It’s no longer acceptable to ignore or side-line technologies designed to facilitate analysis in the teaching of qualitative methods. This post discusses why and illustrates how methods can be taught via software, using qualitative coding as an example
The ‘whether, how and when’ debate
Debate about whether, how and when to teach qualitative software (CAQDAS-packages) alongside the techniques of qualitative data analysis (QDA) is longstanding. Different approaches to the issue can be characterised into two groups:
Designs that ignore or side-line technologies in methods teaching
Just methods – the teaching of qualitative methods without including the use of CAQDAS-packages. There may be a variety of reasons for this, but in these instructional designs CAQDAS-packages are either completely ignored, or just mentioned with students left to learn about them independently if so inclined
Focus on methods – some discussion of CAQDAS-packages but no formal integration with the teaching of methods. Learning a CAQDAS-package may be bolted on to the end of a methods course, for example via a standalone workshop, or students are advised to attend an externally-delivered workshop
Designs that integrating methods and technology
Methods first – successive teaching of methods and CAQDAS-packages. Methods taught first followed by how methods can be operationalised within one or more CAQDAS-packages. The amount of time spent on each within the curriculum varies, but learning about CAQDAS-packages builds on learning about methods.
Methods and technology interwoven – partially integrated teaching of qualitative methods and CAQDAS-packages. A specific analytic method is taught, then different ways it can be operationalised within one or more CAQDAS-packages is taught, thereby switching back-and-forth between methods and technology.
Methods via technology – the teaching of methods and technology is fully integrated, such that analytic techniques are taught not in isolation, but through the use of the CAQDAS-package.
Why it matters: responsibilities to current and next generations
Within the ever-increasingly digital world, methods teachers have responsibilities to teach both methods and technology – meaning adopting a ‘methods first’, ‘methods and technology interwoven’, or ‘methods via technology’ design. This is not to say that dedicated CAQDAS-packages should always be used to undertake qualitative and mixed-methods analysis, or that doing so necessarily results in higher-quality analysis (it’s possible to do high-quality analysis without using dedicated CAQDAS-packages, just like it’s possible to do bad-quality analysis when using dedicated CAQDAS-packages). However, to ignore or side-line technology as happens in ‘just methods’ or ‘methods first’ designs, fails to adequately equip students with knowledge about, and experience of, the variety of tools available that they will need after their studies complete if they want a career in any aspect of qualitative analysis
An example: teaching coding via technology collaboratively
The following example could be adapted for use in the ‘methods first’, ‘methods and technology interwoven’ and ‘methods via technology’ instructional designs. I’m using coding as the example because coding is a common analytic activity in many QDA approaches and is, therefore, a key topic in QDA methods teaching. However, the principles of this example are relevant to – and can be adapted for – any analytic activity or technique taught on a QDA methods course.
The collaborative angle when teaching methods via technology is important because in a methods class multiple students are taught together. This provides powerful opportunities to discuss and illustrate fundamental topics such as interpretive lenses, issues regarding consistency, and practical aspects of team-working. A ‘methods via technology’ instructional design incorporates the collaborative angle of teaching and learning, as well as illustrating key considerations when undertaking QDA in groups.
Note: What follows is not a recipe for teaching coding via a CAQDAS-package – as indicated by the three designs that integrate methods and technology listed above, there is no ideal way – and the instructional design adopted will also depend on a number of other considerations, such as the time available in the curriculum, the expertise of the teacher in CAQDAS-packages, the availability of software at the institution, and the complexity of the CAQDAS-package being used. In addition, the example I’m describing here is not fully fleshed out – but is designed to facilitate thinking about instructional designs that integrate methods and technology, using teaching coding via CAQDAS-packages as an illustrative example.
Strategies for teaching qualitative coding
Coding not a uniform activity – methodologies, practicalities and personal preferences all influence qualitative coding. It’s common and useful to broadly distinguish approaches by directionality – for example, whether inductive (bottom-up, from data to concepts/themes), deductive (top-down, from theory to data), or a combination of the two. There’s great value in contrasting the specifics of different methodological traditions regarding qualitative coding in these broad distinctions because it opens up thinking about the spectrum of analytic methods more generally – for example from the very qualitative approaches to qualitative data analysis on one end of the spectrum (including approaches like Grounded Theory and Interpretive Phenomenological Analysis) to the quantitative approaches to qualitative data analysis (including approaches like Text Mining and Content Analysis).
