Applied Computer-assisted Qualitative Data Analysis using Nvivo

This course is for those already familiar with qualitative research approaches who are interested in using NVivo to assist with the tasks of qualitative data management and analysis. See prerequisites below for the level of prior knowledge and skills required. While the course will provide an overview of the full NVivo tool kit, the main focus is on learning basic data analysis tools through hands-on experience. Participants will systematically apply software tools to the tasks of developing a research project including: planning for collection of data, preparation of data for analysis and beginning analysis. They will also be introduced to advanced analysis tools including those for theory building, validation and presentation of findings. Participants will explore applications of the software to their own research projects. Sample data will be provided but participants should bring their own data sets, if they have them, and/or copies of articles and research reports relevant to their field of study.

Part I: Becoming familiar with the NVivo working environment and tool kit options. Selecting appropriate tools for different data analysis tasks. Project design issues and their application in NVivo. Creating, saving and backing up NVivo Projects. Classifying sources and nodes. Ways of representing demographic characteristics and other attributes.

Part II: Issues in gathering and preparing data. Working with data sources, including text, spreadsheet, audio and video formats and handling non-text data within the context of an NVivo project. Organising and managing data sources in NVivo.

Part III: Working with the literature. How EndNote interfaces with NVivo when reviewing literature. Using automated coding processes to search and code text of articles. Visualising themes, conceptualising the literature and identifying gaps in the current knowledge base.

Part IV: Managing and thinking about data and recording reflections. Using memos, See Also Links and Annotations to reflect on and record ideas about data. Documenting conversations, themes and threads. Creating audit trails. Exporting memos to Microsoft Word.

Part V: Making meaning from data using text searches, word frequency queries and basic coding processes. Viewing, searching and visualising coding. Organising and managing coding, including building and critiquing coding structures. Documenting relationships and visualising networks. Exporting coded data and reporting on coding.

Part VI: Overview of tools for conceptualising and theory building, representing and reporting findings, and interfacing with other software including Microsoft Word, PowerPoint and Excel. These aspects of working with NVivo are addressed more fully in Advanced Qualitative Data Analysis using NVivo 9.

This course will take place in a computer lab.