Data Management in Large-Scale Education Research

Research  data management is becoming more complicated. Researchers are  collecting more data, using more complex technologies, all the while  increasing the visibility of our work with the push for data sharing and  open science practices. Ad hoc data management practices may have  worked for us in the past, but now others need to understand our  processes as well, requiring researchers to be more thoughtful in  planning their data management routines. This book is for anyone  involved in a research study involving original data collection. While  the book focuses on quantitative data, typically collected from human  participants, many of the practices covered can apply to other types of  data as well. The book contains foundational context, instructions, and  practical examples to help researchers in the field of education begin  to understand how to create data management workflows for large-scale,  typically federally funded, research studies. The book starts by  describing the research life cycle and how data management fits within  this larger picture. The remaining chapters are then organized by each  phase of the life cycle, with examples of best practices provided for  each phase. Finally, considerations on whether the reader should  implement, and how to integrate those practices into a workflow, are  discussed. Key Features: Provides a holistic approach to the research  life cycle, showing how project management and data management processes  work in parallel and collaboratively Can be read in its entirety, or  referenced as needed throughout the life cycle Includes relatable  examples specific to education research Includes a discussion on how to  organize and document data in preparation for data sharing requirements  Contains links to example documents as well as templates to help readers  implement practices