Usage rates of blogs, social media, and online courses have been exponentially increasing in the last decade, especially among the college student population (Knight-McCord, et al., 2016). While the benefits of these platforms, including connectivity, visibility, social feedback, persistence, and accessibility are attractive to students as an online learning tool, there is a rising concern regarding privacy and confidentiality. This study aimed to investigate how students’ privacy and confidentiality concerns and attitudes influence their participation level and degree of openness within an online learning environment. Communication privacy management (CPM) theory served as the theoretical framework for this study in order to focus on understanding the way people perceive and manage privacy, both personally and with others. A quantitative correlational research design was selected for this study to examine the relationship between privacy concerns among students enrolled in a bachelor’s, master’s, or doctorate program at a Midwestern university and their participation levels within blogs, social media, and online courses. The quantitative software package SPSS was used to conduct multivariate analysis of variance (MANOVA) to test for the statistical significance of the variables.

eLearning continues to be the fasted growing segment of higher education. With this growth, challenges for higher education institutions have arisen. One of these difficulties is preparing students for learning online. A qualitative case study examined what strategies and processes contributed to student success in eLearning at a Florida public college based on the views of eLearning educators, faculty teaching online courses and the students who have taken online courses. The aspects reviewed were: 1. what contributed to student success, 2. what hindered student success, 3. what prepared students for learning online, and 4. what assistance was available for students that face challenges with online courses. The interviews and questionnaire were examined and compared from the perspectives of educators (eLearning staff and faculty teaching online courses), and students taking the courses, and documents reviewed from the site chosen, to show what are the most significant contributors and hindrances to eLearning success for participants at a Florida public state college. The findings of this study show what helped student success, what hindered student success, what prepared students for eLearning, and what support was available to students while taking an eLearning course from the data collected through the student questionnaire, faculty and staff interviews, and document review. The data supports the finding that student motivation, student time management skills, eLearning course design, and the responsiveness and supportiveness of faculty contribute to the success of the student in eLearning courses. The data supports the finding that what hinders student success is when the student is overwhelmed, distracted, or lacks motivation or time management skills. Additionally, the design of the eLearning course can hinder the student and if there is a lack of faculty communication. The data supports the finding that what prepared students for eLearning was the College’s free eLearning orientation course that explains how to use the Learning Management System and the best practices of learning online. The data supports the finding that the support available to assist students that are enrolled in eLearning is College “Support”, Tutoring (both online and on campus), and their course professor. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2020. / FAU Electronic Theses and Dissertations Collection

We present a novel method for learning Support Vector Machines (SVMs) in the online setting. Our method is generally applicable in that it handles the online learning of the binary, multiclass, and structural SVMs in a unified view. The SVM learning problem consists of optimizing a convex objective function that is composed of two parts: the hinge loss and quadratic regularization. To date, the predominant family of approaches for online SVM learning has been gradient-based methods, such as Stochastic Gradient Descent (SGD). Unfortunately, we note that there are two drawbacks in such approaches: first, gradient-based methods are based on a local linear approximation to the function being optimized, but since the hinge loss is piecewise-linear and nonsmooth, this approximation can be ill-behaved. Second, existing online SVM learning approaches share the same problem formulation with batch SVM learning methods, and they all need to tune a fixed global regularization parameter by cross validation. On the one hand, global regularization is ineffective in handling local irregularities encountered in the online setting; on the other hand, even though the learning problem for a particular global regularization parameter value may be efficiently solved, repeatedly solving for a wide range of values can be costly. We intend to tackle these two problems with our approach. To address the first problem, we propose to perform implicit online update steps to optimize the hinge loss, as opposed to explicit (or gradient-based) updates that utilize subgradients to perform local linearization. Regarding the second problem, we propose to enforce local regularization that is applied to individual classifier update steps, rather than having a fixed global regularization term. Our theoretical analysis suggests that our classifier update steps progressively optimize the structured hinge loss, with the rate controlled by a sequence of regularization parameters; setting these parameters is analogous to setting the stepsizes in gradient-based methods. In addition, we give sufficient conditions for the algorithm's convergence. Experimentally, our online algorithm can match optimal classification performances given by other state-of-the-art online SVM learning methods, as well as batch learning methods, after only one or two passes over the training data. More importantly, our algorithm can attain these results without doing cross validation, while all other methods must perform time-consuming cross validation to determine the optimal choice of the global regularization parameter.

