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Doctor of Philosophy(PhD) / This thesis argues that it is only through understanding the multiple facets of technology that we are able to determine whether any particular manifestation of technology is educational. The reconstruction of educational technology in this thesis begins by building an understanding of the concept of experiential technology from the work of Heidegger, Dewey and Popper. This provides the conceptual architecture required to research the influence of educational technology in universities, which is interpreted in light of the wider theory of modernisation of society developed by Jürgen Habermas. The critical theory of technology formulated by Feenberg provides the methodological basis for reconstructing an understanding of technology and its impact on student learning. A reconstructive analysis requires a number of situational critiques, which in this thesis review the advice given to academic staff about the use of educational technology. It is through a synthesis of these critiques that this thesis examines whether higher education is undergoing a process of colonisation that has reduced its potential to discuss the values of university teaching and learning. Online learning is taken as a case example that has been embraced by academics for dealing with increasing student numbers and the increasing importance of work-based learning. By shifting from the theory of technology to the practice of the Australian Technology University, this thesis demonstrates that one approach to coping with change in the higher education context is to incorporate business values, have increasingly flexible curricula and focus on workplace skills. This thesis concludes that universities could go a lot further to incorporate the values of higher education into educational technology. In the case of the online learner this would support those distinctive characteristics that encourage a deep approach to learning. Following arguments put forward by Feenberg, it is argued that it is through student participation in technical design that we have the greatest chance of influencing technology’s development to emphasize the values of higher education. As long as academics continue to control the technological decision-making, the delivery and management of information is likely to remain the most common use of online technology. The legitimacy of the academic’s decision to use technology in their teaching increases where there is only a narrow gap between the values of the participants and the reality of their practice. Thus, to be morally just and provide students with the developmental opportunities that will serve them in their later professional and citizenship roles, the online classroom needs to ensure that it provides an autonomy-supporting environment.

Leaders in higher education institutions throughout the United States regard distance learning as an important part of their long-term strategic planning (Allen & Seaman, 2015). Counselor education and supervision training programs are following this trend as demonstrated by the increase of online programs being offered to train professional counselors (Renfro‐Michel, O'Halloran, & Delaney, 2010). Some studies have investigated how online supervision compares to in-person or face-to-face counselor training (e.g., Lenz, Oliver, & Nelson, 2011). However, little is known about counselor educators’ experiences of online group supervision. A phenomenological case study explored the counselor educators’ lived experiences of resistance during online group supervision in Council for Accreditation of Counseling and Related Educational Program (CACREP) accredited programs. The results of the study identified four themes: the supervisory relationship matters, differences exist between online and face-to-face supervision, positionality and privilege influence resistance, and resistance is dynamic. The study’s findings could enhance the field’s understanding of resistance and expand on how to consider and approach resistance during online supervision.

The purpose of this study was to examine whether there are significant relationships between the general satisfaction of students and learner-content interaction, learner-instructor interaction, learner-learner interaction, and learner-technology interaction in 100% online courses. There were 310 responses from the students. This study did not use data from duplicate students and instructors. Excel was used to find duplicate students and instructors; therefore, 128 responses were deleted. After examination of box plots, an additional four cases were removed because they were outliers on seven or more variables. Nineteen responses were deleted because they did not answer all questions of interest, resulting in a total sample of 159 students. Multiple regression analysis was used to examine the relationship between the four independent variables and the dependent variable. In addition to tests for statistical significance, practical significance was evaluated with the multiple R2 , which reported the common variance between independent variables and dependent variable. The two variables of learner-content and learner-instructor interaction play a significant role in predicting online satisfaction. Minimally, the variable learner-technology can predict online satisfaction and is an important construct that must be considered when offering online courses. Results of this study provide help in establishing a valid and reliable survey instrument and in developing an online best learning environment, as well as recommendations for institutions offering online learning or considering the development of online learning courses.

At a local community college in Texas, student retention remained a concern as enrollment was increasing while online student retention was decreasing. The purpose of this study was to examine student retention in online courses at the college. The conceptual framework that guided the project study was Tinto’s integration model, which provided insight as to why students choose to leave or continue their educational journey. The overarching question that guided the study queried the factors influencing students’ decisions to take online courses at the higher education level. A qualitative case study was used to capture information on 10 students regarding their perceptions of online learning and retention issues within the programs. Interviews were used to collect the data, along with research notes from each 40 minute interview. All information was transcribed and member checked, the data and research notes were uploaded in Nvivo 11. Once analyzed the following themes emerged, personal, academic, and institutional. The results also revealed that student participation and belonging are key indicators of student performance online and seem to be the most significant reason for failure or withdrawal from online courses. To address the reasons, a professional development plan was developed for the local community college to increase student, faculty, and staff awareness, interaction, and to assist in creating a welcoming, learning, and supportive environment. The implications for social change include presenting the professional development to the local community college to increase student retention and success rates for online courses by understanding the student population and their needs to be successful, resulting in an increase for graduation.

