ADULT LEARNERS’ MOTIVATION IN SELF-DIRECTED E-LEARNING
ADULT LEARNERS’ MOTIVATION IN SELF-DIRECTED E-LEARNINGKyong-Jee KimSubmitted to the faculty of the University Graduate Schoolin partial fulfillment of the requirementsfor the degreeDoctor of Philosophyin the Department of Instructional Systems TechnologyIndiana UniversityAugust, 2005
Accepted by the Graduate Faculty, Indiana University, in partial fulfillment of therequirements for the degree of Doctor of Philosophy.Theodore W. Frick, Ph.D.Elizabeth BolingDoctoralCommitteeCurtis J. Bonk, Ph.D.Susan C. Herring, Ph.D.August 1, 2005ii
2005Kyong-Jee KimALL RIGHTS RESERVEDiii
ACKNOWLEDGEMENTSFirst of all, I am very grateful to my dissertation director, Dr. Ted Frick, for hiswonderful guidance and support throughout this research project as well as during mycoursework at Indiana University. I also thank my research committee members,Professor Elizabeth Boling, Dr. Curt Bonk, and Dr. Susan Herring for sharing theirknowledge and insights with me for this research study. It has been a great pleasure forme to have such an excellent group of scholars and mentors supporting and guiding methroughout this research project.I would like to acknowledge that this research study was supported by a researchgrant from the Kemp Fellowship award. I deeply appreciate Dr. Jerrold E. Kemp and theIST Award Committee members for this grant that made this research study possible.The financial support that I received from this grant made it possible for me to implementthe research plan without financial constraints.I also would like to thank my friends and colleagues for their help and support forthis research project. I am especially grateful to Stacey for her time and effort to help mewith the data collection process for this research study. I am also thankful to Sung PilKang, Jung Won Hur, and Jae Woong Shim for helping me with the data analysis for thisresearch study. I also thank Amy Lawson for reading the manuscript and giving mefeedback on it.Most of all, I am very grateful to my family for putting up with me for many yearsthrough my journey to the completion of my degree. My family has been a source ofcourage for me to pursue what I want to become. I especially thank my parents for theirtireless love and support for me and the family.iv
ABSTRACTKyong-Jee KimADULT LEARNERS’ MOTIVATION IN SELF-DIRECTED E-LEARNINGAs with traditional instruction, learner motivation is important in designingeffective e-learning courses. However, lack of motivation has been a major concern intheory and practice for facilitating successful online learning environments. A review ofliterature indicated that there is little empirical knowledge on how to motivate onlinelearners, particularly in self-directed e-learning settings (SDEL). Research questionsaddressed in this study included: 1) what motivates or inhibits adult learning in SDEL?2) does adult learner motivation change as he or she goes through SDEL? 3) what factorsare related to motivational change during SDEL?This study used mixed methods. A content analysis was conducted on threeSDEL courses in order to better understand the learning context. Twelve qualitativeinterviews of typical learners were conducted to identify major motivational factors.Analysis of these interview results led to construction of a 60-item Web survey of adultlearners who had taken one or more SDEL courses (n 368). Approximately 60 percentof the respondents were from corporate settings and 40 percent from higher education. Afactor analysis of 33 survey items led to identification of three strong factors: ‘e-learningis not for me’; ‘e-learning is right for me’; and ‘I don’t want to be all by myself’.Results from both qualitative and quantitative analyses indicated that learnersstarted SDEL for personal or professional development, and that they chose the onlinev
training option because of its flexibility and convenience. Both qualitative andquantitative results suggested that lack of motivational quality in the e-learning coursewas a key factor for some learners who decided not to complete the course, followed bylack of time. A stepwise multiple regression analysis resulted in five factors thatsignificantly contributed to predicting the learner’s reported motivational change: 1) Elearning is right for me; 2) satisfaction with their learning experience; 3) interactivitywith an instructor or technical support personnel; 4) age (negative relationship); and 5)learning setting (corporate more than higher education).Implications of findings from this study are discussed for design of self-directede-learning environments that may help increase or sustain learner motivation.Theodore W. Frick, Ph.D.Elizabeth BolingCurtis J. Bonk, Ph.D.Susan C. Herring, Ph.D.vi
