remain in the class and who intended to successfully complete the course. Only collecting date from students who remained in the course after the last date to drop with a refund may have had the effect of including only the remaining, more efficacious students with higher motivation than that of the average student population. Data was only collected once and was, therefore, not collected from students who had been enrolled prior to the drop date. Another limitation of the study was that it was a quantitative study and no qualitative data was collected. Qualitative data could provide rich insight into quantitative analysis. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 76 Conclusions Rapidly improving technology and infrastructure are among the factors that led to a surge in the demand for online education (Castle & McGuire, 2010; Lou et al., 2006; Tamim et al., 2011). Online education is of particular interest at the community college level as community college students are taking online courses in increasingly great numbers due to the ease of access and flexibility of scheduling (Capra, 2014; Chen et al., 2010; Hachey et al., 2014). Low retention rates are also of concern among the nontraditional, low income, students of minority backgrounds who make up much of the community college population and the online student population (Grimes, 1997; Hawley & Harris, 2005). While studies addressed differences in the quality of online education (Brown, 2013), and achievement outcomes such as grades (Bernard et al., 2009; Campbell et al., 2008; Castle & McGuire, 2010;), a paucity of research exists relating the differences in motivational beliefs and behaviors of community college students across course delivery modes (Aragon & Johnson, 2008; Hachey et al., 2014; Halsne, 2002; Savoji, 2013; Wang et al., 2013; Xu & Jaggars, 2011). The purpose of this study was to address gaps in the literature pertaining to the study of motivational factors such as self-efficacy, goal orientation and help seeking among online and on-campus community college students. The most significant conclusion of this study was that there were no differences in community college students’ reported self-efficacy, goal orientation and help seeking across course delivery modes. 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(2011). English Composition I: An effective predictor of persistence and retention at a community college (Unpublished doctoral dissertation). Indiana University of Pennsylvania, Indiana, PA. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 87 Wang, C. H., Shannon, D. M., & Ross, M. E. (2013). Students’ characteristics, self-regulated learning, technology self-efficacy, and course outcomes in online learning. Distance Education, 34(3), 302-323. Wolters, C. A. (2004). Advancing achievement goal theory: Using goal structures and goal orientations to predict students’ motivation, cognition, and achievement. Journal of Educational Psychology, 96(2), 236. Xu, D., & Jaggars, S. (2011). The effectiveness of distance education across Virginia’s community colleges: Evidence from introductory college-level math and English courses. Educational Evaluation and Policy Analysis, 33(3) Xu, D., & Jaggars, S. (2013). Adaptability to online learning: Differences across types of students and academic subject areas. Manuscript submitted for publication, Community College Research Center, Teachers College, Columbia University, New York. Retrieved from http://hdl.handle.net/10022/AC:P:19258 Zhan, Z., & Mei, H. (2013). Academic self-concept and social presence in face-to-face and online learning: Perceptions and effects on students’ learning achievement and satisfaction across environments. Computers & Education, 69, 131-138. Zhu, Y. Q., Chen, L. Y., Chen, H. G., & Chern, C. C. (2011). How does Internet information seeking help academic performance?–The moderating and mediating roles of academic self-efficacy. Computers & Education, 57(4), 2476-2484. Zimmerman, B. J., Bandura, A., & Martinez-Pons, M. (1992). Self-motivation for academic attainment: The role of self-efficacy beliefs and personal goal setting. American Educational Research Journal, 29(3), 663-676. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 88 Zimmerman, B. J. (2000). Self-efficacy: An essential motive to learn. Contemporary Educational Psychology, 25(1), 82-91. Zimmerman, B. J. (2008). Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American Educational Research Journal, 45(1), 166-183. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 89 Appendix A Letter of Informed Consent Q1 University of Southern California Rossier School of Education 3470 Trousdale Parkway Los Angeles, CA 90089 INFORMATION/FACTS SHEET FOR EXEMPT NON-MEDICAL RESEARCH MOTIVATIONAL BELIEFS AND BEHAVIORS OF COMMUNITY COLLEGE STUDENTS IN ONLINE VS TRADITIONAL COURSE DELIVERY MODES You are cordially invited to participate in a research study. Research studies include only people who voluntarily choose to take part. This document explains information about this study. You should ask questions about anything that is unclear to you. You can print a copy of this document for your records. You are eligible to participate if you are aged 18 or older and a Pasadena City College Student enrolled in Sociology 001, you are eligible to participate. Participation is voluntary. PURPOSE OF THE STUDY The purpose of this study is to learn about the beliefs and behaviors of community college students who choose to enroll in online versus on-campus courses. The study aims to answer the following research questions: Is there is a difference in student help seeking beliefs, types of help seeking or frequency of help seeking behaviors by course delivery method among community college students?, Is there is a difference in student goal orientation by course delivery method among community college students?, Is there is a difference in student self-efficacy beliefs by course delivery method among community college students?, Do self-efficacy, intrinsic and extrinsic goal orientations predict help seeking, controlling for course delivery