"The book provides a reference point for beginning educational researchers to grasp the most pertinent elements of designing and conducting research..." —Megan Tschannen-Moran, The College of William & Mary Quantitative Research in Education: A Primer, Second Edition is a brief and practical text designed to allay anxiety about quantitative research. Award-winning authors Wayne K. Hoy and Curt M. Adams first introduce readers to the nature of research and science, and then present the meaning of concepts and research problems as they dispel notions that quantitative research is too difficult, too theoretical, and not practical. Rich with concrete examples and illustrations, the Primer emphasizes conceptual understanding and the practical utility of quantitative methods while teaching strategies and techniques for developing original research hypotheses. The Second Edition includes suggestions for empirical investigation and features a new section on self-determination theory, examples from the latest research, a concluding chapter illustrating the practical applications of quantitative research, and much more. This accessible Primer is perfect for students and researchers who want a quick understanding of the process of scientific inquiry and who want to learn how to effectively create and test ideas.

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.

This accessible and authoritative introduction is essential for education students and researchers needing to use quantitative methods for the first time. Using datasets from real-life educational research and avoiding the use of mathematical formulae, the author guides students through the essential techniques that they will need to know, explaining each procedure using the latest version of SPSS. The datasets can also be downloaded from the book′s website, enabling students to practice the techniques for themselves. This revised and updated second edition now also includes more advanced methods such as log linear analysis, logistic regression, and canonical correlation. Written specifically for those with no prior experience of quantitative research, this book is ideal for education students and researchers in this field.

This essential guide for education students and researchers explains how to use quantitative methods for analysing educational data using IBM SPSS Statistics. By using datasets from real-life educational research, it demonstrates key statistical techniques that you will need to know, explaining how each procedure can by run on IBM SPSS Statistics. Datasets discussed in the book are downloadable, allowing you to hone your skills as you read. In this third edition, explanations have been updated with figures and screenshots from SPSS version 28, alongside a range of new research examples and updated further reading. Daniel Muijs is Dean of the Faculty of Education and Society at Academica University of Applied Sciences in Amsterdam.

Assuming no prior knowledge, Educational Research by R. Burke Johnson and Larry Christensen offers a comprehensive, easily digestible introductory research methods text for undergraduate and graduate students. Readers will develop an understanding of the multiple research methods and strategies used in education and related fields; how to read and critically evaluate published research; and the ability to write a proposal, construct a questionnaire, and conduct an empirical research study on their own. Students rave about the clarity of this best seller and its usefulness for their studies, enabling them to become critical consumers and users of research.

This book is designed to help you gain confidence in analysing and interpreting quantitative data and using appropriate statistical tests, by exploring, in plain language, a variety of data analysis methods. Highly practical, each chapter includes step-by-step instructions on how to run specific statistical tests using R, practical tips on how to interpret results correctly and exercises to put into practice what you have learned. It also includes guidance on how to use R and RStudio, how to visualise quantitative data, and the fundamentals of inferential statistics, estimations and hypothesis testing.

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.

An accessible and user-friendly guide to quantitative data analysis in educational research, aimed at those with little or no prior knowledge of statistical methods.

In recent years, academics and professionals in the social sciences have forged significant advances in quantitative research methodologies specific to their respective disciplines. Although new and sophisticated techniques for large-scale data analyses have become commonplace in general educational, psychological, sociological, and econometric fields, many researchers in music education have yet to be exposed to such techniques. Design and Analysis of Quantitative Research in Music Education is a comprehensive reference for those involved with research in music education and related fields, providing a foundational understanding of quantitative inquiry methods. Authors Peter Miksza and Kenneth Elpus update and expand the set of resources that music researchers have at their disposal for conceptualizing and analyzing data pertaining to music-related phenomena. This text is designed to familiarize readers with foundational issues of quantitative inquiry as a point of view, introduce and elaborate upon issues of fundamental quantitative research design and analysis, and expose researchers to new, innovative, and exciting methods for dealing with complex research questions and analyzing large samples of data in a rigorous and thorough manner. With this resource, researchers will be better equipped for dealing with the challenges of the increasingly information-rich and data-driven environment surrounding music education. An accompanying companion website provides valuable supplementary exercises and videos.

This is a comprehensive guide to quantitative research, rooted in the author's own teaching and research. In particular, it challenges both the student who "does not do numbers" and the student who does nothing but numbers (and who therefore fails to interpret or challenge his/her results). The book shows how all educational researchers need to "do" quantitative research, even if only in the sense of reading other people's research findings. In fact, the book 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 secondary data. This leads to one of the main selling points of the book - Gorard's idea of the "idle researcher", who makes valuable contributions to the research literature by using data gathered by other researchers.