Statistical models attempt to describe and quantify relationships between variables. In the models presented in this chapter, there is a response variable (sometimes called dependent variable) and at least one predictor variable (sometimes called independent or explanatory variable). When investigating a possible cause-and-effect type of relationship, the response variable is the putative effect and the predictors are the hypothesized causes. Typically, there is a main predictor variable of interest; other predictors in the model are called covariates. Unknown covariates or other independent variables not controlled in an experiment or analysis can affect the dependent or outcome variable and mislead the conclusions made from the inquiry (Bock, Velleman, & De Veaux, 2009). A p value (p) measures the statistical significance of the observed relationship; given the model, p is the probability that a relationship is seen by mere chance. The smaller the p value, the more confident we can be that the pattern seen in the data 2 is not random. In the type of models examined here, the R measures the prop- tion of the variation in the response variable that is explained by the predictors 2 specified in the model; if R is close to 1, then almost all the variation in the response variable has been explained. This measure is also known as the multiple correlation coefficient. Statistical studies can be grouped into two types: experimental and observational.

Most developed nations measure the performance of teachers in audit evaluations of school productivity. Accountability metrics such as "teacher effectiveness" and "teacher quality" dominate evaluations of student outcomes and shape education policy. The Metrics of Teacher Effectiveness and Teacher Quality Research explores how these metrics distort analyses of student achievement, sideline broader contextual and systemic influences on learning, reinforce input-output analysis of schooling, and skew the educational debate. Focusing on recent phases of school education policy reform, this book utilizes qualitative data from classroom teacher participants to examine how and why issues of teacher effectiveness and teacher quality figure so prominently in policy reform and why pressing matters of social class, school funding, and broader contextual influences are downplayed. The authors use this information to suggest how teachers can develop their role as pedagogic experts in a highly scrutinized environment. This book will be of great interest to education academics and postgraduate students specializing in teacher performance, accountability and governance.

This book focuses on the question of how to understand quality use of research evidence in education, or what it means to use research evidence well. Internationally there are widespread efforts to increase the use of research evidence within educational policy and practice. Such efforts raise important questions about how we understand not just the quality of evidence, but also the quality of its use. To date, there has been wide-ranging debate about the former, but very little dialogue about the latter. Based on a five-year study with schools and school systems in Australia, this book sheds new light on: why clarity about quality of use is critical to educational improvement; how quality use of research evidence can be framed in education; what using research well involves and looks like in practice; what quality research use means for individuals, organisations and systems; and what aspects of using research well still need to be better understood. This book will be an invaluable resource for professionals within and beyond education who want to better understand what using research evidence well means and involves and how it can be supported.

First published in 1988. Routledge is an imprint of Taylor & Francis, an informa company.

This book addresses a wide range of topics, from the principles of evidence-based practice to the process and dissemination of research to unique considerations such as clinical trials, patenting, and health services research. The case for evidence-based practice and a collaborative research culture is made first, followed by a series of chapters walking the reader through the research process by way of the scientific method. One of the more unique aspects of the scope of this book is the inclusion of chapters relating to the dissemination of knowledge, manuscript publication, and how to build an academic research program. Each chapter focuses on introducing the reader to foundational principles, methodology, and terminology, and highlight case studies of radiation therapist research or experience that is relevant to provide contextual examples and inspiration to the reader.

Quality underpins the success (or failure) of any piece of qualitative research. In this book, Uwe Flick takes you through the steps in method and design to ensure quality and reliability throughout the entire research process. Showing hands-on what it means to ′manage′ quality, this book puts the spotlight on practical questions and steps researchers can use to continually interrogate, improve and demonstrate quality in your research.