Contributing+to+Theory


 * ** EDU7006-8 ** ||  ||
 * ** Quantitative Research Design ** || ** 6 Contributing to Theory ** ||
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=Contributing to Theory: Independent, Mediating, Moderating, and Dependent Variables = The rapid advances of technology over the past decade have led to a dramatic shift in the demographics of post-secondary students, as about 40% are over the age of 25 and a majority of these more mature learners are increasingly choosing e-learning to pursue higher education ( Ke & Xie, 2009 ) and professional development ( Gunawardena, Linder-VanBerschot, LaPointe, & Rao, 2010 ). Adults, or nontraditional students, learn differently than traditional students or younger adults who enter post-secondary education straight from secondary education ( Bye, Pushkar, & Conway, 2007; Ke & Xie, 2009; Kenner & Weinerman, 2011; Zemke & Zemke, 1995 ). Historically, these differences have been ignored in higher education, and in online courses, where the same pedagogies and curriculum face both the traditional and non-traditional learner ( Ke & Xie, 2009 ). There has also been little research outside of higher education regarding how mature adults learn best in a virtual classroom ( Chen & Lien, 2011; Donavant, 2009 ). Articles specific to professional development and e-learning, published within the past five years, have been chosen for analysis regarding their contributions to online learning theory through operationalized independent, dependent, moderating, and mediating variables.

The New, Modern Practice of Adult Education
<span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">In a three phase, quasi-experimental quantitative study of American police officers, Donavant (2009) looked at the “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">efficacy of online education for professional development <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 239 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">) and found that learning took place with respect to both online and traditional instruction and that there was no “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">statistically significant difference in the effectiveness of the two delivery methods <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 239 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">). This study also showed no significant differences between these modes with respect to gender, race, age, number of years on the force, or previous exposure to online education, but did show a significant association between level of formal education and potential success with online learning. Phase one consisted of historical data of performance from various courses without descriptive information.* In phase three, open-ended questions were asked of 150 participants, and they indicated four attractive features of online education, which were; (a) general convenience, (b) flexibility in scheduling, (c) remote access, and (d) self pacing of learning. The least attractive feature was “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">the lack of personal interaction or face-to-face contact with the facilitator or other learners <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 239 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">). One problem noted was that “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">little research has been conducted within the professional development environment, that arena involving training relative to the current occupation of the adult learner <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 227 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">). <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">The study’s theoretical framework was based on Andragogy, and <span style="color: #ff0000; font-family: 'Times New Roman',Times,serif; font-size: 120%;">Donavant (2009) * <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">sought to expand knowledge of techniques for professional development in adult education since empirical research “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">is almost nonexistent <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">Donavant, 2009, p. 229 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">). In effect, however, <span style="color: #ff0000; font-family: 'Times New Roman',Times,serif; font-size: 120%; text-decoration: line-through;">the study <span style="color: #ff0000; font-family: 'Times New Roman',Times,serif; font-size: 120%;"> Donavant (2009) <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">did not study techniques of adult education, but rather delivery methods and their effect on learning. Two delivery methods were identified as the independent variable, while effect on learning, the dependent variable, was based on participant perceptions regarding willingness to continue to use, experience with, and practicality of online learning for delivery of professional development training as mediating variables.* Several analyses were run on the data, including descriptive <span style="color: #ff0000; font-family: 'Times New Roman',Times,serif; font-size: 120%;"> statistics <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">, chi-squared, t-tests, and analysis of covariance. <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">The contributions of this study to theory are three-fold. First, Donavant (2009) noted that there is little empirical research regarding professional development courses in online adult education, as opposed to a large amount of online adult education research in higher education. Of importance to theory* is whether there is a difference between types of adult education. Do adults seeking professional development learn differently or have different motivations than do adults in higher education programs? While this article does not directly look at this contribution to theory; it does demonstrate that the mode of delivery for professional development courses does not appear to matter. This result is similar to numerous studies in higher education showing the same thing. Second, Donavant (2009) identified that online learning may not be effective or practical in terms of certain types of learning. This article thus contributes to theory in documenting that for law enforcement, online education is “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">an appropriate method of delivery for professional development <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 238 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">). Finally, Donavant (2009) contributed to theory and more effective online training by documenting the factors of satisfaction and dissatisfaction with online education. Without knowing what works, and what does not, it is impossible to improve.

