Qualitative Data Analysis
Sequence, 5 sessions, 5 days
Qualitative data analysis is an iterative process in which researchers use rigorous techniques to make sense of text, videos, photos, audio files and other data forms. The qualitative approach usually generates an enormous volume of textual data and so, increasingly, researchers adopt software programs to manage qualitative analysis tasks. While software cannot substitute for the thinking necessary in qualitative analysis, the programs have become almost essential for a researcher to get the most out of their data within the shortest time possible.
In this sequence of training sessions, refer back to earlier sessions on Qualitative Methods, revisit approaches to the analysis of qualitative data, and offer classes, including practical sessions, on the use of computer-assisted qualitative data analysis software (NVivo). Remind students that software will help them manage their data, but the analysis relies essentially on the capability, patience, and attentiveness of the researcher.
Schedule the sequence on Quantitative Data Analysis immediately before or after this sequence and relate both to the sequence on the Data Analysis Plan.
Outcomes
By the end of this sequence of sessions, students can:
- Discuss the epistemological orientations guiding qualitative research.
- Identify the best approach for analysing, presenting, and making sense of their qualitative data.
- Appropriately code qualitative data.
- Use qualitative data analysis software for managing and analysing their data.
Preparation
References
- Castleberry, A., & Nolen, A. (2018). Thematic analysis of qualitative research data: is it as easy as it sounds? Currents in pharmacy teaching and learning, 10(6), 807-815.
- Adu, P. Preparing the presentation of qualitative findings: considering your roles and goals. Blogpost.
- University of Hall (2019). NVivo 12 Instructional Videos. Uni Hall Library.
Well before these sessions:
- Provide NVivo software for each student or confirm that all students have the program and that it is functional.
- Develop or find practice exercises for each session. Make sure that you and the resource persons test all the exercises.
Approach
For each session, use a hands-on approach to introduce common practices in qualitative data analysis. After any instruction or demonstration on your own screen, give students specific exercises to enable them to practice.
Assessment
Set practical tasks based on students’ data and research focus, to assess whether students are able to understand the steps.
Set and assess daily assignments that require students to apply the learning to work their own ongoing research.
Steps
| Time | Step |
|---|---|
| Session 1. Philosophies of Qualitative Analysis | 1 day |
| Session 2. The NVivo Software Interface | 1 day |
| Session 3. Codes and Coding | 1 day |
| Session 4. Advanced Data Structuring and Query Tools | 1 day |
| Session 5. Practical Steps and Write Up | 1 day |
Session 1. Philosophies of Qualitative Analysis | 1 day
Cover these elements over the course of the day:
- Modes of thinking for qualitative data analysis.
- Some common approaches to qualitative analysis (including thematic, narrative, content, ethnographic, auto-ethnographic analysis).
Provide a step-by-step guide to conducting thematic and content analyses, with practical examples.
Assign and assess exercises.
Session 2. The NVivo Software Interface | 1 day
Combine explanations and practical exercises to cover these elements over the course of the day:
- Preparing transcripts and other files sources for use in NVivo.
- Importing sources, creating/exporting outputs, working with other files (including Excel, and references.
- Basic visualisation tools.
- Using memos, annotations, and links (see also and memo).
Assign and assess exercises.
Session 3. Codes and Coding | 1 day
Cover these elements over the course of the day:
- Understanding codes.
- Coding approaches in NVivo (including basic coding, in vivo, auto-coding, code description).
- Coding queries: running them, saving and reporting results (including coding matrix).
Assign and assess exercises.
Session 4. Advanced Data Structuring and Query Tools | 1 day
Cover these elements over the course of the day:
- Classifications (cases and sources).
- Sorting and disaggregating data using classifications and codes.
- Running crosstabs and multidimensional tables.
Assign and assess exercises.
Session 5. Practical Steps and Write Up | 1 day
Cover these elements over the course of the day:
- “Some practical steps to get you going”.
- Framework matrix, maps, and charts.
- Generating outputs (exporting and tracking memos, annotations and see also link).
- Practical guides for write up (dos and don’ts, contextualisation and ethnographic summaries, and using tables in report writing/manuscripts).
