I’d like to welcome you to my dissertation defense and thank you for your presence and attention. I’d also like to acknowledge the presence and outstanding help of Dr. Robin Throne, my dissertation chair, and Dr. David Britton, my subject matter expert. Dr. Nicole Avena my other committee member was unable to attend. Slide 2. Andragogy and Online Course Satisfaction: A Correlation Study Stephen W. Watts School of Education, Northcentral University Prescott Valley, AZ December 2014 Robin Throne, Ph.D., Committee Chair , David Britton, Ed.D., Nicole Avena, Ph.D.

Agenda Background Problem and Purpose Significance of the Study I will quickly cover up to the literature review and spend more time discussing the findings, the limitations and implications, and recommendations; both for practice and future research. Slide 3 Agenda Background Problem and Purpose Significance of the Study Theoretical Framework Research Question(s) Literature Review Method Findings Limitations and Implications Recommendations for Practice Recommendations for Future Research Conclusions

My study was based on three main factors: 1. A majority of the factors that appear to have the greatest impact on drop out decisions are learner factors, or elements that a learner either has or does. 2. Lee and Choi (2011) found that the next largest number of factors and greatest subsequent impact on learner decisions for retention or dropout were course–program factors. 3. Knowles (1973, 1975, 1980, 1984, 1990, 1995) posited that an optimal learning environment would take into account a. learner characteristics b. and would have a strategy for designing the experience around the learners, instructors, and institutional goals. Please, turn to slide 4. Background Learner factors have the greatest impact on drop out decisions (Lee & Choi, 2011). Course-program factors come next (Lee and Choi, 2011). Optimal learning environment included learner characteristics and design elements (Knowles, 1973, 1975, 1980, 1984, 1990, 1995)

The specific problem addressed in my study was low satisfaction among adults in online postsecondary courses, which has been considered the largest determinant in reducing online dropout. The purpose of my quantitative correlation study was to investigate relationships between adult learner characteristics, instructional process design elements, and learner satisfaction among adult learners in a postsecondary online environment with at least one physical facility in Missouri. Slide 5 Problem and Purpose Low satisfaction of adults in online postsecondary courses (Donavant, 2009; Huang et al., 2012; Watkins, 2005) Learner satisfaction largest determinant in reducing online dropout (Chen & Lien, 2011; Kozub, 2010; Johnson et al., 2014; Martinez-Caro, 2009). Investigate relationships between adult learner characteristics, instructional process design elements, and learner satisfaction.

Significance of the Study First, because of the vast differences in dropout rates for online courses as compared to traditional courses, past researchers have noted the importance of identifying factors that may minimize this phenomenon. Second, one of the most influential determinants for reducing online dropout is learner satisfaction, and the link between retention and learner satisfaction has been established. Third, the study sought to identify the predictive value of learner characteristics and specific instructional processes from which strategies and interventions may be derived based on the theoretical framework of Andragogy. Slide 6 Significance of the Study Need to identify factors that minimize dropout rates in online classes (Brown, 2012; Lee & Choi, 2011; Wilson & Allen, 2011). The link between retention and learner satisfaction has been established (Chen & Lien, 2011). Identify predictive value of learner characteristics and specific instructional processes from which strategies and interventions may be derived (Donavant, 2009; Gunawardena et al., 2010; Holton et al., 2009; Huang et al., 2012; Taylor & Kroth, 2009b).

Theoretical Framework Malcolm S. Knowles is the educator who popularized the term and theory of andragogy in the United States. Although built on the foundation of the work of several others, Andragogy as defined by Knowles is often broken down into six assumptions that in this study were operationalized as the six adult learner characteristics. Less known; Knowles’ Andragogy included eight instructional process design elements that were also operationalized in this study Although immensely popular with adult educators, many purists and researchers complain that the theory of Andragogy has little empirical support. The point of this study was that by empirically confirming the effect andragogical principles (meaning the adult learning characteristics and instructional process design elements) had on learner satisfaction, more inferential studies may follow, to further strengthen andragogy’s empirical research base. Slide 7 Theoretical Framework Malcolm S. Knowles Andragogy

Research Questions The following research questions guided the study: Question 1 was: Do adult learner characteristics predict learner satisfaction in a Missouri Higher Learning Commission of the North Central Association of Colleges and Schools accredited postsecondary online environment? The adult learner characteristics measured in question 1 included: intrinsic motivation to learn prior experience need to know readiness to learn self-directed learning orientation to learn Question 2 echoed question 1 with the exception that instructional process design elements replaced adult learner characteristics. These design elements included: prepare the learner climate setting mutual planning diagnosis of learning needs setting of learning objectives designing the learning experience learning activities evaluation Slide 8 The following research questions guided the study: Q1. Do adult learner characteristics predict learner satisfaction in a Missouri HLC-NCA accredited postsecondary online environment? Q2. Do the instructional process design elements predict learner satisfaction in a Missouri HLC-NCA accredited postsecondary online environment?