<span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">Length of Online Course and Student Satisfaction
<span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">Ferguson and DeFelice (2010) presented an exceptional review of the literature regarding the factors effecting satisfaction with courses taught online, concluding “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">that connectedness to the course, either by participating collaboratively with other students or by interacting with the professor, will likely impact student satisfaction <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 75 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">) the most. Equivalency theory, which posits that regardless of delivery mode “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">course learning experiences. . . should be designed in order to provide equivalent learning <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 75 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">), was utilized as the theoretical framework for this study to determine if “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">there were differences in online student satisfaction, perceived learning, and performance <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 76 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">) when the independent variable was length of the course; in this case five-weeks versus fifteen-weeks, while all other pedagogical factors were kept constant. The dependent variable learning, was measured using “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">final grades from a total of 114 students. . . from three summer [(5-week)] sessions and four full-semester [(15-week)] sessions <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 77 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">). Equivalency theory was supported in this study because students were taught the same material, in the same ways, utilizing the same professor, in both formats. In part one of the study, 75 graduate students were administered a 15-question Likert scale survey to measure the moderating variables of student satisfaction and perceived learning. Statistical analyses of the data included descriptive and t-tests to determine if there were differences between the 5-week and 15-week formats regarding learning, student satisfaction, and perceived learning. <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">Students were significantly more satisfied with the interaction with the teacher in the longer format, while students were significantly more satisfied with the interaction with fellow students in the shorter format. No significant difference was found for perceived learning or desire to take additional online classes between the two format lengths. Students in the shorter sessions showed significantly stronger “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">academic performance than the full-semester students <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">Ferguson & DeFelice, 2010, p. 81 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">). Improvements to the pedagogy of the class were identified for both formats. In regard to the shorter format a shift needs to be made “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">to emphasize interaction with the professor <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 81 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">) and several possibilities were proposed. Limitations to the study were that students in the shorter format (summer semester) may have been different from those attending the longer format (regular semesters) and that students were not randomly selected. This article contributes to adult learning theory by being “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">the first to explore how different formats. . . influence student attitudes and academic performance <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 81 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">).

<span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">Predictors of Learner Satisfaction and Transfer of Learning
<span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">In a mixed-methods design, Gunawardena et al. (2010) conducted a survey, face-to-face, and phone interviews, and administered an open-ended questionnaire to gather data on the perceptions of students, instructors, and instructional designers to determine that “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">online self-efficacy [was the] strongest predictor of learner satisfaction; [while] collegial support was the strongest predictor of transfer of learning <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 207 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">) in a professional development program. The major problems in the current literature in terms of distance education in the corporate sector is that they describe only “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">specific contexts and programs <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 208 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">) and there is a need to move beyond case studies to determine the characteristics of training that “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">lead to learning gains, transfer of learning, and satisfaction <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 208 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">).* <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">Four independent variables were measured in part one of the study, “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">online self-efficacy, course design, learner-instructor interaction, and learner-learner interaction <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">Gunawardena et al., 2010, p. 211 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">), with the dependent variable being online learning success. Mediating variables were learner satisfaction and transfer of learning. All variables were operationalized as scores on the Learner Satisfaction and Transfer-of-learning Questionnaire (LSTQ) developed by the authors and validated prior to the study. Regression analysis identified a close relationship between the independent variables and the dependent variable, with “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">88 percent of the total variability <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 217 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">) associated with the four factors. Gunawardena et al. (2010) contributed to theory by adding to knowledge regarding adult professional development and “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">moved online education research in corporate settings beyond descriptive case studies to understanding factors that promote learner satisfaction and transfer of learning <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 224 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">).

