The papers in this portfolio are part of the author's efforts to 'make things better' in education, and are the products of over a decade's thinking and research. While most of the papers are written from within the context of the state school system in NSW, their messages apply equally well to school systems elsewhere. The papers reflect an eclectic mix of research perspectives and methodological paradigms. It is suggested that student learning outcomes may be improved if schools specify goals and objectives, make the necessary resources available and establish accountability mechanisms for monitoring and measuring performance. The analysis and synthesis generates critical knowledge, that is, knowledge which is explanatory and interpretive. The desire to assist schools to achieve a position where they are able to (firstly) assemble their own data systems, and secondly to conduct their own analysis of this data and report this to the school community has been the common theme underpinning all the professional work of the author. The works evolved in this portfolio document an evolving process, and one which is far from concluded. There is much further work that could be done. An analysis of the macro and micro-politics of school improvement processes, for example, would be a useful contribution to the literature. For the present purposes, there is a practical need to limit the scope and number of the works presented. The works included all address, in some way, the common theme of improving school and systemic effectiveness through better information management. Hopefully, they have made some small contribution to better understanding the phenomenon, and will in turn positively impact on the performance of schools and school systems / Doctor of Education

Thesis (Ph. D.)--Ohio State University, 2003. / Title from first page of PDF file. Document formatted into pages; contains xii, 107 p.; also includes graphics (some col.). Includes abstract and vita. Advisor: Douglas B. Downey, Dept. of Chemistry. Includes bibliographical references (p. 92-98).

Thesis (MSocSc (ApplSocRes))--University of South Australia

Thesis (Ph.D.)--University of Delaware, 2006. / Principal faculty advisor: James Raths, School of Education. Includes bibliographical references.

Thesis (Ed.D.) -- Central Connecticut State University, 2009. / Thesis advisor: Karen Beyard. "... in partial fulfillment of the requirements for the degree of Doctor of Education." Includes bibliographical references (leaves 201-210). Also available via the World Wide Web.

Thesis (Ed. D.)--University of North Texas, May, 2008. / Title from title page display. Includes bibliographical references.

Thesis (Ph. D.)--Illinois State University, 2005. / Title from title page screen, viewed September 26, 2006. Dissertation Committee: Patricia H. Klass (chair), Paul Baker, Glenn Schlichting, Meredith Peterson. Includes bibliographical references (leaves 99-104) and abstract. Also available in print.

In this thesis a prediction model using graduation rate as the performance indicator is obtained for community colleges for three cohort years, 2003, 2004, and 2005 in the states of California, Florida, and Michigan. Multiple Regression analysis, using an aggregate of seven predictor variables, was employed in determining this prediction model. From this prediction model, a predicted graduation rate was obtained for each of the 142 institutions in this study. Using this predicted graduation rate, an Institutional Performance Ratio (IPR), was then calculated for each institution, by dividing the actual graduation rate for each institution by its predicted graduation rate. These IPR values were then used to classify the performance of each institution as meeting expectation, exceeding expectation or falling below expectation. Inter institutional comparisons were also made using these IPR values. / by Susan Moosai. / Thesis (Ph.D.)--Florida Atlantic University, 2010. / Includes bibliography.

The problem was to determine how comparable is comparable improvement for campuses in Texas. An alternative strategy for determining comparable improvement was developed using 2000 comparable improvement data provided by the Texas Education Agency for 2,403 elementary campuses. Comparable improvement is a measure that shows how student performance has changed from one year to the next and then compares that growth to 40 schools that are demographically most similar to the target school. Instead of using the most dominant characteristic as in the current process, the percent of students in poverty was the initial sorting characteristic. The impact of sorting by poverty was reviewed in four areas: 1.) the impact on quartile placement, 2.) the TLI average growth for the comparison group, 3.) the award eligibility, and 4.) the changes in comparison group composition. No practical significant difference was found for research questions 1 and 3, however, a practical significant difference was found in group average TLI growth for math and in the comparison group composition. Overall, the alternative process had the greatest impact on campuses with 40-80% poverty. Three possible factors may have influenced the results. First, the middle poverty campuses had the most change in comparison group as found in question 4. Second, the interaction between the middle poverty campuses and the alternative process could have been fueled by the removal of the 1,295 campuses with poverty as the dominant characteristic in current system. Third, the high correlation between poverty and ethnicity may have limited any impact of the alternative process.

Esta pesquisa toma como objeto de estudo o desempenho escolar nos anos iniciais da Rede Municipal de Ensino de São Paulo. Com base em indicadores educacionais disponibilizados pelo Instituto Nacional de Pesquisas Educacionais Anísio Teixeira (INEP), reunimos uma ampla gama de informações sobre as 549 escolas municipais de São Paulo. Como revelaram inúmeras pesquisas, nacionais e internacionais, o desempenho escolar apresenta uma forte associação com o nível socioeconômico das famílias. Sem negligenciar esta dimensão do desempenho escolar, a hipótese trabalhada nesta pesquisa dizia respeito ao peso de outros fatores, descritos na literatura como efeito-escola e efeito-professor. Na primeira etapa do trabalho, procedemos à coleta das estatísticas e examinamos a distribuição dos novos indicadores educacionais (INEP, 2014) na Rede Municipal de Ensino de São Paulo. Em seguida, recorremos a uma Análise de Componentes Principais (ACP), visando produzir uma representação, à uma só vez, multidimensional e sintética do conjunto das escolas municipais de São Paulo. Como esperado, os resultados evidenciaram, no primeiro eixo, uma correlação entre desempenho escolar e nível socioeconômico das famílias. A segunda componente principal expressa uma correlação que traz à tona a importância dos novos indicadores educacionais para a compreensão dos resultados escolares. As demais componentes principais revelam a contribuição de fatores propriamente escolares para a explicação do êxito escolar / This research takes as its object of study school performance in the early years of the Municipal Education Network of São Paulo. Based on educational indicators provided by the National Institute of Education Research Anísio Teixeira (INEP), we gathered a wide range of information about 549 municipal schools from São Paulo. As evidenced by numerous, national and international researches, school performance has a strong association with the socioeconomic level of families. Without neglecting this dimension of school performance, the hypothesis worked on in this research related to the weight from other factors, described in the literature as \"school-effect\" and \"teacher-effect\". In the first step of the research, we proceeded to collect statistics and examined the distribution of the new educational indicators (INEP, 2014) on the Municipal Education Network of São Paulo. Then, we referred to a Principal Components Analysis (PCA), aiming to produce a multidimensional and synthetic representation from all municipal schools in São Paulo. As expected, the results showed, on the first axis, a correlation between school performance and socioeconomic level from families. The second major component expresses a correlation that brings to light the importance of the new educational indicators for the school outcomes understanding. The other main components reveal the contribution of school-based factors for the school success explanation