This study aimed to explore the effectiveness of graduation coach services in reducing student risk factors for dropping out of high school and increasing student academic performance, a strong correlate of student persistence to high school graduation (Battin-Pearson et al., 2000). The study employed a quasiexperimental nonequivalent control group design utilizing student risk ratio and individualized Georgia High School Graduation Test (GHSGT) scores in English/language arts and mathematics as measures to compare students who received the services of a graduation coach to those who did not. The sample for this study included 39,326 Georgia students continuously enrolled in the 11th grade during the 2008 – 2009 school year and characterized as at risk for high school noncompletion by virtue of possessing a student risk ratio greater than zero. Of these students, 9,076 (23.08%) were selected as caseload students to receive the intervention and support services of a graduation coach (GaDOE, 2009c). To assess the differential effects of graduation coach services on student risk ratio across school improvement regions, gender, and ethnicity, the researcher conducted a series of general linear model (GLM) multivariate repeated measures analyses. Risk ratios for students served by a graduation coach were found to be significantly lower in May 2009 than in August 2008. Differences in student risk ratios existed regionally across the state regardless of graduation coach caseload status. While analyses related to the differential effects of graduation coach service provision revealed no significant difference in the student risk ratio metric according to gender, they did reflect a significant difference in the student risk ratio metric according to graduation coach caseload status and ethnicity. Regression analyses determined that student risk ratio may account for 12.5 percent of the variance in student GHSGT mathematics scores and 9.6 percent of the variance in student GHSGT English/language arts scores for first-time 11th graders. Adding student caseload status into the equation increases the variance accounted for to 12.9 percent in mathematics and 10.4 percent in English/language arts.

Most quantitative research is conducted by randomly selecting members of a population on which to conduct a study. When statistics are run on a sample, and not the entire population of interest, they are subject to a certain amount of error. Many factors can impact the amount of error, or bias, in statistical estimates. One important factor is sample size; larger samples are more likely to minimize bias than smaller samples. Therefore, determining the necessary sample size to obtain accurate statistical estimates is a critical component of designing a quantitative study. Much research has been conducted on the impact of sample size on simple statistical techniques such as group mean comparisons and ordinary least squares regression. Less sample size research, however, has been conducted on complex techniques such as hierarchical linear modeling (HLM). HLM, also known as multilevel modeling, is used to explain and predict an outcome based on knowledge of other variables in nested populations. Ordinal logistic HLM (OLHLM) is used when the outcome variable has three or more ordered categories. While there is a growing body of research on sample size for two-level HLM utilizing a continuous outcome, there is no existing research exploring sample size for OLHLM. The purpose of this study was to determine the impact of sample size on statistical estimates for ordinal logistic hierarchical linear modeling. A Monte Carlo simulation study was used to investigate this research query. Four variables were manipulated: level-one sample size, level-two sample size, sample outcome category allocation, and predictor-criterion correlation. Statistical estimates explored include bias in level-one and level-two parameters, power, and prediction accuracy. Results indicate that, in general, holding other conditions constant, bias decreases as level-one sample size increases. However, bias increases or remains unchanged as level-two sample size increases, holding other conditions constant. Power to detect the independent variable coefficients increased as both level-one and level-two sample size increased, holding other conditions constant. Overall, prediction accuracy is extremely poor. The overall prediction accuracy rate across conditions was 47.7%, with little variance across conditions. Furthermore, there is a strong tendency to over-predict the middle outcome category.