<span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">What Types of Learning Style Leads to Online Participation
<span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">Huang, Lin, and Huang (2012) extended previous research by testing a model that examined the mediating process of prior knowledge in the relationship between learning style and e-learning performance. They posited that (a) learning style is positively related to online participation, (b) that online participation is positively related to e-learning performance, and (c) the greater the prior knowledge, the stronger the relationship between online participation and learning performance. This study included 219 college students in a single course and measured (a) student learning style using the Index of Learning Styles (ILS) survey, (b) student online participation through “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">recorded student online trails <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 344 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">), (c) student performance as measured by scores on tests, (d) prior knowledge of the tool used in the course based on a 5-point Likert scale, and (e) the control variables of gender, computer experience, and Internet experience. <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">Huang et al. (2012) used structured equation modeling (SEM) to analyze the data. Support was found that online participation is a mediating construct between learning style and performance. The study also found that sensory learning style individuals tend to participate more frequently and for a longer duration. Prior knowledge was shown to moderate the relationship between participation and learning performance only in terms of passive participation. Several recommendations were made by the Huang et al. (2012). First, “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">although it is difficult to determine the degree of influence of the mediating construct, educational institutions should take action to boost ‘students’ online participation in e-learning courses <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 347 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">). Second, “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">most learners appear to be able to benefit [from e-learning] immediately <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 347 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">). The authors also commented on several suggestions for further research, namely (a) the model needs to be tested in different subject contexts, (b) additional mediating processes that link learning styles and learning performance should be explored, and (c) a more mature, professional, and autonomous set of online learners should be enlisted.

<span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">Faculty Actions that Result in Student Satisfaction in Online Course
<span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">This quantitative research study <span style="color: #ff0000; font-family: 'Times New Roman',Times,serif; font-size: 120%;">by Jackson, Jones and Rodriguez (2010), <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;"> correlated faculty actions with student satisfaction in online classes at two community colleges in Texas. Data for the study was obtained from student responses to each institution’s existing online course evaluation. All online students were requested to fill out the online evaluation, and 426 students (30%) from College 1 and 1004 students (69%) from College 2 participated. Descriptive statistics, bivariate correlations, and multiple regressions were used to identify the faculty actions that affected student satisfaction in online courses. Jackson et al. (2010) determined that “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">student satisfaction with online courses appears to be impacted by instructor actions within the course <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 91 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">). The highest correlations with student satisfaction were “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">timeliness/accessibility of instructor, clearly stated expectations, instructor enthusiasm, and comfortable climate <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">p. 91 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">) and a moderate correlation existed with activities.* Multiple regression analysis indicated that 69% of the variance of student satisfaction could be explained by those independent variables. <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">Jackson et al. (2010) utilized a theoretical framework drawn from Chickering and Gamson (1987) and “ <span style="color: #0000ff; font-family: 'Times New Roman',Times,serif; font-size: 120%;">sought to clarify the relationship between student satisfaction and student learning in the online classroom <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">” ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">Jackson et al., 2010, p. 82 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">). The data was analyzed separately for each college, as well as across institutions, due to each college’s online evaluation being different. For College 1, seven independent variables were selected, including directions, timeliness, expectations, enthusiasm, climate, and activities* that were measured using a 5-point Likert scale. The dependent variable for College 1 was value, which was also measured using a 5-point Likert scale. College 2 measured two independent variables, timeliness and activities, and one dependent variable, value; all measured with a 5-point Likert scale. The across institution interaction was analyzed using Levene’s test for equality of variances, a one-way analysis of variance (ANOVA) to identify differences, and t-tests to confirm the differences. <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">Jackson et al.’s (2010) article contributes to theory by identifying specific actions that instructors can perform in their online courses to increase student satisfaction. The article contains good discussion from the literature regarding the impact of faculty on student satisfaction in online classes and then confirms this result in the findings. The findings clarify that instructor actions directly impact student satisfaction, and which actions are most effective in doing so.

