Three questions guided this research study: a) Is Goal Accomplishment Style, as measured by Atman's Goal Orientation Index (GOI), related to persistence and dropout in an online, computer-conferenced class? b) Is there a relationship between other selected variables (Demographic, Personal, Institutional, and Participative) and student persistence or dropout in the online, computer-conferenced environment? And, c) Can a relationship between goal accomplishment style and the other selected student variables be identified and related to persistence and dropout in an online computer-conferenced class? The data sources for this study were students registered in twenty online, computer-conferenced courses at a mid-sized university specializing in delivering courses, both in the traditional face-to-face mode and at a distance, to working adults. Using logistic regression, this study investigated the relationship among twenty-five selected independent variables in an attempt to better understand the variables and their influence on the dichotomous dependent variable, persistence/dropout in the online classroom. The independent variables were culled from traditional classroom dropout research and adapted for use in the online environment. In addition, variables specific to the online environment were developed. The purpose of the logistic regression was to identify the most parsimonious set of variables predicting student persistence and dropout. At the end of the semester, qualitative interviews were conducted with six dropout students. The interviews were conducted in an attempt to add depth to the depth provided by the quantitative results. During the interviews the students were asked specifically about their perceptions of interactivity and collaboration in the online classroom. Using both qualitative and quantitative analyses, a more complete picture of why students participate in or dropout of online, computer-conferenced classes was developed. Three variables were identified as significant predictors of persistence/dropout, predicting persistence correctly between 98 to 100 percent of the cases. These variables included whether or not a student would recommend another online class, whether or not the student submitted assignments in a timely manner, and Acting, one of the three categories of Atman's Goal Orientation Index. Dropouts, however, proved to be more difficult to predict. (The models predictive strength regarding dropouts ranged from only to 0% to 45%.) The qualitative interviews identified the fact that the dropout students were really hybrid in that they appeared as dropouts on the institution's master list but who were persisters in other classes. Four of the six "dropout" students interviewed were taking two courses during the semester. During the interviews, the students said they found it difficult to balance the requirements of family, home, work and school while taking two classes, especially during the shortened summer semester. Almost all (95 per cent) of the study participants indicated they would be taking online courses in the future. Enrollments in online courses at the institution are increasing dramatically. Institutions must begin to examine the true nature and definition of dropouts, especially with respect to adult working students in the online environment. / Ph. D.

Internet enables construction of flexible online learning environments without time and distance barriers. However, learners typically experience isolation and alienation in online learning environments. These negative experiences can be reduced by enhancing perceived social presence of learners. With the development of learning technologies, learners can communicate asynchronously and synchronously with other participants. If social cues could be delivered adequately in online classrooms, it may become a real possibility for learners to experience the benefits that are typically only available in the social environment of a traditional classroom. However, the perceived social presence among learners is not the same for everyone. In order to better facilitate the social presence in an online classroom, this study attempted to build a model for measuring social presence and its relationships with other factors in online learning based on the social cognitive theory. An instrument with sufficient reliability and validity was developed to measure these factors. A formal study was carried out with a paper-based questionnaire for those learners who had previous learning experiences in online learning. A total of 535 valid samples were collected and analyzed from three schools in Taiwan. The method of structural equation modeling was applied to examine the proposed model and test the hypotheses. The results of measurement model testing show that five second-order constructs, user interface, mediated communication, social presence, interaction performance, and learning performance, can be synthesized from eleven first-order constructs. The results of structural model testing show that user interface and mediated communication have significant influences on social presence. User interface also has positive impact on mediated communication. Moreover, this study provided evidence that social presence has significant effects on interaction performance, and then interaction performance has significant effects on learning performance. Finally, the implications of research findings were discussed for further research directions and practical applications.

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In response to the COVID-19 pandemic, many students have been forced to learn online. However, more information is needed about effective strategies for promoting active engagement in the online classroom, particularly the impact of peer modeling. This study investigated peer modeling and behavioral skills training to increase hand raising and question asking/answering behavior in six elementary school students. The study employed a multiple baseline across participants design, with data collected live during Zoom sessions by three research assistants, one acting as the teacher and two acting as peer models. Latency to speech was also coded subsequently to the live session as a shyness measure. Although minor improvements were observed in hand raising behavior in one participant and question answering in two participants, overall baseline engagement was higher than anticipated, which limited the magnitude of the observed improvements. High baseline engagement rates demonstrated that participants engaged actively in online classrooms without intervention. Future research should investigate the effectiveness of teacher prompting and peer modeling separately and target children that are not engaging on their own.