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The study applies modified quadriform analytics (MQA) across three school years (2008–2010), comparing fiscal resources with mandated academic test outcomes while accounting for uncontrollable sociodemographic factors. It reviews historical and theoretical debates, details Australian and New South Wales funding contexts and prior efficiency research, and presents unit-of-analysis results by school and by region, concluding with implications and recommendations for future policy and research.",{"@graph":14,"@context":72},[15,34,55],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & 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problem does the research address about measuring educational productivity in public schools?","Question",{"text":62,"@type":63},"It addresses limited knowledge about public schools’ educational productivity when examined outside market-based cost-minimization frameworks, motivating an alternative efficiency measurement approach.","Answer",{"name":65,"@type":60,"acceptedAnswer":66},"How does the study measure educational productivity and efficiency?",{"text":67,"@type":63},"It uses modified quadriform analytics (MQA) to assess educational productivity by comparing fiscal resources with mandated academic test scores while incorporating sociodemographic factors beyond a school’s control.",{"name":69,"@type":60,"acceptedAnswer":70},"What theoretical perspective is used to challenge traditional cost-minimizing assumptions?",{"text":71,"@type":63},"The study draws on collective choice theory, which argues public schools do not necessarily behave like private cost-minimizing agencies due to 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Quadriform Analytics  \nR. Anthony Rolle  \nR. Anthony Rolle is Professor and Chair, Department of Educational Leadership and Policy Studies, at the University of Houston. He is Vice President of the National Educational Finance Academy and a Distinguished Research Fellow atthe Shanghai Academy of Education Sciences. His current professional interests are organizational productivity and public finance equity.  \nIntroduction  \nLittle is known about the educational productivity of public schooling organizations when examined outside of market-based, cost-minimization frameworks (Hickrod et al. 1990; Anderson 1996; Rolle 2003, 2004a, b; Houck, Rolle, and He 2010). Consequently, the purpose of this research was to extend the literature that supports the appropriateness of measuring levels of the economic efficiency of public schools via an alternative approach, utilizing modified quadriform analytics (MQA) to assess the educational productivity of New South Wales public elementary and secondary schools in Australia over three school years, 2008-2010.1 To that end, this study identified and compared the economic efficiency of New South Wales schools in terms of level of fiscal resources and national, mandated academic test scores while taking into account sociodemographic factors over which a school has no control.  \nIn the following sections, this article: (1) presents historical background and alternative perspectives on educational productivity and its measurement; (2) describes the history of primary and secondary school funding in Australia and New South Wales; (3) reviews recent efficiency research on Australian schools; (4) explicates MQA, research methods, and data sources; and (5) presents analytical results. Analytical results include those for New South Wales schools using the school as the unit of analysis followed by a comparison of New South Wales schools by region. The concluding section summarizes findings and discusses implications of the study for educational efficiency theory, research, and policy within the Australian context, and makes recommendations for future research.  \nHistorical Background on Educational Productivity and Its Measurement  \nDebate surrounding educational efficiency has endured more than half a century after the release of Coleman et al.'s 1966 research in Equality of Educational Opportunity which challenged conventional wisdom that factors, like  \nEducational Considerations 7  \nlevel of educational expenditure, had an effect on student achievement. In sharp contrast, Coons, Clune, and Sugarman (1970, 30) dissented, stating:  \nWhatever it is that money may be thought to contribute to the education of children, that commodity is something highly prized by those who enjoy the greatest measure of it. If money is inadequate to improve education, the residents of poor districts should at least have an equal opportunity to be disappointed by its failure (1970, 30).  \nSubsequently, a large cadre of researchers turned to the use of an economic model and multivariate analytic approach referred to as \"production function\" to determine what, if any, statistically significant relationship existed between educational inputs, such as, but not limited to, expenditures, and academic outcomes (See, for example, Hanushek 1986; Murphy and Hallinger 1986; Odden 1986; Rossmiller 1987; Murnane 1991; Hedges, Laine, and Greenwald 1994; Laine, Greenwald, and Hedges 1996).  \nThe net result of decades of production function research, as well as more recent studies using difference-in-difference, discontinuity, and value-added regression methodologies (Jacob and Lefgran 2004; Donald and Lang 2007; Rothstein 2009; Ou 2010; Corcoran and Goldhaber 2013; Goldhaber, Cowan, and Walch 2013), is inconclusive, giving rise to the need to consider alternative economic theories and methodologies, such as those embodied","cbCainFxbxZ8bZaB","https://ap.wps.com/l/cbCainFxbxZ8bZaB","pdf",357034,18,"English","# Introduction\n## Historical Background on Educational Productivity and Its Measurement\n## Theoretical Framework and Motivation\n## Modified Quadriform Analytics, Methods, and Data Sources\n## Analytical Results and Regional Comparisons\n## Conclusions, Implications, and Future Research","[{\"question\":\"What problem does the research address about measuring educational productivity in public schools?\",\"answer\":\"It addresses limited knowledge about public schools’ educational productivity when examined outside market-based cost-minimization frameworks, motivating an alternative efficiency measurement approach.\"},{\"question\":\"How does the study measure educational productivity and efficiency?\",\"answer\":\"It uses modified quadriform analytics (MQA) to assess educational productivity by comparing fiscal resources with mandated academic test scores while incorporating sociodemographic factors beyond a school’s control.\"},{\"question\":\"What theoretical perspective is used to challenge traditional cost-minimizing assumptions?\",\"answer\":\"The study draws on collective choice theory, which argues public schools do not necessarily behave like private cost-minimizing agencies due to lack of property rights and profit motives, and because funding can be independent of “consumer satisfaction.”\"}]","Reconceptualizing Educational Productivity for New South Wales Public Schools - An Empirical Application of Modified Quadriform Analytics | PDF",1792093437,45]