<span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">Gap Analysis
<span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">The largest factor of dissatisfaction in adult online learning is the lack of face-to-face interaction by the learner with the facilitator or other learners ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">Alshare, Freeze, Lane, & Wen, 2011; Boling, Hough, Krinsky, Saleem, & Stevens, 2012; Donavant, 2009; Pigliapoco & Bogliolo, 2008 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">). Dissatisfaction culminates in markedly higher dropout rates ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">Al-Fahad. 2010; Pigliapoco & Bogliolo, 2008 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">), decreased motivation to learn ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">Omar, Kalulu, & Belmasrour, 2011; Park & Choi, 2009 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">), less participation, and consequently, less learning ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">Jackson et al., 2010; Martinez-Caro, 2009; Shea, Fredericksen, & Pickett, 2006; Zemke & Zemke, 1995 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">). A relationship has been demonstrated between online participation and learning performance ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">Huang et al., 2012; Martinez-Caro, 2009; Pelz, 2010; Ruey, 2010 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">), as well as between learning performance and student satisfaction in online courses ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">Ali & Ahmad, 2011; Chen & Lien, 2011; Ferguson & DeFelice, 2010; Kozub, 2010; Martinez-Caro, 2009 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">). However, there is little empirical research regarding <span style="color: #ff0000; font-family: 'Times New Roman',Times,serif; font-size: 120%;">online <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">adult professional development or appropriate techniques for teaching and engaging non-traditional learners ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">Chen & Lien, 2011; Donavant, 2009 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">), or on appropriate modes of interaction in learning management systems ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">So & Bonk, 2010 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">). The specific problem to investigate involves identifying factors in an online adult professional development learning environment that can eliminate or moderate the lack of face-to-face interaction, fostering increased learner participation, satisfaction, and perceived learning, which contribute to online learning success.* Knowledge gained will enlarge the currently small knowledge base regarding online professional development training ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">Chen & Lien, 2011; Donavant, 2009 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">), will contribute a better understanding of facilitating engaging online instruction ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">Bradley, 2009; Huang et al., 2012 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">), and assist in identifying the proper level and types of media for use in the online classroom ( <span style="font-family: 'Times New Roman',Times,serif; font-size: 90%;">Fletcher, Tobias, & Wisher, 2007; Martinez-Caro, 2009 <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">).

<span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">Proposed Study
<span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">I propose a quasi-experimental nonequivalent groups study to investigate whether the addition of a visual element (webcam) can foster increased online success as mediated by increased learner participation, increased learner satisfaction, and increased perceived learning in an online adult professional development learning environment. At least ten instructors will teach two instances of two separate live virtual courses (LVC) for a US-based technology company. One instance of each course will be a control and one will utilize the webcam to promote additional interaction for the student-instructor relationships, and attempt to mitigate the lack of face-to-face interaction noted as the primary source of dissatisfaction for online students. The students of these LVC, who can sign in from any location worldwide, will be surveyed after each class to ascertain their satisfaction, engagement, and perceived learning with the class as measured by sections of the Learner Satisfaction and Transfer-of-learning Questionnaire (LSTQ) developed by Gunawardena et al. (2010). A one-way analysis of variance (ANOVA) and t tests will be conducted to determine whether the use of the visual element increases the mediating variables of learner participation, satisfaction, or perceived learning in the experimental classes versus the control classes thereby promoting online success.

