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.
The target audience for this course is researchers in the socal sciences and related fields that draw on qualitative data, post graduate students and supervisors.
Day 1
Becoming familiar with the NVivo working environment. Project design issues and their application in NVivo. Creating, saving and backing up NVivo Projects. 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.
Day2
Managing and thinking about data and recording reflections - the role of journals, memos and an audit trail. Using memos, See Also Links and Annotations to reflect on and record ideas about data. Documenting conversations, themes and threads. Exporting memos to Microsoft Word. Introduction to coding including ways coding data in media other than text. Comparing coding and linking as tools for making meaning. Introduction to framework matrices.
Day 3
Using automated coding processes to search and code text of articles. Introduction to word frequency queries and cluster analysis. Working with the literature, including how EndNote and related bibliographic packages interface with NVivo. Using NVivo to assist with visualising themes, conceptualising the literature and identifying gaps in the current knowledge base.
Day 4
Classifying sources and nodes. Ways of representing demographic characteristics and other attributes. Advanced coding procedures. Introduction to advanced find and query functions including applications of matrix coding queries
Day 5
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.
Completion of an introductory ACSPRI course in qualitative research techniques or an equivalent tertiary course is required. Alternatively a reasonable level of experience and familiarity with qualitative data analysis procedures would be acceptable. Efficiency in using Windows based software is essential. No prior knowledge of NVivo is required.
Richards, L. (2009). Handling Qualitative Data: A Practical Guide (Second ed.). London: Sage.
Bazeley, P., & Jackson, K. (2013). Qualitative Data Analysis with NVivo (Second ed.). London: Sage.
Saldana, J. (2013). The Coding Manual for Qualitative Researchers 2nd Edition (Second ed.). London: Sage.
Silver, C., & Lewins, A. (2014). Using Software in Qualitative Research: A Step-by-Step Guide (Second ed.). London: Sage
Issues arising for users of NVivo for Mac will be addressed but all instruction will in NVivo for Windows.
This course will take place in a computer lab. All equipment will be provided.