TABLE OF CONTENTSCHAPTER I. INTRODUCTION.11.1 Statement of the Problem . 11.2 Definitions . 51.2.1 Adult Learners.51.2.2 Self-Directed e-Learning.51.2.3 Motivation .71.3 Purpose of the Study / Research Questions . 91.4 Significance of the Study. 9CHAPTER II. REVIEW OF THE LITERATURE.112.1 Theories of Motivation . 112.1.1 Intrinsic Motivation.112.1.2 Continuing Motivation .132.1.3 Measuring Motivation .152.2 Theoretical Framework of Factors Influencing Learner Motivation. 172.2.1 Internal Factors.182.2.2 External Factors.282.2.2 Personal Factors .292.3 Literature Review Conclusion . 31CHAPTER III. METHODOLOGY .353.1 Research Design . 353.1.1 Content Analysis .353.1.2 Exploratory Mixed-Method Research Design.363.1.3 The Population of this Study.393.2 Content Analysis. 413.2.1 Content Analysis of Sample e-Learning Courses .413.2.2 Content Analysis of Course Design Documents .453.2.3 Data Collection and Analysis.453.3 Interview Study. 473.3.1 Participants .473.3.2 The Qualitative Instrument.493.3.3 Qualitative Data Collection.503.3.4 Qualitative Data Analysis.513.3.5 Trustworthiness of the Qualitative Study.543.4 Survey Study . 563.4.1 Sampling Procedures.563.4.2 The Survey Instrument .573.4.3 Quantitative Data Collection.623.4.4 Quantitative Data Analysis.64CHAPTER IV. THE CONTENT AND DESIGN OF SELF-DIRECTED E-LEARNINGCOURSES: RESULTS OF THE CONTENT ANALYSIS.684.1 Findings from the Content Analysis. 684.1.1 The Course Structure.68vii
4.1.2 The Amount of Textual and Graphic Components .704.1.3 Interactivity .724.1.4 Learner Control .764.2 Summary of the Content Analysis. 78CHAPTER V. LEARNER MOTIVATION IN SELF-DIRECTED E-LEARNING:RESULTS OF THE MIXED-METHODS STUDY .805.1 Findings from the Qualitative Study . 805.1.1 Learners’ Motivation to Start Self-Directed e-Learning .805.1.2 Learners’ Motivation during Self-Directed e-Learning .825.1.3 Motivational Influences during Self-Directed e-Learning .845.1.4 Learners’ Motivation to Continue Self-Directed e-Learning.965.2 Findings from the Quantitative Study . 975.2.1 Participants’ Demographics and Backgrounds in e-Learning.975.2.2 Motivations for Self-Directed e-Learning.1005.2.3 Factors Associated with the Learner’s Motivational Change .1135.2.4 Learners’ Motivation to Continue Self-Directed e-Learning.1165.2.5 Learner’s Overall Satisfaction with the e-Learning Course.1195.3 Summary of the Mixed-Methods Study . 120CHAPTER VI. DISCUSSIONS AND CONCLUSION.1245.1 Overall Summary of the Study . 1245.1.1 Overall Design of Self-Directed e-Learning Courses .1255.1.2 Learner Motivation for Self-Directed e-Learning.1255.1.3 Learners’ Motivational Change during Self-Directed e-Learning .1315.2 Implications for the Motivational Design of Self-Directed e-Learning Environments. 1325.3 Limitations of the Study . 1355.4 Recommendations for Future Study . 1375.5 Concluding Remarks . 139REFERENCES .140APPENDICES .162Appendix A. Analysis Scheme for the Content Analysis. 162Appendix B. Interview Protocol. 163Appendix C. E-mail Message Sent to Recruit Survey Participants. 165Appendix D. Questionnaire for the Survey Study. 166CURRICULUM VITA: KYONG-JEE KIM .180viii
LIST OF TABLESTable 1Table 2Table 3Table 4Table 5Table 6Table 7A Synthesis of the Literature on Motivational Influences in e-Learning . 33A Priori Scale on Motivational Influences in the Survey Instrument. 61Amount of Textual and Graphic Information in Sample e-Learning Courses. 72Interactive Features Used in Sample e-Learnieng Courses and their Frequeencies 75Retention Rates of the Interview Participants across Course Topics . 83Repondents' Motivations for Starting Self-Directed e-Learning . 100A Comparison of Motivation for Starting Self-Directed e-Learning acrossLearners in Different Educational Settings. 101Table 8 Respondents' Reasons for Choosing an Online Training Option . 102Table 9 Respondents' Reasons for Dropping out of the e-Learning Course. 103Table 10 ANOVA for Course Completion Rates among Different Course Topics. 104Table 11 A Cross-Tablution of Course Completion Rates Between Learners in DifferentEducational Settings. 105Table 12 Factor Analysis and Reliability Analysis Results . 106Table 13 Descriptive Statistics for the Motivational Factors in Self-Directed e-Learning. 108Table 14 ANOVA betweem Learners' Motivational Attributions and Course CompletionRates. 110Table 15 Variables that are Significantly Correlated with the Learner's MotivationalChange during Self-Directed e-Learning. 113Table 16 A Summary of Multiple Stepwise Regression of Analysis Variables forPredicting the Learner's Motivational Change during Self-Directed e-Learning . 115Table 17 Respondents' Reasons for Continuing Self-Directed e-Learning . 117Table 18 Variables that are Significantly Correlated with the Learner's Intention toContinue Self-Directed e-Learning in the Future . 119Table 19 The Relationship between the Motivational Factors in Self-Directed e-Learningand the Learner's Overall Satisfaction with the Course . 120Table 20 Instructional Design Principles Recommended for Sustaining LearnerMotivation in Self-Directed e-Learning. 134ix
LIST OF FIGURESFigure 1. A screenshot of simulation in the sample soft skills course. 69Figure 2. An example of course page with text and graphics. 70Figure 3. A screenshot of animation in the sample desktop application course. . 74Figure 4. User preferences screen. 77Figure 5. Results of descriptive analysis of learner’s motivational change. 112x