method? Research into this topic is needed to determine whether differences exist in certain motivational beliefs and behaviors according to program delivery method. PARTICIPANT INVOLVEMENT If you agree, you are invited to participate in completing an online survey comprised of 48 questions. The survey will take approximately 15-20 minutes to complete. COMPENSATION SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 90 You will not be compensated for your participation; however will be eligible to be enrolled into a drawing for a $25 iTunes gift card. You do not have to answer any question you don’t want to in order to be eligible for the raffle drawing. ALTERNATIVES TO PARTICIPATION Your alternative is to not participate. Your academic standing and grade in this course will not be affected whether you participate or not in this study. CONFIDENTIALITY Your name, address or student ID number will not be linked to your responses. Email addresses will be collected for the purposes of issuing the iTunes card only. Your responses will be coded with a false name (pseudonym) and maintained separately. The data will be stored on a password-protected computer in the researcher’s locked office. The members of the research team and the University of Southern California’s Human Subjects Protection Program (HSPP) may access the data. The HSPP reviews and monitors research studies to protect the rights and welfare of research subjects. INVESTIGATOR CONTACT INFORMATION Principal Investigator, Hollie Luttrell, via email at luttrell@usc.edu; Co-Investigator, Jee Kim, via email at jeeekim@usc.edu or Faculty Advisor, Kimberly Hirabayashi, via email at hirabaya@rossier.usc.edu IRB CONTACT INFORMATION University Park Institutional Review Board (UPIRB), 3720 South Flower Street #301, Los Angeles, CA 90089-0702, (213) 821-5272 or upirb@usc.edu m Agree (1) m Disagree (2) SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 91 Appendix B Recruitment Script Q2 Hello, my name is Hollie Luttrell , and I am conducting a research study, under the supervision of Kimberly Hirabayashi, Ph.D., from the University of Southern California. If you are aged 18 or older and a Pasadena City College Student enrolled in Sociology 001, you are eligible to participate. Participation is voluntary. The aim of the study is to see whether differences exist in student beliefs and behaviors in online and on-ground learning environments. The study will specifically examine motivational beliefs of self-efficacy, goal orientation and help seeking. If you agree to participate in the study you will be asked to complete an online survey. The length of time for taking the survey is approximately 15-20 minutes and consists of 48 questions. You will be asked to complete a section on demographic information, such as your gender, age, major, and will need to indicate your level of agreement or disagreement to statements such as “I expect to do well in this class.,” “Getting a good grade in this class is the most satisfying thing for me right now.,” and “It is important to ask the instructor to clarify concepts I don't understand well.” All responses are anonymous; identifiable information will not be linked to your responses. Please note: Whether or not you participate in this study will have no bearing on your course grade in this course. Survey respondents will be entered into a raffle drawing for a $20 iTunes gift card. If you agree to participate in this study, an information sheet will be provided once you click on the link below or copy the address below to your browser. If you agree to participate by checking the box and submitting your signature, you will be directed to complete the survey. <qualtricssurveylinkhere> Thank you very much for your time and consideration. If you have any questions, please feel free to contact me by email at luttrell@usc.edu. m I am over 18 and I agree to participate in the study (1) m I am under 18 or I do not wish to participate in the study (2) SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 92 Appendix C Demographic Questions Q3 What is your gender? m Male (1) m Female (2) m Transgender (3) Q4 What is your age in years? Q5 What is your current employment status? m Not currently working (1) m Working part-time (2) m Working full-time (3) Q6 Please indicate your ethnicity m American Indian or Alasaka Native (1) m Asian (2) m Black or African American (3) m Hispanic/Latino (4) m Native Hawaiian or other Pacific Islander (5) m White (6) m Two or more races (7) m Other (8) ____________________ Q7 Please indicate your relationship status m Single (1) m Married/Domestic Partner (2) m Separated/Divorced (3) m Widowed (4) Q8 What is the highest level of education either of your parents has completed? m Primary school or less (1) m Middle school (2) m Some high school (3) m High school (4) m Associate Degree (5) m Some college (6) m Bachelor's Degree (7) m Master's Degree (8) m Doctoral Degree (9) SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 93 Q9 What is your major Q10 How many units are you currently enrolled in? Q11 How many diversity or multicultural classes have you taken in higher education? m 0 (1) m 1 (2) m 2 (3) m 3+ (4) Q12 Do you have a previous graduate degree? m Yes (1) m No (2) Q13 How many online courses have you taken for college credit prior to this course? SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 94 Help Seeking Q14 Indicate the degree which you agree or disagree with the following statements. Please answer the following question in the context of your experience in this course, SOC 001. Strongly Disagree (1) Disgree (2) Neither Agree nor Disagree (3) Agree (4) Strongly Agree (5) Even if I have trouble learning the material in this class, it is important that I try to do the work on my own, without help from anyone. (1) m m m m m It is important to ask the instructor to clarify concepts I don't understand well. (2) m m m m m If I don't understand the material in this course, it is important that I ask another student in this class for help. (3) m m m m m SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 95 It is