Online learning continues to widen in popularity by providing greater access and flexibility in time and location the learning occurs. There is a shift in the profile of a traditional college student. Almost half of the students who are enrolled in online classes are 24 or older and tend to carry increased time constraints due to external factors such as employment and family responsibilities. Student retention remains a concern for institutions. Many students lack the skills necessary to be successful in the online platform. Research reports self-regulation learning skills are essential. Providing reminders for an upcoming assignment may give needed scaffolding. Intervention research is sparse in this domain. This dissertation is written in a three journal article format. Article 1 is a systematic review of the literature focused on the use of auto-reminders or nudges as an intervention in higher education. This review employed systematic criteria to allow rigorous analysis, critique, and synthesis of related literature search. The search strategy focused on auto-reminder interventions in online classes. Keywords were searched in each of the databases (n = 3) ERIC, PsychINFO, and Scopus. Articles (n = 291) were added to Zotero. Three themes emerged. Health (n = 3), procrastination (n = 2), and motivation (n = 4) for a total of 9 articles. Findings reveal that the health field is successful in nudging their patients into better health practices; however, published research in the education field is lacking. Building on findings from Article 1, Article 2 sought to address nudging in the education field. Instructors volunteered to use a nudging app to remind students of upcoming assignments in their courses (n= 158). Enrolled students were invited to download a mobile app. This study attempted to create a profile of students who used the app. Findings reveal that students who used the app were more likely to be Asian and International and had higher scores on college entrance exams. App users had slightly lower prior GPAs, despite having earned significantly more credits in college at the time of the study. Building on Article 2, Article 3 explored the behavioral interaction with app users tapping (n = 443) and not tapping (n = 1102) of push notifications. Findings reveal app users submit more assignments and have higher average assignment grades when they tap the notifications. Assignment weight is generally lower, and there is generally less time between the time the student submitted the assignment and the assignment deadline. When push notifications are not tapped, assignment weight is higher, and there is more time between submission and deadline. More research is needed to determine push notification behavior.

Algorithms that are being used in sensitive contexts such as deciding to give a job offer or giving inmates parole should be accurate as well as being non-discriminatory. The latter is important especially due to emerging concerns about automatic decision making being unfair to individuals belonging to certain groups. The machine learning literature has seen a rapid evolution in research on this topic. In this thesis, we study various problems in sequential decision making motivated by challenges in algorithmic fairness. As part of this thesis, we modify the fundamental framework of prediction with expert advice. We assume a learning agent is making decisions using the advice provided by a set of experts while this set can shrink. In other words, experts can become unavailable due to scenarios such as emerging anti-discriminatory laws prohibiting the learner from using experts detected to be unfair. We provide efficient algorithms for this setup, as well as a detailed analysis of the optimality of them. Later we explore a problem concerned with providing any-time fairness guarantees using the well-known exponential weights algorithm, which leads to an open question about a lower bound on the cumulative loss of exponential weights algorithm. Finally, we introduce a novel fairness notion for supervised learning tasks motivated by the concept of envy-freeness. We show how this notion might bypass certain issues of existing fairness notions such as equalized odds. We provide solutions for a simplified version of this problem and insights to deal with further challenges that arise by adopting this notion. / Graduate

The purpose of this study was to determine if there was a significant relationship between learning styles and student learning outcomes in an online college mathematics course. Specifically, the study was guided by two research questions focused on (a) the extent to which learning styles had a predictive relationship with student achievement in an online college mathematics course and (b) the extent to which various learning styles among mathematics students in online versus face-to-face courses predicted mathematics achievement. The population for this study consisted of the 779 college mathematics and algebra (CMA) students who were enrolled in a private multimedia university located in the southeast. A total of 501 students were enrolled in the online class, i.e., the experimental group, and 278 students enrolled in the face-to-face class comprised the control group. All students completed (a) an initial assessment to control for current mathematics knowledge, (b) the online Grasha-Reichmann Student Learning Styles Scales (GRSLSS) Inventory, and (c) 20 questions selected from the NAEP Question Tool database. Hierarchical linear regressions were used to address both research questions. A series of ANCOVA tests were run to examine the presence of any relationships between a given demographic and course modality when describing differences between student test scores while controlling for prior academic performance. The results indicated that predominant learning style had no apparent influence on mathematics achievement. The results also indicated that predominant learning style had no apparent influence on iv mathematics achievement for online students. When examining demographics alone without respect to modality, there was no significance in course performance between students in various ethnicity, gender, or age groups