CHAPTER I.INTRODUCTION1.1 Statement of the ProblemThe technology of the World Wide Web (henceforth, the Web) is changing theway people learn, work, and socialize (Bonk & King, 1998). In particular, more andmore adults are turning to the Web for their learning needs due to its flexible deliverysystem in both education and training settings. Although the effectiveness of Web-basedinstruction - now often called e-learning - has been reported in many studies (e.g., Jung &Rha, 2000; Olson & Wisher, 2002), high learner drop-out rates have been a concern inWeb-based instruction (Carr, 2000; Cornell & Martin, 1997; Dalton, Manning, Hagen,Paul, & Tong, 2000; Diaz, 2002; Frankola, 2001; Islam, 2002); this has also been the casein distance education (Howell, Williams, & Linsday, 2003; M. G. Moore & Kearsley,1996).Past studies of factors contributing to learner attrition in distance education ineducational and training settings suggest that lack of time and lack of motivation are themajor causes of the problem (Bonk, 2002; Galvin, 2003; Gibson, 1998; Visser, Plomp,Amirault, & Kuiper, 2002; Wolcott & Burnham, 1991). Therefore, those factors need tobe taken account in addressing the problem of learner attrition in Web-based instruction.In addressing this issue, although instructional designers or instructors do not havecontrol over the learner’s time, they can exert some influence on the learner’s motivation.Cognitive theories of motivation and research findings indicate that learners’ motivationtends to change over time through instruction (R. C. Clark, 2003; Coldeway, 1991; Song1
& Keller, 1999). Hence, we need to pay attention to improving the motivational qualityof Web-based instruction in order to address the issue of online learner attrition.E-learning is a rapidly growing market and is expected to continue to be so in thefuture. According to a survey report, the U.S. e-learning market in 2002 was 10.3billion and is projected to grow to 83.1 billion in 2006 (Adkins, 2002).1 From a globalperspective, the worldwide corporate e-learning market is expected to leap from 6.6billion in 2002 to over 23 billion by 2006 (IDC, 2003). Considering the amounts spenton e-learning, it is imperative that the investment be worthwhile for stakeholders. Toaccomplish that goal, e-learning courses need to provide learners with a learningenvironment that builds success for them. Many researchers and practitioners in elearning believe that stimulating student motivation is one of the critical factors forcreating a successful online learning environment (Hofmann, 2003; Powers & Guan,2002).Many argue that motivation makes significant impacts on learners. First of all,past research has consistently reported positive and robust correlations between thelearner’s motivational level and his or her academic achievement in traditional classroomenvironments (Fyans & Maehr, 1987; Uguroglu & Walberg, 1979; Walberg, 1984). It isargued that learners need not only to possess the necessary cognitive and meta-cognitiveskills to be effective in their learning, but also need to be motivated to use such cognitivestrategies to regulate their cognition and effort to use their cognitive and meta-cognitive1Consumers of the e-learning market consist of those from various sectors, yet business organizations andeducational institutions (K-12 and higher education) were the most dominant sectors, representing over70% of the total e-learning spending in 2002.2
skills effectively (Pintrich & De Groot, 1990). Accordingly, several researchers haveemphasized the importance of motivational influences of learning as key principles ofeffective instruction (American Psychological Association, 1993; Bransford, Brown, &Cocking, 2000).Second, motivation has a si
ADULT LEARNERS’ MOTIVATION IN SELF-DIRECTED E-LEARNING As with traditional instruction, learner motivation is important in designing effective e-learning courses. However, lack of motivation has been a major concern in theory and practice for facilitating successful online learning environments. A review of
The motivation structure analysis will be based on the general knowledge of the theory of motivation, together with the analysis of the employees’ motivation profiles. The fundamental tool used in this process is a cluster analysis and its usage in the creation of motivation programs. The analysis of motivation factors and their order will be
ANALYSIS OF MOTIVATION IN THE PROFESSIONAL ENVIRONMENT. For our study and for a better understanding of the relationship professional identity-motivation, we considered relevant the presentation of aspects regarding motivation, be it economical or professional. 3.1 Economic motivation . The financial motivation is based on financial stimulus.
motivation for all of their daily activities - including reading! Motivation can be intrinsic or extrinsic. Intrinsic motivation: behavior that is driven by internal rewards. Intrinsic motivation is a type of motivation that arises from within the individual because the activity is naturally satisfying to him/her. Examples of intrinsic .
6 Theories of Motivation 6.1 Motivation: General Considerations 6.2 Self Determination Theory of Motivation 6.3 Motivation Design : ARCS, FEASP References: E. L. Deci and R. M. Ryan: The “What” and “Why” of Goal Pursuits: Human Need and Self-determination of Behaviour. Psychological Inquiry, 4 (2000), 227-268.
motivation scales for their research and classroom. The goals of this review were to identify a set of reading motivation student self-report scales used in research, examine the development and psychometric properties of each reading motivation scale, and compare scales on availability, reliability, age range, and motivation constructs measured.
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