<span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;"> [TT1] What about phase two? <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">[TT2] It is not the study's framework that seeks to expand knowledge, it is the researcher. <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">[TT3] This sentence is slightly confusing. Which variables are dependent and which are mediating? <span style="font-family: 'Times New Roman','serif'; font-size: 16px;">[TT4] <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">This is another case of personification. It is not really important to the theory, but to our development or understanding of the theory. <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">[TT5] Check subject/verb agreement here. <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">[TT6] Which activities? Do you mean assignment? <span style="color: #ff0000; font-family: 'Times New Roman',Times,serif; font-size: 120%;">[No, in this study, the variable is called Activities. This is what I am referencing here.] <span style="color: #000000; font-family: 'Times New Roman',Times,serif; font-size: 120%;">[TT7] Again what type of activities? <span style="color: #ff0000; font-family: 'Times New Roman',Times,serif; font-size: 120%;"> [In the article, the type of activities was not specified.] <span style="font-family: 'Times New Roman',Times,serif; font-size: 120%;">[TT8] I see that you have updated this, but it is still written in terms of a restated purpose. This is something you can get your dissertation chair’s opinion on as well. But, I recommend trying to write it in negative terms. For example, if the purpose is to identify the factors that alleviate the lack of face to face interaction in online education, then the problem might be that we don’t know what factors would help alleviate this problem. Do you see the difference?


 * = References ||
 * * Al-Fahad, F. N. (2010). The learners’ satisfaction toward online e-learning implemented in the college of applied studies and community service, King Saud University, Saudi Arabia: Can e-learning replace the conventional system of education? //Turkish Online Journal of Distance Education (TOJDE), 11//(2), 61-72. Retrieved from https://tojde.anadolu.edu.tr/
 * Ali, A., & Ahmad, I. (2011). Key factors for determining students’ satisfaction in distance learning courses: A study of Allama Iqbal Open University. //Contemporary Educational Technology, 2//(2), 118-134. Retrieved from http://cedtech.net/
 * Alshare, K. A., Freeze, R. D., Lane, P. L., & Wen, H. J. (2011). The impacts of system and human factors on online learning systems use and learner satisfaction. //Decision Sciences: Journal of Innovative Education, 9//(3), 437-461. doi:10.1111/j.1540-4609.2011.00321.x
 * Boling, E. C., Hough, M., Krinsky, H., Saleem, H., & Stevens, M. (2012). Cutting the distance in distance education: Perspectives on what promotes positive, online learning experiences. //Internet and Higher Education//. doi:10.1016/j.iheduc.2011.11.006
 * Bradley, J. (2009). Promoting and supporting authentic online conversations – which comes first – the tools of instructional design? //International Journal of Pedagogies and learning, 5//(3), 20-31. doi:10.5172/ijpl.5.3.20
 * Bye, D., Pushkar, D., & Conway, M. (2007). Motivation, interest, and positive affect in traditional and nontraditional undergraduate students. //Adult Education Quarterly//, //57//, 141<span style="font-family: 'Cambria','serif';">‐ 158. doi:10.1177/0741713606294235
 * Chen, L.-C., & Lien, Y.-H. (2011). Using author co-citation analysis to examine the intellectual structure of e-learning: A MIS perspective. //Scientometrics, 89//, 867-886. doi:10.1007/s11192-011-0458-y
 * Chickering, A. W., & Gamson, Z. F. (1987). Seven principles for good practice in undergraduate education. //American Association for Higher Education Bulletin, 39//(7), 3-7. Retrieved from ERIC database. (ED282491)
 * Donavant, B. W. (2009). The new, modern practice of adult education: Online instruction in a continuing professional education setting. //Adult Education Quarterly, 59//(3), 227<span style="font-family: 'Calibri','sans-serif';">‐ 245. doi:10.1177/0741713609331546