While use of hierarchical linear modeling (HLM) to predict an outcome is reasonable and desirable, employing the model for prediction without first establishing the model’s predictive validity is ill-advised. Estimating the predictive validity of a regression model by cross-validation has been thoroughly researched, but there is a dearth of research investigating the cross-validation of hierarchical linear models. One of the major obstacles in cross-validating HLM is the lack of a measure of explained variance similar to the squared multiple correlation coefficient in regression analysis. The purpose of this Monte Carlo simulation study is to explore the impact of sample size, centering, and predictor-criterion correlation magnitudes on potential cross-validation measurements for hierarchical linear modeling. This study considered the impact of 64 simulated conditions across three explained variance approaches: Raudenbush and Bryk’s (2002) proportional reduction in error variance, Snijders and Bosker’s (1994) modeled variance, and a measure of explained variance proposed by Gagné and Furlow (2009). For each of the explained variance approaches, a cross-validation measurement, shrinkage, was obtained. The results indicate that sample size, predictor-criterion correlations, and centering impact the cross-validation measurement. The degree and direction of the impact differs with the explained variance approach employed. Under some explained variance approaches, shrinkage decreased with larger level-2 sample sizes and increased in others. Likewise, in comparing group- and grand-mean centering, with some approaches grand-mean centering resulted in higher shrinkage estimates but smaller estimates in others. Larger total sample sizes yielded smaller shrinkage estimates, as did the predictor-criterion correlation combination in which the group-level predictor had a stronger correlation. The approaches to explained variance differed substantially in their usability for cross-validation. The Snijders and Bosker approach provided relatively large shrinkage estimates, and, depending on the predictor-criterion correlation, shrinkage under both Raudenbush and Bryk approaches could be sizable to the degree that the estimate begins to lack meaning. Researchers seeking to cross-validate HLM need to be mindful of the interplay between the explained variance approach employed and the impact of sample size, centering, and predictor-criterion correlations on shrinkage estimates when making research design decisions.

Standardized testing has been part of the American educational system for decades. Controversy from the beginning has plagued standardized testing, is plaguing testing today, and will continue to be controversial. Given the current federal educational policies supporting increased standardized testing, psychometricians, educators and policy makers must seek ways to ensure that tests are not biased towards one group over another. In measurement theory, if a test item behaves differently for two different groups of examinees, this test item is considered a differential functioning test item (DIF). Differential item functioning, often conceptualized in the context of item response theory (IRT) is a term used to describe test items that may favor one group over another after matched on ability. It is important to determine whether an item is functioning significantly different for one group over another regardless as to why. Hypothesis testing is used to determine statistical significant DIF items; an effect size measure quantifies a statistical significant difference. This study investigated the addition of reporting an effect size measure for differential item functioning of items and tests’ (DFIT) noncompensatory differential item functioning (NCDIF), and reporting empirically observed power. The Mantel-Haenszel (MH) parameter served as the benchmark for developing NCDIF’s effect size measure, for reporting moderate and large differential item functioning in test items. In addition, by modifying NCDIF’s unique method for determining statistical significance, NCDIF will be the first DIF statistic of test items where in addition to reporting an effect size measure, empirical power can also be reported. Furthermore, this study added substantially to the body of literature on effect size by also investigating the behavior of two other DIF measures, Simultaneous Item Bias Test (SIBTEST) and area measure. Finally, this study makes a significant contribution to the body of literature by verifying in a large-scale simulation study, the accuracy of software developed by Roussos, Schnipke, and Pashley (1999) to calculate the true MH parameter. The accuracy of this software had not been previously verified.

During a time when most institutions of higher education are in search of underrepresented student participation, Georgia State University (GSU), a majority White institution, has observed a lack of involvement of White students in co-curricular activities. The purpose of the research study was to critically examine White students’ (dis) engagement in traditional student organizations at this university that has a significant student of color population. I used case study methodology that allowed for a breadth of conceptual frameworks and research options. The methods of collecting data included interviews (formal, informal, and oral history) of current and former students, as well as campus administrators. In addition, the use of archived texts and photographs, yearbooks, organization rosters, and university enrollment statistics allowed for crystallization of data, layered interpretations, and document analyses. I used the data sources to interpret GSU White students’ perceptions of campus climate, racial interactions, leadership among students of color, and racial identity that influence their (dis) engagement in traditional student organizations and campus life. In exploring the “rhetoric of diversity,” I argue that the experiences and attitudes of White students can inform the policy debate on institutional mission and offerings.