Online learning sessions are becoming increasingly common. In this study, we reviewed over 150 studies of online and blended learning, revealing that the factors that affect student preferences for online or in-person learning vary widely and compiled a table of these factors. They can be categorized as either learning preferences or current lifestyle conditions. To better understand these preferences, we implemented an intervention in which college-level engineering students were given the choice to attend either an online or in-person session for a class they normally attended in a different modality. We compared college students' stated preferences with demonstrated attendance for online or in-person instruction. We surveyed approximately 150 undergraduate students from two different courses in engineering who participated in both in-person and online learning experiences. We conducted a pre and post survey, created based on the categories formed from our literature review. Data were analyzed using a paired sample t-test, Phi correlations, and structural equation modeling in order to determine the most salient combination of preferences that affect students' choice to attend either an online or in-person class. Furthermore, this research specifically sought to understand why students' stated preferences may or may not align with their demonstrated attendance for online or in-person learning. Based on survey results, we used targeted interviews to understand student choices from 13 students whose choices did not match their stated preferences. We found that most students in our context of a typical in-person university prefer in-person instruction, but they also want some online class sessions if it is more convenient for them at the time. Through applying The Reasoned Action Approach and Model, we analyzed students' stated preferences and compared these with their demonstrated actions. The analysis revealed that students' self-prediction via a survey about whether or not they would attend an online class session was statistically significant at predicting their actual attendance, whereas stated preference for some online class sessions were not predictive. This finding suggests that preference-based surveys may not reliably predict students' actions in regards to attending online or in-person class sessions. Instead, we recommend using a survey with an appropriate predictive question, which will allow universities and professors to determine if it will be worth investing the time and resources in to creating online class sessions.

Magister Curationis - MCur / Digital integration is evident in many countries and across all sectors. The need for integration of Information and Communications Technology with higher education was almost inevitable because of the effect of the COVID-19 pandemic. The closure of higher education institutions in South Africa has made it mandatory for institutions to transition from traditional face-toface classroom learning to online learning. This mitigation left minimal time to achieve institution readiness in adopting this new manner of learning and subsequently will influence the students’ learning experiences.

K-12 online learning continues to grow, and with it, the need for well-trained online teachers. This multiple-article dissertation explores K-12 online teaching professional development. A literature review describes research trends regarding unique strategies and competencies related to online teaching. It explores strategies such as acting as a facilitator, developing course knowledge, encouraging student engagement, interacting regularly with students, giving feedback, and developing time management skills. The literature review suggests that there is a lack of specific recommendations about what content should be covered and why professional development is beneficial for both teachers and students. Programs that incorporate online teaching professional development specific to their model may have more satisfied and motivated students and teachers. The second article provides insight into the design process for a K-12 online teaching professional development course that focuses on effectively communicating with online students. The course is designed as a professional development opportunity to enhance teachers' knowledge of online pedagogy and technology skills unique to communicating in the online environment. The course contains hands-on experiences and activities, allowing teachers the opportunity to learn in the role of teacher and student. The professional development was designed using Desimone's five core features commonly used for traditional classroom teacher professional development. This article describes the professional development goals, course structure, evaluation process, and preliminary findings. By sharing the development and design of this professional development course the hope is that other K-12 online designers and administrators will have a framework on which to build. The final article presents the implementation and evaluation results of the professional development course mentioned in article two. This case study shares the learning perspective of 80 teachers that completed the professional development course through pre and post assessments and a course evaluation. Researchers conducted interviews with 11 participants to further explore how the course impacted their pedagogical and technical knowledge in relation to effectively communicating with their online students. Overall, participants reported a satisfactory experience and personal growth in the topics provided. More research is needed on the effects of professional development for online teachers and if it can help lead to student success.

