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Increasingly researchers are turning to online focus groups as a qualitative research method, yet rigorous methodological studies regarding the quantity, quality and diversity of the data generated relative to traditional in-person focus groups are limited. This study experimentally tests the idea generation capabilities of online text-based focus groups versus traditional in-person focus groups using sustainability in the hospitality industry as the idea generation topic. Participants were purposively sampled from the hospitality program at a large Southeastern university and randomly assigned into one of two treatment groups: online text-based or traditional in-person focus groups. The in-person focus groups resulted in a larger word count, and a higher number of ideas generated, although both in-person and online generated an equivalent number of unique ideas. The online focus group generated a comparable average quality of ideas and number of good ideas. There was a high degree of overlap in themes generated by both groups. The results show that online focus groups are capable of generating a comparable level of idea quantity, quality and diversity relative to in-person focus groups.

The racial academic achievement gap, identified as the underachievement of racially, culturally, ethnically, and linguistically diverse (RCELD) students and documented by research, is visible in all education organizations (Griner & Stewart, 2013; National Center for Education Statistics, 2019; O'Connor, Hill, & Robinson, 2009). Since the United States Supreme Court decision of Brown v. Board of Education of Topeka, Kansas, repudiating the concept of separate but equal, laws concerning the need for equal education access have been enacted and educational policies have been created and implemented, but this achievement gap continues to exist (Williams, 2011). Culturally responsive leadership and culturally relevant pedagogy are research-based theories and practices that work towards meeting the needs of the growingly diverse population (Gay, 2018). A mixed method design utilized the explanatory sequential approach to research what culturally responsive beliefs, espoused practices, and supports elementary public-school principals convey in high performing urban schools. The design included the use of surveys and interviews to collect anonymous data from principals on their experiences in these roles and the influences they convey at their urban elementary school to narrow the racial academic achievement gap. Survey data collected with the use of Qualtrics Survey Software and interview data collected through individual interviews were conducted. Audio recordings of the interviews were transcribed and reviewed for themes. Creswell's six steps of data analysis and interpretation were utilized to analyze and interpret the data collected. Multiple reliability and validity measure occurred in this study. The results are compiled for future implications and recommendations are made.

This dissertation used classroom observations, movement mapping, instructor interviews, and student focus groups to examine the ways in which both instructors and students navigated the classroom spaces they were assigned in upper-level, discipline-specific courses. By focusing on three diverse disciplines (writing and rhetoric, education, and chemistry), this dissertation makes arguments about how the design of classroom spaces (as well as the tools that are housed therein) support, facilitate, and detract from a student's ability to develop a disciplinary identity, which is defined here as the social and linguistic construction of a practitioner of a discipline that is shaped by the language, positions, and peer acknowledgement negotiated by that discipline. Moreover, this dissertation also makes arguments about how tools that are common across many disciplines (desktops, chairs, etc.) support or detract from student engagement. Ultimately, this dissertation argues that teachers across disciplines can be mindful of the spaces they are assigned (even if those spaces were perhaps not designed with disciplinary goals in mind) in an effort to help students begin to think of those spaces as extensions of their discipline so they can better imagine themselves as future professionals in those spaces.

A mixed method, exploratory, sequential research design was conducted to investigate the presence of latent bias in early childhood STEM literature content, applying a non-biased, sociocultural, STEM identity, theoretical framework. A survey of children's perceptions of gender and a content analysis found unintentional bias. Exploratory findings confirmed 102 children were gendering images. An examination of the relationship between the participants' gender and how the participant gendered AND preferred the images indicated differences existed between boys and girls. Children preferred images perceived as matching their own, with statistical significance. Girls were found to prefer images less than boys AND they were more likely to gender the images. Children were more likely to give gender to the 50 images considered in the study, than to non-gender them. The gendering and preference was found to be statistically significantly higher for anthropomorphic and personified inanimate images. Additionally, a content analysis of eight award winning and popular selling STEM children's books were conducted and were found to contain biased narratives and image content. A content analysis found significant differences relating to the frequency of character representation in the eight books. Analysis indicated a higher lexical representation of females to males, and image representation was more male than female. Further analysis of additional books and images is warranted from the findings of this exploratory study.

Recent literature suggested that while the discussion of presidential selection, evaluation, and compensation was common to both private and public institutions, special attention was paid to public university presidents. They and their presidencies were subject to intense public debate and scrutiny. Florida's public university presidents have contended with the same issues as their counterparts in other states. However, the 2001 changes in the state's higher education governance created distinct challenges and opportunities for the 11 presidents in the Florida State University System. The purpose of this study was to analyze the trends in the selection, evaluation, and compensation of the 11 university presidents in the Florida State University System (SUS) from 1996-2006, the period five years before and five years after the changes in governance. Interviews with university presidents, members of boards of trustees, and members of the Florida Board of Governors, members of the Florida Legislature, and salary histories from seven of the 11 Florida institutions were used to analyze the trends in light of the shift in perceptions of the presidents' roles and the changes in higher education governance. Since 2001, and the establishment of boards of trustees and by Florida statute, presidents were seen as the chief executive officer of their institutions, a change from an academic to a business model. Trustees, who primarily came from a business background, viewed them as CEOs and chose to compensate presidents at a higher level than they had previously been paid. The Board of Governors, a majority of whose members also had corporate backgrounds, implied the need for a CEO-type leadership style and more corporate-style accountability. In 2003, the Florida Legislature responded to the salary surge at the chief executive level and placed a $225,000 salary cap from appropriated funds on the university presidents' salaries. The legislation did not place any restrictions on university foundations or other sources for supplementing the compensation package.

