Assignment 7: Finding patterns from interview-based data
- 30 Oct 18:35: Added more information about what open and axial coding is like. See the text above Report contents section.
- 31 Oct 21:15: Added a concrete example about open and axial coding to the discussion forum. See the discussion thread and my example from this link.
This assignment will give you:
- Experience on qualitative analysis of interview material. You will analyse a subset of reports that were collected in last week’s assignment (i.e., A6).
- A chance to compare different interview techniques and their usefulness for qualitative analysis.
Following the research question (RQ) of Assignment 6, your task is to seek answers to the same question (i.e., “How should Instagram increase its support for self-branding?”) by analyzing interviews. The analysis process will borrow elements from the Grounded Theory method, which is a bottom-up data-driven analytical approach.
There is a lot of literature about Grounded Theory. Here are a few sources:
- Wikipedia: https://en.wikipedia.org/wiki/Grounded_theory
- Muller, M. (2014). Curiosity, creativity, and surprise as analytic tools: Grounded theory method. In Olson, J. S. and Kellogg, W. A. (eds.). Ways of knowing in HCI, pp. 25–48. Springer. The book chapter (and the rest of the book too) can be downloaded from Aalto Library: http://libproxy.aalto.fi/login?url=http://link.springer.com/10.1007/978-1-4939-0378-8
- Elliott & Timulak (2005). Descriptive and interpretive approaches to qualitative research. In Jeremy Miles, Paul Gilbert (eds): A Handbook of Research Methods for Clinical and Health Psychology. Oxford University Press, pp. 147-159. Link to article in SemanticScholar.
The task this week is to analyse a subset of data from your last week's interviews on Instagram, using qualitative methods and adopting some of the principles of Grounded Theory. The purpose is to answer the same RQ that was presented already last week.
Follow these steps:
- Familiarize yourself with Grounded theory by reading e.g. the material above.
- Download your dataset: Visit https://users.aalto.fi/~asalovaa/assignment7 , enter your student ID, open the link provided, and download the contents from each link to your computer. All of you will have a set of 10 interviews to analyse. If you returned a report in A6, you will find your own report in your dataset.
- Open coding:
- Start by reading all the interviews one by one
- While you read:
- Try to get into a mindset of making discoveries from the data, e.g., getting you into thoughts that “it could be this way” or “x could be important here”
- Highlight parts (e.g., with your PDF viewer’s highlighting tool) that you find important and meaningful
- Write remarks about your own observations: for example, copy-paste parts from the PDFs to a separate document and add your remarks/observations next not them
- Develop “working hypotheses” about concepts and phenomena that could be important to the RQ or could be answers to it.
- Re-read interviews if you feel that you want to deepen or re-interpret some of your earlier observations.
- Axial coding:
- This stage consists of comparisons of your last step's open observations with each other.
- Categorise your observations together into larger concepts. Here it may help if you use Post-It notes or other small pieces of papers that you can sort and group together. Each piece may contain a one observation and information where in the data you can find the exact data again.
- Develop larger working hypotheses (“substantive theories” in the GT terminology) based on your data and observations.
- Identify similarities and contradictions between different interview contents.
- When you develop a new working hypothesis, seek to verify it by contrasting it with the rest of the content in PDFs. Copy-paste the appropriate parts (especially quotes from participants) to your document
- Summarize your answers to the RQ into 1-3 main ideas. Gather the interview quotes (and screenshots, if applicable) that represent these answers to your summary. This way you can validate the trustworthiness of your findings and also provide the necessary evidence for others.
The report contents
Structure your report into answers to these sections:
1. Codes (1p)
1a. Open codes
Provide a following kind of 3-column table with 5-10 open codes explained:
|Open code||Explanation||Example quote|
|(a short code name)||(one-sentence explanation on what this code is about)||(exact word-by-word quote from the interview materials that exemplifies the code)|
1b. Axial codes
Provide a following kind of 3-column table with 3-7 axial codes explained:
|Axial code||Explanation||Example quote|
|(a short code name)||(one-sentence explanation on what this code is about)||(an exact word-by-word quote from the interview materials that exemplifies the code)|
A full-point answer from this part contains codes that are meaningful with respect to the research question, where the axial codes have a link to the lower-level open-codes, and where the relationships between the codes and the example quotes are understandable.
2. Findings (1p)
Present here 2-3 main findings, as your answer to the research question, using the following structure:
2.1 Finding 1 (replace this heading name with a short name for your finding)
- Describe the idea behind this finding. Refer to the open and axial codes in this description
- Provide quotes and/or screenshots as evidence, so that you can show that your finding is valid
2.2. Finding 2...
A full-point answer from this part contains findings that answer to the research question, and are based on your findings from open and axial coding.
3. Reflection (1 p)
Based on your experience from working with this kind of data, how would you describe a good interviewing technique vs a poor interviewing technique?
A full-point answer from this part describes differences between the interviews that you read, and analyses which ones were easiest to work with in terms of identifying codes and, eventually, findings.
How to return this assignment
This assignment, like every other assignment in this course, is carried out independently. The deadline for this report is on Sunday 3 November at 23:55 and it will be returned here in MyCourses as a single PDF.