Literature Review Online Technological Advances There is much in the literature about andragogy, about online learning, and about learner satisfaction. For that reason there was quite a bit to say in the literature review. There were seven major sections in the review. I started by identifying the affordances and dramatic growth that online technologies have brought to higher education. I then discussed the benefits of boundaryless, any time, any where learning that may often be done at one’s own pace that may enhance communication between the learner and content, other learners and the instructor. A number of factors were discussed that enables success for learners online, including factors that dealt with the relationship between the learner and instructor, other learners, the content, reflection, collaboration and the development of a community of learning, the need for exercises and learning to be relevant and immediate, and the need to encourage and for the learner to have extant motivation Drop out occurs because of academic factors, learner characteristics, lack of specific skills (like time management, an ability to balance life’s demands, and information literacy), as well as psychological characteristics of the individual learner. In addition, inadequate student support services by the online institution and poor course design have been shown to increase drop out. Learner satisfaction results from and encourages learner engagement, higher academic performance, greater learner motivation and learning, and a better opportunity for online success. When a learner is satisfied with a course or program they tend to persist and are less likely to drop out, while conversely, the less satisfied the learner is, the more likely they are to withdraw. As learners participate in classes and interact with other learners and instructors they are more likely to persist with their online programs. The literature corroborates the more a learner participates, the higher his or her probability of succeeding and of completing. As the instructor rewards greater learner effort and time spent engaged in learning, and a learner has higher expectations for themselves, they are more likely to persist, show greater commitment to, and be motivated to learn. Learners who take a deep learning approach and achieve at higher levels are also more likely to be satisfied. Learners tend to be dissatisfied online or ambivalent in negative environments, where there is cognitive overload, when difficulties with technology are pervasive or the course is poorly designed, and when methods of communication are difficult, time consuming, and impede information. Slide 9 Literature Review Online Technological Advances Purported Benefits of eLearning Factors that Bring eLearning Success Learner Factors of Dropout Online Course or Program Factors of Dropout Learner Satisfaction and Online Course Dropout Factors that Engender eLearner Satisfaction

Method Quantitative Correlational Study [Higher Learning Commission of the North Central Association of Colleges and Schools] The study used a Quantitative method with a Correlational design. The sample consisted of postsecondary students over the age of 24 using a stratified random sample of students from 13 HLC-NCA universities and colleges in Missouri. An online survey was conducted using Survey Gizmo. The survey consisted of a combination of two pre-validated instruments; the Andragogy in Practice Inventory and the Satisfaction subscale of the Learner Satisfaction and Transfer-of-Learning Questionnaire. Email invitations were sent to 50,808 students. Of these invitations 5,683 clicked on the link to enter the survey, 3,646 completed the demographic information, but only 2,058 answered every question in the survey and were used as the sample. Hierarchical multiple regression analysis was used for hypothesis testing to determine whether either or both of the two sets of andragogical principles significantly added to the prediction of the criterion variable satisfaction. Slide 10 Quantitative Correlational Study Postsecondary students over the age of 24 using a stratified random sample of students from 13 HLC-NCA universities and colleges in Missouri. Online survey through Survey Gizmo, which was a combination of two pre-validated instruments. Hierarchical multiple regression analysis was used for hypothesis testing

In hierarchical regression analysis factors are grouped to determine the amount of variance accounted for in the criterion variable; in this case, online learner satisfaction. Model 1 consisted of participant demographic characteristics. These demographic characteristics explained 7.6% of the variance in learner satisfaction. Model 1 was statistically significant and was used to partial the affects of the demographic factors from the affects of the study’s predictor variables included in models 2 and 3. Slide 11 Findings: Model 1 Variable Beta t p Unique Common Total %R2 Constant 2.161 26.783* .000   Number of Courses .271 12.598* .073 -.000 96.9 Age Range .029 1.336 .182 .001 .002 3.0 School Type -.010 -.460 .545 0.0 Gender .006 .273 .785 0.1 Ethnicity .009 .427 .669 Education Level -.056 -2.518 .012 .003 -.003 0.5 R2 .076* F 27.622* Cohen’s f 2 .081 Note. N = 2,058; *p < .01; Unique = x’s unique effect on learner satisfaction, Common = Σ x’s common effects; Total = Unique + Common; %R2 = Total/R2.

