From Data to Decisions in Music Education Research: Data Analytics and the General Linear Model Using R

The book "From Data to Decisions in Music Education Research" provides a structured and hands-on approach to working with empirical data in music education research, using the R programming language. It offers a comprehensive framework for thinking about data analysis processes, common data structures and types, techniques for cleaning, preprocessing, manipulating, aggregating, and mining data, methods for summarizing and visualizing data, and detailed applications of descriptive, diagnostic, and predictive analytics processes. The book is designed for graduate music education students and can be used across a wide range of courses that rely on the application of empirical data analyses.

Format: Hardback
Length: 494 pages
Publication date: 23 February 2022
Publisher: Taylor & Francis Ltd

From Data to Decisions in Music Education Research is a comprehensive guide that provides a structured and hands-on approach to working with empirical data in the field of music education. By utilizing step-by-step tutorials accompanied by detailed examples of music education data, the book draws upon concepts from data science and statistics to offer a comprehensive framework for analyzing and solving data-driven problems.

The book is designed to enhance readers' computational thinking abilities and data literacy skills, utilizing the R programming language, a free, open-source statistical computing and graphics environment. R enables users to refine their data analysis skills while promoting reproducibility, replication, and transparency in data analysis practices.

The book offers a clear and comprehensive framework for understanding data analysis processes within the context of music education. It provides an overview of common data structures and types used in statistical programming and data analytics, covering techniques such as cleaning, preprocessing, manipulating, aggregating, and mining data. Methods for summarizing and visualizing data are also discussed, aiding in the identification of structures, patterns, and trends within data sets.

Detailed applications of descriptive, diagnostic, and predictive analytics processes are presented, demonstrating how these techniques can be applied to analyze music education data and make informed decisions. Step-by-step code for all concepts and analyses is provided, allowing readers to follow along and replicate the results. Additionally, direct access to all data sets and R script files is provided through the accompanying eResource, making it convenient for readers to explore and experiment with the data themselves.

From Data to Decisions in Music Education Research is not only a valuable resource for music education researchers but also for graduate students in the field. It breaks down data analysis processes and skills in an approachable fashion, making it accessible to students with varying backgrounds and levels of expertise. The book serves as a reference cookbook of code and programming recipes, providing practical guidance for conducting data analysis and developing insights into music education.

In conclusion, From Data to Decisions in Music Education Research is a must-read for anyone interested in leveraging empirical data to advance music education research and practice. By providing a comprehensive framework, practical techniques, and direct access to data, the book empowers readers to make informed decisions based on data-driven insights. Whether you are a researcher, educator, or practitioner, this book will help you unlock the potential of data analysis in music education and drive positive change in the field.

Dimension: 254 x 178 (mm)
ISBN-13: 9781032060521