important to identify students in this class whom I can ask for help if necessary. (4) m m m m m If I were to seek help in this class, I would ask the teacher rather than another student. (5) m m m m m I would prefer asking another student for help in this class rather than the instructor. (6) m m m m m In this class, the teacher would be better to get help from than would a student. (7) m m m m m SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 96 Q15 Please answer the following question in the context of your experience in this course, SOC 001.During this class, how often did you seek help from; Not al all (1) 1-2 times per semester (2) 1-2 times per month (3) 1-2 times per week (4) More than twice a week (5) Instructor/teaching assistant (1) m m m m m Peer (2) m m m m m Other (3) m m m m m SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 97 Self-Efficacy Q16 Please answer the following question in the context of your experience in this course, SOC 001. Strongly Disagree (1) Disagree (2) Neither Agree nor Disagree (3) Agree (4) Strongly Agree (5) I believe I will receive an excellent grade in this class. (1) m m m m m I'm certain I can understand the most difficult material presented in the readings for this course. (2) m m m m m I'm confident I can understand the basic concepts taught in this course. (3) m m m m m I'm confident I can understand the most complex material presented by the instructor in this course. (4) m m m m m SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 98 I'm confident I can do an excellent job on the assignments and test in this course. (5) m m m m m I expect to do well in this class. (6) m m m m m I'm certain I can master the skills being taught in this class. (7) m m m m m Considering the difficulty of this course, the teach, and my skills, I think I will do well in this class. (8) m m m m m SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 99 Intrinsic Goal Orientation Q17 Please answer the following question in the context of your experience in this course, SOC 001. Strongly Disagree (1) Disagree (2) Neither Agree nor Disagree (3) Agree (4) Strongly Agree (5) In a class like this, I prefer course material that really challenges me so that I can learn new things (1) m m m m m In a class like this, I prefer course material that arouses my curiosity, even if it is difficult to learn. (2) m m m m m The most satisfying thing for me in this class is trying to understand the content as thoroughly as possible. (3) m m m m m When I have the opportunity in this class, I choose course assignments that I can learn from even if they don't guarantee a good grade. (4) m m m m m SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 100 Extrinsic Goal Orientation Q18 Please answer the following question in the context of your experience in this course, SOC 001. Strongly Disagree (1) Disagree (2) Neither Agree nor Disagree (3) Agree (4) Strongly Agree (5) Getting a good grade in this class is the most satisfying thing for me right now. (1) m m m m m 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. (2) m m m m m If I can, I want to get better grades in this class than most of the other students. (3) m m m m m I want to do well in this class because it is important to show my ability to my family, friends, employer, or others. (4) m m m m m SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 101 Student Satisfaction Q25 Are you an Honors Transfer Program Student (HTPS)? m Yes (1) m No (2) Q26 Are you taking this course online, on-campus, or telecourse? m Online (1) m On-campus (2) m Telecourse (3) If On-campus Is Selected, Then Skip To Which campus are you taking this course? Q27 Which campus are you taking this course? m Pasadena Main Campus (1) m PCC Rosemead Campus (2) Q28 Why did you choose to take this format? (Check all that apply) q Scheduling (1) q Instructional considerations (e.g., preferred method of instruction, quality of instruction, access to instructor) (2) q Geographic reasons (3) q Family responsibilities (4) q Professional responsibilities (5) q Other (6) ____________________ SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 102 Q29 When answering the following questions, "format" refers to either online or on-campus. Strongly Disagree (1) Disagree (2) Neither Agree nor Disagree (3) Agree (4) Strongly Agree (5) I am satisfied with my decision to take the course/program in this format. (1) m m m m m If I had an opportunity to take another course/program in this format, I would do so. (2) m m m m m I feel that this course/program format served my needs. (3) m m m m m I will take as many courses/programs in this format as I can. (4) m m m m m I feel the quality of the course/program I took was largely enhanced by the format. (5) m m m m m I would take another course with this instructor. (6) m m m m m Q22 If you would like to enter the drawing for one (1) of the five (5) $25 iTunes gift cards, please enter your email below. SELF-EFFICACY, HELP SEEKING AND GOAL ORIENTATION 103 Appendix D Summary of Research questions, Variables and Analysis Research Question IV(s) Level of Measurement DV(s) Level of Measurement Statistical Test 1. Is there is a difference in student help seeking by course delivery method among community college students? Method of delivery (online vs. on campus) Nominal Help seeking beliefs Interval T-test Help seeking behavior type Interval Frequency of Help seeking behavior Interval 2. Is there is a difference in student goal orientation by course delivery method among community college students? Method of delivery (online vs. on campus) Nominal Goal orientation Intrinsic/extri nsic Interval T-test 3. Is there is a difference in student academic self-efficacy beliefs by course delivery method among community college students? Method of delivery (online vs. on campus) Nominal Academic Self-efficacy Interval T-test 4. Do academic self-efficacy, intrinsic and extrinsic goal orientations predict help- seeking, controlling for course delivery method? Academic Self- efficacy, Intrinsic and Extrinsic goal orientation Interval Help Seeking Frequency Interval Regression