This study examines the current state of computer-based instructional systems design (ISD) tools and outlines its implications for the future. The study utilizes the grounded theory methodology to capture and document modern instructional designers' perspectives regarding the current state of ISD tools, the issues associated with them, and their interrelationships. The study also presents a framework for classifying modern ISD tools and a conceptual prototype of a designer-oriented system of computer-based ISD tools.

The pursuit of this ethnographic study was inspired by my lived experiences as an urban school teacher for 18 years, as well as, the experiences of a group of other urban teachers. The study explored the following question: Does knowledge and practice of Ubuntu pedagogy help to improve teachers' cultural competencies in an urban school? The research documents how knowledge and practice of the three pillars of Ubuntu pedagogy help to transform the perspective of urban teachers. The three pillars are (1) Humanism and Ubuntu Competency, (2) Collaboration and Partnership, and (3) Relationship and Learning Community. Data were collected using multiple techniques, which included semi-structured interviews, book study, reflective digital journal notes, observations and a focus group. Seven participants, who were interviewed, were selected using convenience sampling (Creswell, 2013). Transformative learning and Ubuntu pedagogy are constructs in the conceptual framework that guided the process of the research design. For the data analysis procedures, the description of the interpretation of the cultural-sharing group provided more insights about teachers' experiences in an urban school. Recommendations were made based on the data collected, which provided evidence of how the knowledge and practice of Ubuntu pedagogy helped to improve teachers' cultural competencies. The teachers' focus group, book study reflections and classroom observations revealed that all the teachers experienced levels of a disorienting dilemma, a shift in frame of reference that was more inclusive and self-reflective.

Studies have indicated that intergenerational relationships can assist children to learn more efficiently by providing support. As new forms of media have emerged and become pervasive in our society, it is important to understand how children use them to learn. Just as television coviewing has been observed by past researchers to aid youths to learn with parents and grandparents, three-dimensional virtual learning environments (VLE) are being investigated for their potential. This study seeks to examine the potential learning impact on children, ages 8 to 13, encountering a three-dimensional virtual learning environment with their grandparents. The primary research question this study examines is whether children exploring a 3D VLE with a grandparent learn the information being conveyed within the environment more effectively. A second aspect of the study considered if the grandparent-child pair would spend a greater amount of time in the virtual environment compared to a child exploring alone. Additionally, this research seeks to determine if there are other benefits a child could gain while interacting with a grandparent while using a VLE. This study used ChronoLeap: The Great World's Fair Adventure, an educational VLE developed at the University of Central Florida under a National Science Foundation Informal Science Education grant. ChronoLeap permits children to explore a virtual representation of the 1964-65 New York World's Fair where they can discover the roots of current technology in their 1960s form and its evolution to the present. This environment affords a child a unique opportunity to encounter a virtual recreation of an era in which their grandparents would have firsthand memories potentially eliciting the grandparent's personal reflections.

High-dimensional data has a wide range of applications in research, such as education, health, social media, and many other research fields. However, the high dimensionality of data can raise many problems for data analyses. This study focuses on commonly used techniques of dimensionality reduction for machine learning models, which play an essential and inevitable role in data prepossessing and statistical analysis. The main issues of high-dimensional data for machine learning tasks include the accuracy of data classification and visualization in machine learning models. Therefore, in this study, machine learning algorithms are used to predict and classify datasets to evaluate the accuracy, precision, recall, and F1 score of results, which are evaluated and compared by mean, variance, confidence intervals, and coverage. This study focuses on data mining issues, comparing and discussing different dimensionality reduction techniques with different dataset features. Eight dimensionality reduction techniques (Principal Component Analysis, Kernel Principal Component Analysis, Singular Value Decomposition, Non-negative matrix factorization, Independent Component Analysis, Multidimensional Scaling, Isomap, and Auto-encoder) are compared and evaluated on simulated datasets. Specifically, this study evaluates and compares the performances of the commonly used dimensionality reduction techniques by exploring the issues about features and characteristics of different techniques through Monte Carlo simulation studies with four machine learning classification models: logistic regression, linear support vector machine, nonlinear support vector machine, and k-nearest neighbors. The results of this study indicated that the DRTs decreased the accuracy, precision, recall, and F1 scores compared with results without DRTs. And overall, MDS performed dramatically better than other DRTs. SVD, PCA, and ICA had similar results because they are all linear DRTs. Although it is also a linear DRT, NMF performed as poorly as KPCA, which is a nonlinear DRT. The other two nonlinear DRTs, Isomap and Autoencoder, had the worst performance in this study. The results provided recommendations for empirical researchers using machine learning models with high dimensional data under specific conditions.