Arts education must continually provide justification for its inclusion in the K-12 curriculum. This dissertation utilizes philosophical and conceptual analysis to probe the tensions, ironies, and contradictions that permeate the arts education advocacy discourse. Using evidence from advocacy materials published online, scholarly critiques of themes in the advocacy discourse, and research reports describing school-based arts programs, I construct an argument that posits generative consequences for student learning when arts-centered inquiry is reimagined as pragmatic instrumentalism. Such a reimagining of arts-centered inquiry seeks to draw a distinction between utilitarian justifications for the arts and instrumental benefits the arts provide individual students in mediating complex and connected learning. In reclaiming the term “instrumental” for arts-centered inquiry, I offer a way to restore the notion of generativity to arts learning and a means to promote greater understanding among practitioners, researchers, policymakers, and advocates.

There has been an increasing number of students with learning disabilities attending colleges and universities over the past two decades. As a result of federal legislation, institutions of higher education are required through an office of student support services to provide accommodations and modifications for students with disabilities in order to receive federal monies. This semi-structured interview-based qualitative study seeks to understand how four higher education students with disabilities make the choice to “come out” as possessing a learning disability in order to seek academic assistance from the office of student support services. The foundation for this inquiry emerges out of the differences between the medical and social models of disabilities. The framework for the medical model places the individual with a disability as needing to be cured in order to have a normal life, while the social model of disabilities focuses on how society is constructed around able-bodied individuals without substantive consideration for individual differences – specifically disabilities. The data collected were analyzed using a cross-interview analysis of participants’ responses to interview questions. Because little research has been conducted in this content area, the research focused on themes relating to the stigma of disability labels, the choice to come out as possessing a disability, the role of the academic resource center to obtain accommodations and modifications, and the meaning of success for higher education students with disabilities. The stigma associated with possessing a disability while attending an institution of higher education can place additional anxiety on individuals who decide to come out as possessing a disability. The significance of this research to the fields of higher education and disability studies is to gain a better understanding of how the stigma that is associated with students with disabilities affects the manner in which they choose to access student support services and identify themselves as possessing a learning disability. By making the choice to be identified as possessing a disability, students can access academic accommodations and modifications to support academic success, yet the same choice has the potential to have a negative social consequence of being socially labeled as an othered individual. The outcomes for this research study can inform policies and practices relating to the self-identification that students with disabilities must adhere to in order to obtain accommodations and modifications.

African descent students often are subjected to pedagogical practices and curricula that do not validate their home cultures or their individual and collective histories. In response to this problem, many teachers implement culturally relevant pedagogy (CRP) and curricula to address the needs of this population. Focusing on two African descent teachers in an African-centered school, the purpose of this qualitative African-centered inquiry was to 1) examine how the ancient Kemetic philosophy, Ma’at, manifests in their epistemologies, worldviews, and pedagogical practices, 2) explore how their epistemologies and worldviews inform their pedagogical practices, and 3) understand how their life experiences shaped their epistemologies and worldviews. A holistic theoretical framework comprised of Afrocentric and womanist theories and a CRP theoretical approach informed the “retooled” life history methodology employed in this study. The culturally sensitive data collection methods included dialogue, storytelling, participatory witnessing, and Afrocentric group conversation. Thematic and dialogic/performance narrative analysis techniques were used to analyze the data. The significance of this study is fourfold. First, this study adds to the paucity of existing literature on exemplary African descent teachers by bringing to the fore how the epistemologies and worldviews of teachers shape their pedagogical practices in an African-centered school. Second, this study explored the intended liberatory effects of African descent teachers’ implementation of CRP for themselves and for their students, ultimately affecting how both position themselves in the broader society. Third, use of the cardinal virtues of Ma’at (truth, justice, righteousness, order, harmony, balance, and reciprocity) as the philosophical foundation for this study presents an ontological alternative to privileging western philosophical frameworks typically used in educational research. Finally, as the ancient Kemetic philosophy employed in this study and as this study’s philosophical foundation, Ma'at specifically encourages policy makers, researchers, and practitioners to reexamine their notions of contemporary education in terms of its purpose, methods, and conceptions of the whole child. The findings illuminate ways that Ma’at undergirds the participants’ epistemologies, worldviews, and culturally relevant pedagogical practices enabling them to facilitate critical thinking, critical consciousness, and identity development with their students.