Abstract (if available)

Abstract The purpose of this study was to investigate academic self‐efficacy, help seeking and goal orientation beliefs and behaviors in online versus on‐campus learning settings among a community college student population enrolled in a first-year, college‐level introductory sociology course. Gateway courses such as introductory sociology are a requirement for a great number of undergraduate students who wish to take more advanced courses, earn a degree or transfer to a four‐year university. Due to the demand for both online courses and gateway courses such as introductory sociology at the community college level, it is of particular interest to study the differences in student academic motivational constructs in online and traditional course formats. ❧ The findings indicate that there are no statistically significant differences between students’ academic self‐efficacy, help seeking, or goal orientation across course delivery methods. The study did find relationships between students’ academic motivational factors such as goal orientation and help seeking. The study also found correlations between student characteristics. For example, most students who were enrolled in an online course had previously taken at least one online course, and as the number of units in which students were enrolled increased, their reported employment status, academic self‐efficacy, intrinsic goal orientation and satisfaction decreased. The implications of this study can serve to inform instructors, professional development and instructional designers as to students’ needs and how to best design support and interventions that foster academic motivation, which can positively affect student learning and success.

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Creator Luttrell, Hollie (author)

Core Title Student academic self‐efficacy, help seeking and goal orientation beliefs and behaviors in distance education and on-campus community college sociology courses

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 06/22/2015

Defense Date 04/17/2015

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

Tag academic motivation,academic self‐efficacy,community college,goal orientation,help seeking,OAI-PMH Harvest,on‐campus,online,Sociology,student satisfaction,undergraduate

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Hirabayashi, Kimberly (committee chair), Seli, Helena (committee chair), Tirapelle, Leslie (committee member)

Creator Email hollieluttrell@gmail.com,luttrell@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-574985

Unique identifier UC11299928

Identifier etd-LuttrellHo-3496.pdf (filename),usctheses-c3-574985 (legacy record id)

Legacy Identifier etd-LuttrellHo-3496.pdf

Dmrecord 574985

Document Type Dissertation

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Rights Luttrell, Hollie

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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...

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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