 * Ferguson, J. M., & DeFelice, A. E. (2010). Length of online course and student satisfaction, perceived learning, and academic performance. //International Review of Research in Open and Distance Learning, 11//(2), 73-84. Retrieved from http://www.irrodl.org/index.php/irrodl
 * Fletcher, J. D., Tobias, S., & Wisher, R. A. (2007). Learning anytime, anywhere: Advanced distributed learning and the changing face of education. //Educational Research, 36//(1), 96<span style="font-family: 'Calibri','sans-serif';">‐ 102. doi:10.3102/0013189X07300034
 * Gunawardena, C. N., Linder-VanBerschot, J. A., LaPointe, D. K., & Rao, L. (2010). Predictors of learner satisfaction and transfer of learning in a corporate online education program. //The American Journal of Distance Education, 24//(1), 207-226. doi:10.1080/08923647.2010.522919
 * Huang, E. Y., Lin, S. W., & Huang, T. K. (2012). What type of learning style leads to online participation in the mixed<span style="font-family: 'Calibri','sans-serif';">‐ mode e<span style="font-family: 'Calibri','sans-serif';">‐ learning environment? A study of software usage instruction. //Computers & Education//, 58(1), 338<span style="font-family: 'Calibri','sans-serif';">‐ 349. doi:10.1016/j.compedu.2011.08.003
 * Jackson, L. C., Jones, S. J., & Rodriguez, R. C. (2010). Faculty actions that result in student satisfaction in online courses. //Journal of Asynchronous Learning Networks, 14//(4), 78-96. Retrieved from http://jaln.sloanconsortium.org/index.php/jaln
 * Ke, F., & Xie, K. (2009). Toward deep learning for adult students in online courses. //Internet and Higher Education, 12//, 136-145. doi:10.1016/j.iheduc.2009.08.001
 * Kenner, C., & Weinerman, J. (2011). Adult learning theory: Applications to nontraditional college students. //Journal of College Reading and Learning, 41//(2), 87-96. Retrieved from http://www.crla.net/journal.htm
 * Kozub, R. M. (2010). An ANOVA analysis of the relationships between business students' learning styles and effectiveness of web based instruction. //American Journal of Business Education, 3//(3), 89-98. Retrieved from http://journals.cluteonline.com/index.php/AJBE
 * Martinez<span style="font-family: 'Cambria','serif';">‐ Caro, E. (2011). Factors affecting effectiveness in e<span style="font-family: 'Cambria','serif';">‐ learning: An analysis in production management courses. //Computer Applications in Engineering Education, 19//(3), 572<span style="font-family: 'Cambria','serif';">‐ 581. doi:10.1002/cae.20337
 * Omar, A., Kalulu, D., & Belmasrour, R. (2011). Enhanced instruction: The future of e-learning. //International Journal of Education Research, 6//(1), 21-37. Retrieved from http://www.journals.elsevier.com/international-journal-of-educational-research/
 * Park, J.-H., & Choi, H. J. (2009). Factors influencing adult learners’ decision to drop out or persist in online learning. //Journal of Educational Technology & Society, 12//(4), 207-217. Retrieved from http://www.ifets.info/journals/12_4/18.pdf
 * Pelz, B. (2010). (My) three principles of effective online pedagogy. //Journal of Asynchronous Learning Networks, 14//(1), 103-116. Retrieved from http://sloanconsortium.org/publications/jaln_main
 * Pigliapoco, E. E., & Bogliolo, A. A. (2008). The effects of psychological sense of community in online and face-to-face academic courses. //International Journal of Emerging Technologies in Learning, 3//(4), 60-69. Retrieved from http://www.online-journals.org/i-jet
 * Ruey, S. (2010). A case study of constructivist instructional strategies for adult online learning. //British Journal of Educational Technology, 41//(5), 706-720. doi:10.1111/j.1467-8535.2009.00965.x
 * Shea, P., Fredericksen, E., & Pickett, A. (2006). Student satisfaction and perceived learning with on-line courses: Principles and examples from the SUNY learning network. //Journal of Asynchronous Learning Networks, 4//(2), 2-31. Retrieved from http://sloanconsortium.org/publications/jaln_main
 * So, H.-J., & Bonk, C. J. (2010). Examining the roles of blended learning approaches in computer-supported collaborative learning (CSCL) environments: A Delphi study. //Educational Technology & Society//, //13//(3), 189–200. Retrieved from ERIC Database. (EJ899878)
 * Zemke, R., & Zemke, S. (1995). Adult learning: What do we know for sure? //Training, 32//, 69-82. Retrieved from ERIC Database. (ED504481) ||