This mixed methods study sought to uncover the needs of culturally diverse students in the online learning environment. Several of the unexplored factors that may contribute to high attrition rate among online undergraduate students, were also analyzed. The study examined how the variables of prior educational experience, age, gender, ethnicity, country of birth, and first or native language spoken contributed to success in online classes. The research also explored how institutional support contributed to the success of online learners. Through the use of survey data collection and interviews, the results of this study indicated that culturally diverse learners reported three skills that are essential to their success in online learning environments: time management, self-directedness, and computer or technical skills. Students also indicated that institutional and instructor support are vital to their success in online classes. Although all variables examined were not significant predictors to the success of online learners, the results of this study provide insight into the needs of culturally diverse learners. These findings may be helpful to educators and policymakers when planning for or designing online courses for culturally diverse learners. These findings may also aid in reducing the high attrition rate of culturally diverse learners in online environments by encouraging more readiness assessments for students enrolling in online courses to determine their level of readiness for online learning. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2020. / FAU Electronic Theses and Dissertations Collection

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Applied Behavior Analysis has experienced an increase need for practitioners at all certification levels. Most recently, a demand for the paraprofessional-level certification, the Registered Behavior Technician™ (RBT®), is being driven by state licensure and health insurance reform. This has subsequently led to pressure to quickly train paraprofessionals to work with at-need clients. While this growth is favorable for the field it means that agencies are often at odds with balancing quality and breadth of knowledge, which can negatively impact clients’ lives. Furthermore, outside of basic minimum training standards, the behavior analytic governing bodies do not currently regulate RBT trainings the way they do for higher levels of certification, leaving it up to training supervisors to determine competency. In a series of experiments, some of the concerns with respect to RBT training will be addressed. The first will determine if an online curriculum is feasible for training RBT candidates to a level of proficiency for conceptual and practical knowledge. The second thread of research will examine if Acceptance and Commitment Training can lead to gains in RBT performance. Implications for the findings as well as future directions are discussed.

Blended Online Learning (BOL) combines synchronous and asynchronous online learning in ways that potentially can overcome limitations of fully asynchronous online. Although BOL has been an emergent modality for decades, research on the experiences, benefits and challenges of its implementation has been limited. However, the Covid-19 pandemic forced many college courses to go fully online, including courses with hands-on learning components assumed to require face-to-face instruction to support learners. For this study, the pandemic disruption offered an authentic learning setting to investigate the learning and experiences of pre-service teachers in a technology course that was forced into a fully online BOL modality. Previously, the technology course was delivered in a Blended Learning modality (BL) that combined face-to-face computer lab meetings with asynchronous online materials and activities using a Learning Management System (LMS). BOL replaced face-to-face meeting with synchronous online (e.g., Zoom) meetings.The purpose of this study was to explore if BL and BOL course modalities would generate different student outcomes in terms of rubric scores obtained on a final project (competence), along with student-written reflections on the final project (confidence/self-efficacy) that covered topics and skills such as digital audio, digital video, and PowerPoint. The study showed that students enrolled in the BL modality obtained higher scores on the final project as compared to students engaged in the BOL modality. On the other hand, BOL students made a higher number of problem-solving statements in their written reflections about the final project, displaying an antifragile disposition. This study contributes to the existing body of research on online learning modalities by exploring the dimension of competency and self-efficacy of students enrolled in blended and blended online versions of a course with concentration on learning technology. The findings of this study can inform decisions of teacher education administrators and faculty about how they are going to integrate educational technology into Teacher Education Programs. Further, the study has implications for adopting BOL modality in a range of higher education courses in which fully online delivery has been resisted because of students’ assumed needs for face-to-face support in skills learning.