Findings: Model 2 (Hypothesis 1) Slide 11 includes the results from model 2, which included the demographic characteristics and the adult learner characteristics. All told, the 12 variables accounted for 56.2% of the variance in online learner satisfaction. The model was significant, and after partialing for the effects of the demographics, the adult learner characteristics accounted for an additional 48.6% of the variance in online learner satisfaction. Therefore, the null hypothesis for hypothesis 1 was rejected, and support was found for the alternate hypothesis. Slide 12 Findings: Model 2 (Hypothesis 1) Variable Beta t p Unique Common Total %R2 Constant .529 6.215* .000   Number of Courses .103 6.681* .010 .0626 .0727 12.9 Age Range -.017 -1.147 .251 .002 0.4 School Type -.022 -1.463 .144 .001 -.001 0.0 Gender .026 1.772 .077 Ethnicity -.009 -.611 .541 Education Level -.052 -3.322* .003 -.002 0.1 Intrinsic Motivation .326 10.418* .024 .471 .495 88.0 Self-directed Learning .110 5.773* .007 .219 .226 40.3 Prior Experience .125 5.658* .356 .363 64.6 Need to Know .113 5.234* .006 .320 58.0 Readiness to Learn .161 5.243* .449 .456 81.1 Orientation to Learn .004 .246 .806 .090 16.1 R2 .562* F 369.73* Cohen’s f 2 1.28 Note. N = 2,058; * p < .01, ΔR2 = .486; Unique = x’s unique effect on learner satisfaction, Common = Σ x’s common effects; Total = Unique + Common; %R2 = Total/R2.

Findings: Model 3 (Hypothesis 2) Slide 12 shows the results for model 3, which included all of the measured variables; the demographic characteristics, the adult learner characteristics, and the instructional process design elements. The 20 variables accounted for 65.1% of the variance in online learner satisfaction, and was statistically significant. After partialing of the demographic characteristics and the adult learner characteristics, the instructional process design elements accounted for an additional 8.9% of the variance in online learner satisfaction. Therefore, the null hypothesis for hypothesis 2 was rejected and support was found for the alternate hypothesis. Slide 13 Variable Beta t p Unique Common Total %R2 Constant .333 4.130* .000   Number of Course .085 6.191* .007 .066 .073 11.2 Age Range -.010 -.722 .471 .002 0.4 School Type -.024 -1.731 .084 0.0 Gender .017 1.294 .196 Ethnicity -.005 -.385 .700 Education Level -.040 -2.826* .005 Intrinsic Motivation .269 9.529* .016 .479 .495 76.0 Self-directed Learning .078 4.803* .004 .223 .226 34.7 Prior Experience .071 3.545* .361 .363 55.7 Need to Know -.074 -2.806* .324 .326 50.0 Readiness to Learn 3.000* .003 .454 .456 70.0 Orientation to Learn .009 .586 .558 .090 13.9 Prepare the Learner .115 4.234* .362 .366 56.2 Mutual Planning -.129 -4.704* .183 .188 28.8 Climate Setting 8.658* .013 .400 .410 62.9 Setting of Objectives -.009 -.321 .749 .175 26.8 Diagnosis of Needs -.096 -4.206* .218 .220 33.9 Learning Activities .046 2.632* .001 .266 .268 41.1 Designing Experience .034 1.181 .238 .344 52.8 Evaluation .274 12.167* .027 .446 .473 72.6 R2 .651* F 64.939* Cohen’s F2 1.833 Note. N = 2,058; * p < .01, ΔR2 = .089; Unique = x’s unique effect on learner satisfaction, Common = Σ x’s common effects; Total = Unique + Common; %R2 = Total/R2.