ABSTRACT ROBUSTNESS OF TWO FORMULAS TO CORRECT PEARSON CORRELATION FOR RESTRICTION OF RANGE by Dung Minh Tran Many research studies involving Pearson correlations are conducted in settings where one of the two variables has a restricted range in the sample. For example, this situation occurs when tests are used for selecting candidates for employment or university admission. Often after selection, there is interest in correlating the selection variable, which has a restricted range, to a criterion variable. The focus of this research was to compare Alexander, Alliger, and Hanges’s (1984) formula to Thorndike’s (1947) formula and population values using Monte Carlo simulation when the assumption of normal distribution is violated in a particular way. In both Thorndike’s and Alexander et al.’s correction formulas, values for the variances in the restricted and the unrestricted situations are required. For both formulas, the variance in restricted situations was a sample estimate. In the Monte Carlo simulation, the difference between the two approaches was that in Thorndike’s formula, the variance in the unrestricted situation was the population variance from the exogenous variable, whereas in Alexander et al.’s approach, the population variance was estimated based on the sample variance in the restricted situation. In the simulation, robustness situations were created from non-normal distributions for predicted group membership in a classification problem. As expected, Thorndike’s corrected correlation values were more accurate than Alexander et al.’s corrected correlation values, and Thorndike’s formula had a smaller standard error of estimates. Absolute values of the mean differences between the estimated and population correlations for Alexander et al.’s approach compared to Thorndike’s approach in robustness situations ranged from 1.37 to 2.15 larger. Nevertheless, Alexander et al.’s approach, which is based only on estimated variances, appears to be a worthwhile correction in most of the simulated situations with a few notable exceptions for non-normal distributions.

Contemporary federal education policy discourse from A Nation at Risk to the Race to the Top program has promoted and extended neoliberal discourse from the national level to the level of the school and its personnel. This study highlights the persistence of neoliberal discourse within federal education policy and the consequences this persistence holds for critiques of current policies and practices. Analyzing reports published by the United States Department of Education and contemporary United States education policy starting from A Nation at Risk, moving through America 2000, Goals 2000, and No Child Left Behind, and ending with the Race to the Top program, I use rhetorical tropes to provide a method of analysis for education policy. Due to the novelty of this project for the field of education policy studies, I bring in concepts from rhetorical studies and discourse analysis to produce an interdisciplinary approach to policy analysis that fills a particular gap in existing analyses. At present, there exists no framework within the traditional analyses of education policy that offers a theoretical account of how a discourse maintains and propagates itself through policy. This dissertation offers a new method of policy analysis that examines how a discourse stabilizes and perpetuates itself through education policy. Specifically, an analysis of these policies and reports demonstrates how neoliberal discourse uses the tropes of metaphor, where two objects are identified with one another, and synecdoche, where the part is made to represent the whole and vice-versa, to ground and naturalize its growing presence in education policy and practice. Through the tropological analysis of the above cited texts, the co-operation of metaphor and synecdoche, what I term “organic identification,” accounts for the persistence of neoliberal discourse through its identification and integration with federal education policy discourse specifically through the constitution of places, e.g., the nation and the school. The conclusion suggests the critical potential for considering the role of tropes in the discursive constitution of place by mapping the persistence of a discourse and providing a critical distance from which contradictions and alternative trajectories can be forwarded.