From Data To Decisions In Music Education Research

From Data to Decisions in Music Education Research provides a structured and hands-on approach to working with empirical data in the context of music education research. Using step-by-step tutorials with in-depth examples of music education data, this book draws upon concepts in data science and statistics to provide a comprehensive framework for working with a variety of data and solving data-driven problems. All of the skills presented here use the R programming language, a free, open-source statistical computing and graphics environment. Using R enables readers to refine their computational thinking abilities and data literacy skills while facilitating reproducibility, replication, and transparency of data analysis in the field. The book offers: A clear and comprehensive framework for thinking about data analysis processes in a music education context. An overview of common data structures and data types used in statistical programming and data analytics. Techniques for cleaning, preprocessing, manipulating, aggregating, and mining data in ways that facilitate organization and interpretation. Methods for summarizing and visualizing data to help identify structures, patterns, and trends within data sets. Detailed applications of descriptive, diagnostic, and predictive analytics processes. Step-by-step code for all concepts and analyses. Direct access to all data sets and R script files through the accompanying eResource. From Data to Decisions in Music Education Research offers a reference "cookbook" of code and programming recipes written with the graduate music education student in mind and breaks down data analysis processes and skills in an approachable fashion. It can be used across a wide range of graduate music education courses that rely on the application of empirical data analyses and will be useful to all music education scholars and professionals seeking to enhance their use of quantitative data.

From Data to Decisions in Music Education Research provides a structured and hands-on approach to working with empirical data in the context of music education research. Using step-by-step tutorials with in-depth examples of music education data, this book draws upon concepts in data science and statistics to provide a comprehensive framework for working with a variety of data and solving data-driven problems. All of the skills presented here use the R programming language, a free, open-source statistical computing and graphics environment. Using R enables readers to refine their computational thinking abilities and data literacy skills while facilitating reproducibility, replication, and transparency of data analysis in the field. The book offers: A clear and comprehensive framework for thinking about data analysis processes in a music education context. An overview of common data structures and data types used in statistical programming and data analytics. Techniques for cleaning, preprocessing, manipulating, aggregating, and mining data in ways that facilitate organization and interpretation. Methods for summarizing and visualizing data to help identify structures, patterns, and trends within data sets. Detailed applications of descriptive, diagnostic, and predictive analytics processes. Step-by-step code for all concepts and analyses. Direct access to all data sets and R script files through the accompanying eResource. From Data to Decisions in Music Education Research offers a reference "cookbook" of code and programming recipes written with the graduate music education student in mind and breaks down data analysis processes and skills in an approachable fashion. It can be used across a wide range of graduate music education courses that rely on the application of empirical data analyses and will be useful to all music education scholars and professionals seeking to enhance their use of quantitative data.

Editorial Board: Deborah Blair VanderLinde, Oakland University. William Bauer, University of Florida. Lisa R. Hunter, The State University of New York at Fredonia. Ronald Kos, Boston University. Joshua A. Russell, The Hartt School, University of Hartford. Peter Whiteman, Institute of Early Childhood, Macquarie University. Analyzing Influences: Research on Decision Making and the Music Education Curriculum examines influences on research in music teacher preparation, practices, and policies. These influences include administrators’ perspectives, preservice music educators’ beliefs, and in-service teachers’ practices. Invited essays offer insights into past and present trends in music teacher preparation. This collection of studies represents best thinking in the field and serves as an impetus for further research and action. Each author’s analysis on the influences affecting their specific areas provides insights into key issues affecting decision making processes. This volume is a significant addition to the libraries of Colleges of Education and Schools of Music, as well as an important reference for music scholars and educators, researchers, and graduate students who are concerned with advancing both the scope and quality of research in the study of music teaching and learning.

In Statistics in Music Education Research, author Joshua Russell explains the process of using a range of statistical analyses from inception to research design to data entry to final analysis using understandable descriptions and examples from extant music education research. He explores four main aspects of music education research: understanding logical concepts of statistical procedures and their outcomes; critiquing the use of different procedures in extant and developing research; applying the correct statistical model for not only any given dataset, but also the correct logic determining which model to employ; and reporting the results of a given statistical procedure clearly and in a way that provides adequate information for the reader to determine if the data analysis is accurate and interpretable. While it is written predominately for graduate students in music education courses, Statistics in Music Education Research will also help music education researchers and teachers of music educators gain a better understanding of how parametric statistics are employed and interpreted in music education.

This volume provides an understanding of various research methodologies that have been used in music education projects. These methodologies include: historical research; quantitative research; narrative inquiry; action research; ethnography; case study; interpretative phenomenological analysis; arts-based methods; and mixed methods. Each of these research methodologies is detailed, before examples of music education projects that have used these methodologies are described. A separate chapter is devoted to each methodology, and each chapter has been written by a researcher with extensive experience and knowledge of the methodology in question. The book project is an initiative of the Australian and New Zealand Association for Research in Music Education (ANZARME).This association is the peak body for music research across the two countries. ANZARME promotes and supports all styles of research in all avenues of music education. The book will assist all those who are undertaking research in music education, particularly future researchers in music education, such as postgraduate research students. The text will assist researchers in understanding the many available research methods, and will provide clarity in choosing the most appropriate method for their particular research.

In a newly updated paperback release, Collecting, Analyzing, and Reporting Data considers an array of strategies for working with qualitative data in American music education. Observations, interviews, focus groups, document analysis and music-making as data reveal unique potential to inform the field of music education. The capabilities of digital technologies to collect and analyze data, as well as the challenges they present, are examined in the context of an increasingly digitized American society. Guidance is provided to the researcher to understand their role and the ethical landscape they navigate. Collecting, Analyzing, and Reporting Data is the second of three paperback volumes derived from the original Oxford Handbook of Qualitative Research in American Music Education, which outlines the history of qualitative research in music education and explores the contemporary use of qualitative approaches in examining issues related to music teaching and learning.

Pitts investigates the long term aims, impact and effects of music education in a school setting. Evaluating the extent to which school music provides a foundation for lifelong involvement in music, Pitts integrates empirical data with a review of historical and contemporary debates on the practices of music teaching and learning.