Amongst the instructional objectives for teaching coding within such a framework might be the illustration of:
the interpretive processes involved in inductive coding – for example deciding what to code, how much to code, how many codes to generate, and so on…
the importance of precise definitions – for example, to ensure shared understandings amongst multiple researchers, and to open up discussion about the concept of reliability in relation to coding in qualitative methodology
the variety in interpretations – for example highlighting the influence of human factors (knowledge of the topic, preconceptions, level of analytic thinking) and interpretive factors (the nature of concepts and themes), and so on…
the challenges involved in developing shared understandings of concepts – for example comparing students’ codes, and discussing how/why this dialogue contributes to understanding the qualitative material, the length of time it takes to come to shared understandings of concepts
the role of theory and processes of hypothesis testing in qualitative analysis – for example how a coding scheme can be developed a priori entirely or partially derived from an existing theory, or previous research project, and the appropriateness of this way of working in the context of different research objectives, contexts and methodologies
the need to consider units of meaning when coding – for example discussing the meaning and appropriate use of information about the frequency of code-application, and the importance of context in informing decisions of how much to code
what codes can represent – for example, the use of codes to represent descriptive topics, structural features of qualitative materials, concepts and categories, dimensions and properties of themes, and so on…
the role of analytic note-taking whilst coding – for example keeping notes on the adequacy of a priori coding schemes when taking deductive approaches and keeping track of growing interpretations and the meaning of concepts in inductive approaches
Tactics for teaching coding
So how could we go about teaching coding with instructional objectives like these? If we were doing so without using dedicated CAQDAS-packages we’d likely provide a few hard-copy transcripts to students and a bunch of differently coloured highlighter pens. If teaching inductive coding we’d provide a loose research question to guide the coding - but otherwise minimal instructions for what and how much to code, how many codes to develop and so on. Whereas, if teaching deductive coding we’d provide a much tighter research question to code towards, accompanied by a structured and well-defined codebook that includes precise inclusion and exclusion criteria for each code. Either way, we’d give them a set amount of time and off they’d go…either working independently or in small groups.
Some benefits of teaching coding via technology
It takes very little time to teach how to operate a CAQDAS-package for the purposes of coding, because they all enable coding via very simple click or drag/drop processes. The benefits of teaching coding via technology become especially apparent when students have accomplished some coding in a CAQDAS-package – either independently, or in small groups – and you begin discussing how the process felt to open up thinking around the instructional objectives you’re working towards.
Note: I’ve used screenshots below from four different CAQDAS-packages. The intention of this article is not to make direct comparisons between products or to promote any product over any other. Any CAQDAS-package can be used to teach qualitative coding drawing on the principles discussed here. The screenshots have simply been chosen to show a range of different visualisations that are useful when teaching qualitative coding via technology.
Bringing students’ coding together
The way this can happen depends on the functionality of the CAQDAS-package. If it’s an online application or you’re working with a multi-user version, then you’d be able to have all students log-in to one project and all work on the same data files at the same time. Depending on the CAQDAS-package, this might mean they’d be able to see each other’s coding as they work – which may or may not be instructionally beneficial.
If the instructional design requires students to initially work separately and then combine their work, this can be done by bringing their multiple CAQDAS projects together. This happens in different ways depending on the CAQDAS-package but results in being able to see the coding work of all students together in one place – so their work can be compared and discussed in relation to the instructional objectives.
Code development when teaching inductive coding
If you’ve given students a loose research question to guide their coding, and only minimal instructions, it’s highly likely they will have made a range of decisions concerning how much to code, how many codes to develop, how to organise codes, the level of detail of their code definitions and so on. Looking at these differences through the software is a visually powerful way of illuminating and discussing these common issues when adopting inductive coding approaches. That can be done in several ways, depending on how the CAQDAS-package you’re using works.
Comparing students coding
It’s much quicker and easier to compare how students have coded via a CAQDAS-package so you can have discussions around developing and defining codes when teaching inductive coding and issues involved in applying an a priori coding scheme when teaching deductive coding. This is because it’s easily possible to see ‘who did what’ so the group can discuss differences in how codes were applied.
Some CAQDAS-packages include the ability to even more systematically compare coding which can be incredibly instructionally powerful when teaching deductive coding because they can calculate inter-coder agreement.
We don’t need to throw away our highlighter pens
Adopting instructional designs that integrate methods and technology doesn’t mean we have to throw away our highlighter pens! Many advocates of dedicated CAQDAS-packages who use and teach those technologies suggest students should experience manual coding at least once – if only to realise how messy it can be in comparison to the use of dedicated CAQDAS-packages that are designed for the purpose. This approach is embedded in both ‘methods first’ and ‘methods interwoven with technology’ designs.
Adaptability
I’ve used qualitative coding as an illustrative example in this article but the principles and techniques discussed can be adapted to any analytic activity in any qualitative or mixed-methods approach.