Handbook Of Quantitative Methods For Educational Research

As part of their research activities, researchers in all areas of education develop measuring instruments, design and conduct experiments and surveys, and analyze data resulting from these activities. Educational research has a strong tradition of employing state-of-the-art statistical and psychometric (psychological measurement) techniques. Commonly referred to as quantitative methods, these techniques cover a range of statistical tests and tools. Quantitative research is essentially about collecting numerical data to explain a particular phenomenon of interest. Over the years, many methods and models have been developed to address the increasingly complex issues that educational researchers seek to address. This handbook serves to act as a reference for educational researchers and practitioners who desire to acquire knowledge and skills in quantitative methods for data analysis or to obtain deeper insights from published works. Written by experienced researchers and educators, each chapter in this handbook covers a methodological topic with attention paid to the theory, procedures, and the challenges on the use of that particular methodology. It is hoped that readers will come away from each chapter with a greater understanding of the methodology being addressed as well as an understanding of the directions for future developments within that methodological area.

This guide to quantitative research argues that the conventional distinction between primary and secondary research data is inadequate, since there is enormous need/opportunity for conducting research through using and reinterpreting data.

This book provides a clear and straightforward guide for all those seeking to conduct quantitative research in the field of education, using primary research data samples. While positioned as less powerful and somehow inferior, non-parametric tests can be very useful where the research can only be designed to accommodate data structure which is ordinal, or scale but violates a normality assumption, which is required for parametric tests. Non-parametric data are a staple of educational research, and as such, it is essential that educational researchers learn how to work with these data with confidence and rigour.

Published for the American Educational Research Association by Routledge. The Handbook of Complementary Methods in Education Research is a successor volume to AERA's earlier and highly acclaimed editions of Complementary Methods for Research in Education. More than any book to date (including its predecessors), this new volume brings together the wide range of research methods used to study education and makes the logic of inquiry for each method clear and accessible. Each method is described in detail, including its history, its research design, the questions that it addresses, ways of using the method, and ways of analyzing and reporting outcomes. Key features of this indispensable book include the following: Foundations Section-Part I is unique among research books. Its three chapters examine common philosophical, epistemological, and ethical issues facing researchers from all traditions, and frames ways of understanding the similarities and differences among traditions. Together they provide a tripartite lens through which to view and compare all research methods. Comprehensive Coverage-Part II (the heart of the book) presents 35 chapters on research design and analysis. Each chapter includes a brief historical overview of the research tradition, examines the questions that it addresses, and presents an example of how the approach can be used. Programs of Research-Part III examines how research programs connected to eight specific lines of inquiry have evolved over time. These chapters examine phenomena such as classroom interaction; language research; issues of race, culture, and difference; policy analysis; program evaluation; student learning; and teacher education. Complementary Methods-As the title suggests, a central mission of this book is to explore the compatibility of different research methods. Which methods can be productively brought together and for what purposes? How and on what scale can they be made compatible and what phenomena are they best suited to explore? Flexibility-The chapters in Parts II and III are largely independent. Therefore, selected portions of the book can be used in courses devoted to specific research methods and perspectives or to particular areas of education. Likewise, established researchers interested in acquiring new techniques or greater expertise in a given methodology will find this an indispensable reference volume. This handbook is appropriate for any of the following audiences: faculty teaching and graduate students studying education research, education researchers and other scholars seeking an accessible overview of state-of-the-art knowledge about specific methods, policy analysts and other professionals needing to better understand research methods, and academic and research libraries serving these audiences.

This handbook focuses on the often neglected dimension of interpretation in educational research. It argues that all educational research is in some sense ‘interpretive’, and that understanding this issue belies some usual dualisms of thought and practice, such as the sharp dichotomy between ‘qualitative’ and ‘quantitative’ research. Interpretation extends from the very framing of the research task, through the sources which constitute the data, the process of their recording, representation and analysis, to the way in which the research is finally or provisionally presented. The thesis of the handbook is that interpretation cuts across the fields (both philosophically, organizationally and methodologically). By covering a comprehensive range of research approaches and methodologies, the handbook gives (early career) researchers what they need to know in order to decide what particular methods can offer for various educational research contexts/fields. An extensive overview includes concrete examples of different kinds of research (not limited for example to ‘teaching’ and ‘learning’ examples as present in the Anglo-Saxon tradition, but including as well what in the German Continental tradition is labelled ‘pädagogisch’, examples from child rearing and other contexts of non-formal education) with full description and explanation of why these were chosen in particular circumstances and reflection on the wisdom or otherwise of the choice – combined in each case with consideration of the role of interpretation in the process. The handbook includes examples of a large number of methods traditionally classified as qualitative, interpretive and quantitative used across the area of the study of education. Examples are drawn from across the globe, thus exemplifying the different ‘opportunities and constraints’ that educational research has to confront in different societies.

`I often... wonder to myself whether the field needs another book, handbook, or encyclopedia on this topic. In this case I think that the answer is truly yes. The handbook is well focused on important issues in the field, and the chapters are written by recognized authorities in their fields. The book should appeal to anyone who wants an understanding of important topics that frequently go uncovered in graduate education in psychology′ - David C Howell, Professor Emeritus, University of Vermont Quantitative psychology is arguably one of the oldest disciplines within the field of psychology and nearly all psychologists are exposed to quantitative psychology in some form. While textbooks in statistics, research methods and psychological measurement exist, none offer a unified treatment of quantitative psychology. The SAGE Handbook of Quantitative Methods in Psychology does just that. Each chapter covers a methodological topic with equal attention paid to established theory and the challenges facing methodologists as they address new research questions using that particular methodology. The reader will come away from each chapter with a greater understanding of the methodology being addressed as well as an understanding of the directions for future developments within that methodological area. Drawing on a global scholarship, the Handbook is divided into seven parts: Part One: Design and Inference: addresses issues in the inference of causal relations from experimental and non-experimental research, along with the design of true experiments and quasi-experiments, and the problem of missing data due to various influences such as attrition or non-compliance. Part Two: Measurement Theory: begins with a chapter on classical test theory, followed by the common factor analysis model as a model for psychological measurement. The models for continuous latent variables in item-response theory are covered next, followed by a chapter on discrete latent variable models as represented in latent class analysis. Part Three: Scaling Methods: covers metric and non-metric scaling methods as developed in multidimensional scaling, followed by consideration of the scaling of discrete measures as found in dual scaling and correspondence analysis. Models for preference data such as those found in random utility theory are covered next. Part Four: Data Analysis: includes chapters on regression models, categorical data analysis, multilevel or hierarchical models, resampling methods, robust data analysis, meta-analysis, Bayesian data analysis, and cluster analysis. Part Five: Structural Equation Models: addresses topics in general structural equation modeling, nonlinear structural equation models, mixture models, and multilevel structural equation models. Part Six: Longitudinal Models: covers the analysis of longitudinal data via mixed modeling, time series analysis and event history analysis. Part Seven: Specialized Models: covers specific topics including the analysis of neuro-imaging data and functional data-analysis.

The aim of this book is to bridge the gap between introductory and more advanced ‘technical’ books on quantitative methods, helping the reader to progress clearly.