Limitation of Results Potential self-selection bias The largest potential limitation of any survey study is that individuals choose to participate or not, and there is no way to verify that those who participated were not different in some substantial way from those who chose not to participate. Participants were selected from schools with physical locations in Missouri, which could limit generalizability of the findings to other states, regions or countries. While surveys have many advantages, they cannot always measure a target population exactly. One possible limitation may have existed as participants may have intentionally misreported or had poor recall of the events or circumstances requested. Slide 14 Limitation of Results Potential self-selection bias Schools in Missouri, potentially limiting generalizability Potential inaccuracy in answers given, or intentional misreports

According to the results, instructors may engender learner satisfaction by encouraging their students to be disciplined, willing to learn, independent, taking the initiative, using their life experiences, and being actively engaged in the classroom. This means that instructors should implement as many adult learning principles as possible to bolster learner-directedness and positive learner outcomes, including satisfaction. The Andragogy in Practice Inventory may be used in future inferential studies to strengthen andragogy’s empirical research base that many authors have proclaimed is sorely lacking. The significant, positive, predictive relationship found between the eight instructional process design elements and learner satisfaction showed that online learner satisfaction and the instructional process design elements were related and predictive of learner satisfaction. This finding was theoretically consistent with the premises of andragogy, that as instructors include these elements in an adult learning scenario, the outcomes of adult learners, including learner satisfaction, will be positive. Course designers may use the positive, predictive models to design online offerings to emphasize the instructional process design elements and take advantage of the adult learner characteristics that the present study showed predicted learner satisfaction. Slide 15 Implications Instructors implement adult learning principles (Knowles, 1973, 1975, 1984, 1995). The Andragogy in Practice Inventory may strengthen andragogy’s empirical research (Brookfield, 1986; Holton et al., 2009; Long et al., 1980; Rachel, 2002). Instructors apply the instructional process design elements Course designers may use to design online offerings

Recommendations for Practice One recommendation for practice is that by employing the Andragogy in Practice Inventory, instructors may hone their instructional skills and establish whether learners perceive their efforts as andragogical so as to determine whether the learning outcomes match curricular outcomes. Also, since learner satisfaction has been demonstrated to coincide with decreased dropout, the findings from both hypotheses may be used to encourage instructors to better and more consciously apply andragogy in their online classroom settings. Finally, online course and instructional designers may use these findings to incorporate more of the instructional process design elements into their designs to engender greater learning outcomes for learners, including satisfaction. Slide 16 By employing the Andragogy in Practice Inventory, instructors may hone their instructional skills Encourage instructors to better and more consciously apply andragogy in their online classroom settings. Online course and instructional designers may incorporate more of the instructional process design elements

Recommendations for Future Research The most apparent recommendation for future research is to conduct a quantitative experimental study focused on specific or single elements of the adult learning characteristics and instructional process design elements utilizing a between- or within-groups design, which may extend the present study and establish causality between the predictors examined and online learner satisfaction. Further confirmatory correlational studies may consider the adult learner characteristics portion of the API in a pre- and posttest design, and the instructional process design elements and learner satisfaction as a posttest-only design. Further quantitative correlational studies should also be employed to determine other factors not considered in the current study that may explain the remainder of the variance of online learner satisfaction. Future quantitative correlational or experimental studies should scrutinize the affect of the predictors based on learning setting; such as technical schools, business schools, organizational and professional learning, government agencies, religious organizations, or in private. Finally, further experimental, correlational, and qualitative case studies should be conducted to identify the specific behaviors that correlate with each of the instructional process design elements individually, and confirm that they continue to predict learner satisfaction, so that instructors, designers, administrators, and researchers may utilize these more specific findings in the classroom and in future research. Slide 17 A quantitative experimental study focused on specific or single elements of the adult learning characteristics and instructional process design elements Further confirmatory correlational studies Further quantitative correlational studies to determine other factors Future quantitative correlational or experimental studies based on learning setting Further experimental, correlational, and qualitative case studies to identify the specific behaviors that correlate with each of the instructional process design elements individually

Conclusions Primarily, the theoretical framework of andragogy; specifically the tenets of six adult learner characteristics and eight instructional process design elements were inferentially supported. Secondarily, the API was shown to have internal consistency as well as predictive abilities with regard to online learner satisfaction. Finally, the findings of the study provided evidence of significant, positive, predictive relationships and large effect sizes between the learner characteristics, collectively, the design elements, collectively, and online learner satisfaction. Please turn to the next slide. The theoretical framework of andragogy was inferentially supported. The API has predictive abilities with regard to online learner satisfaction. The findings of the study provided evidence of significant, positive, predictive relationships

Complete References list can be found in the dissertation manuscript Thank you for your attentiveness during the presentation of my study, findings, implications, and recommendations. What questions do you have for me? Thank You! Questions Complete References list can be found in the dissertation manuscript