E-Book, Englisch, 384 Seiten, Format (B × H): 186 mm x 232 mm
Silver / Lewins Using Software in Qualitative Research
2. Auflage 2014
ISBN: 978-1-4739-0522-1
Verlag: SAGE Publications
Format: PDF
Kopierschutz: 1 - PDF Watermark
A Step-by-Step Guide
E-Book, Englisch, 384 Seiten, Format (B × H): 186 mm x 232 mm
ISBN: 978-1-4739-0522-1
Verlag: SAGE Publications
Format: PDF
Kopierschutz: 1 - PDF Watermark
Using Software in Qualitative Research is an essential introduction to the practice and principles of Computer Assisted Qualitative Data Analysis (CAQDAS). The book will help you to choose the most appropriate package for your needs and get the most out of the software once you are using it.
This book considers a wide range of tasks and processes in the data management and analysis process, and shows how software can help you at each stage. In the new edition, the authors present three case studies with different forms of data (text, video and mixed data) and show how each step in the analysis process for each project could be supported by software.
The new edition is accompanied by an extensive companion website with step-by-step instructions produced by the software developers themselves. Software programmes covered in second edition include the latest versions of:
- ATLAS.ti
- DEDOOSE
- HyperRESEARCH
- MAXQDA
- NVivo
- QDA Miner
- TRANSANA
Ann Lewins and Christina Silver are leading experts in the field of CAQDAS and have trained thousands of students and researchers in using software. Reading this book is like having Ann and Christina at your shoulder as you analyse your data!
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Introduction
Qualitative Data Analysis and CAQDAS
The Nature of Software Support for Research Projects
Software Summaries
Data and Their Preparation for CAQDAS Packages
Early Steps in Software: Practical Tasks and Familiarisation
Exploration and Data-level Work
Qualitative Coding in Software: Principles and Processes
Basic Retrieval of Coded Data
Working with Coding Schemes
Managing Processes and Interpretations by Writing
Mapping Ideas and Linking Concepts
Organising Data by Known Characteristics
Interrogating the Dataset
Convergence, Closeness, Choice