How to perform automatic focus group coding using ATLAS.ti
Written by: Dr. Neringa Kalpokaite & Ivana Radivojevic
ATLAS.ti 8 Windows and Mac have a brand-new feature to facilitate your qualitative data analyses: automatic focus group coding. How does this work? ATLAS.ti can automatically detect and code each passage of speech in your focus group transcription, so you can quickly and easily recollect all of the responses of each participant and make comparisons. ATLAS.ti can also automatically associate multiple codes at a time, so you can take advantage to prepare your focus group data in whichever way you want to.
Focus groups and possible applications of focus group coding
What is a focus group? Conducting focus group discussions is a method of data collection whereby data are collected from multiple participants at the same time. Focus groups involve a relatively unstructured, but guided, discussion focused around a topic of interest. The researcher only moderates the discussion, because the aim is to foster a natural and free-flowing conversation about the topics. Focus groups are an increasingly popular way to collect data from participants nowadays. Although this was originally developed as a social science method and it was used by many health researchers, it is now rapidly growing and has also spread to political research, market research, and more.
So, typically when we work in ATLAS.ti, we add our data in multiple documents. For example, if we have conducted ten interviews, we will add ten interview transcripts to our ATLAS.ti project. We can then group these ten interviews according to the sex, age, role, and so on, of each participant. By grouping documents according to these different factors, we can easily compare and contrast across our participants. What, then, happens with focus group data? Well, things become a bit more “complicated” since we have all of the information of all of the participants in one single document. Therefore, we cannot group each of our participants according to our different factors of interest (such as age, sex, role, etc.). For example, a single focus group often has a mix of male and female participants, the participants might be in different age groups, have different backgrounds, etc. Thus, it is not possible to add an entire focus group file to a document group of gender: male, or gender: female.
Focus group data therefore need to be treated differently: each speaker unit needs to be identified and coded. The developers of ATLAS.ti foresaw this need, and that is why they developed a dedicated focus group coding tool to facilitate our analysis of rich focus group data.
How to carry out focus group coding
To prepare the focus group transcript, we simply need to make sure that each speaker is clearly indicated by their name, pseudonym, or some abbreviation, followed by a colon (“:”). For example, your transcript may look like this:
Alex: I don’t know, I’m the sort, I don’t really struggle making friends cos everyone tells me I’ve got a big mouth and I don’t stop talking [laughs] …
Tom: So is that how, is that how you met just, just through you striking up a conversation?
Deb: I’m trying to think exactly [laughs] I think that’s what it was, we were both in the same research methods class …
ATLAS.ti will automatically code your focus group data by searching for any colons in the transcript. It is also helpful to start each speaker or passage of speech on a new line in the transcript (although it is not necessary). So, the only thing to remember is that each speaker needs to be clearly indicated by their name/pseudonym followed by a colon. Apart from that, you can follow whichever transcription protocol you prefer. And remember, consistency is key for any quality transcription!
With your transcript ready, you can import it into ATLAS.ti as a regular document. Open your transcript and click on “Focus group coding.”
The focus group coding window will open. You can select which pattern you followed for identifying the speakers in your transcription. If you followed the example above, you can select Pattern 1.
ATLAS.ti now shows all the speakers (or units of speech) that it identified. You can write the name of the code(s) you would like to associate to each speaker on the righthand side. You can enter more than one code name for each speaker/unit of speech by writing the codes names separated by a semicolon (“;”). For example, you can easily add any relevant demographic information about each participant.
Click on “code,” and ATLAS.ti will automatically code your focus group transcript following your indications. You can now see the codings in the transcript,
You can also revise the new codings in the codes and quotations managers, from which you could also export reports of your coded quotations. With this preliminary coding done, you can proceed to read your transcript and continue coding and analysing your data in full (for deeper meanings, themes, or patterns, according to your methodology). You can also carry out content analyses (with word clouds or word lists in ATLAS.ti 8 Windows; with the word cruncher tool in ATLAS.ti 8 Mac). You may like to use auto-coding as well to continue quickly and easily identify keywords throughout your data. Once you have completed coding your focus group data, you can use the code co-occurrence table to compare the responses of your participants. You can also visually explore and present your findings in networks. If you want to recuperate quotations based on specific combinations of your codes, you can take advantage of the query tool.
This article outlines how to carry out focus group coding in ATLAS.ti 8 Windows and Mac. This tool allows you to automatically code all of your focus group data according to each participant (or unit of speech). Focus group coding can facilitate comparisons among your participants. After carrying out focus group coding, you can further analyze your data through manual coding and auto coding. To make comparisons among your participants, you can use the code co-occurrence table. The focus group coding tool makes it easier than ever to analyze your focus group data and draw analytic insights.
Kalpokaite, N., & Radivojevic, I. (2018). Best Practice Article: How to perform automatic focus group coding using ATLAS.ti. Retrieved from https://atlasti.com/2018/08/29/how-to-perform-automatic-focus-group-coding-using-atlas-ti/
About the authors:
Dr. Neringa Kalpokaite has dedicated her professional career to qualitative methodology. From her doctoral thesis for which she received the cum laude award in the Complutense University of Madrid to working as a visiting researcher at Harvard University, all of her research projects have been qualitative and carried out with ATLAS.ti. During her 15 years of professional work, she has published numerous articles in a variety of high-impact journals, she has given over 450 trainings, and she has helped over 8,500 people carry out qualitative research. In addition to leading the Europe Team of ATLAS.ti and being the CEO of NkQualitas, she is also a member of the Editorial Advisory Board of the Journal of New Approaches in Educational Research and a professor at the international IE University. Following students’ demand for more rigorous training in qualitative research, she pioneered and taught the qualitative research and ATLAS.ti course at IE University. She continually participates in international conferences to continue sharing knowledge, and she is part of a team of reviewers of articles from high-impact journals. She has repeatedly received awards for excellent teaching in qualitative research. She has also received several research grants from the Ministry of Foreign Affairs and International Cooperation, the Government of Lithuania, and Harvard University. Her latest publications include “Demystifying Qualitative Data Analysis for Novice Qualitative Researchers“, “Teaching qualitative data analysis software online: A comparison of face-to-face and e-learning ATLAS.ti courses“, and “Leading a successful transition to democracy: A qualitative analysis of political leadership in Spain and Lithuania“.
Ivana Radivojevic, a former student of Dr. Neringa Kalpokaite’s Qualitative Research course, is passionate about qualitative research and ATLAS.ti. After finishing her training, she was invited to join Neringa’s NkQualitas team and has been participating in numerous qualitative research projects since 2015, resulting in multiple publications in high-impact journals. She is currently the Project Coordinator of ATLAS.ti and is a Senior Professional Trainer. She has given numerous courses, including over 250 webinars, and she has helped over 3,000 people learn to use ATLAS.ti and conduct qualitative research. She continually participates in international conferences to learn and share knowledge with the scientific community. Her latest publications include “Demystifying Qualitative Data Analysis for Novice Qualitative Researchers“, “Teaching qualitative data analysis software online: A comparison of face-to-face and e-learning ATLAS.ti courses“, and “Leading a successful transition to democracy: A qualitative analysis of political leadership in Spain and Lithuania“.