Identifying Themes and Coding Interview Data: Reflective

Identifying Themes and Coding

Interview Data: Reflective Practice

in Higher Education

© 2015 SAGE Publications, Ltd. All Rights Reserved.

This PDF has been generated from SAGE Research Methods Datasets.

Identifying Themes and Coding

Interview Data: Reflective Practice

in Higher Education

Student Guide

Introduction

This example introduces coding as an important process for conducting a

comprehensive thematic analysis of interview data. Coding helps to achieve

all three of the aims of thematic analysis: examining commonality, examining

differences and examining relationships.

The interview transcripts used in this exemplar were provided by Jamie Harding, a

Senior Lecturer at Northumbria University. The research carried out was inductive

and the objectives were to explore lecturers’ motivation in choosing their career,

their experiences of teaching students and their views on reflective practice and

change in higher education.

Coding

Coding helps to achieve all three of the aims of thematic analysis: examining

commonalities within a dataset, examining differences and examining

relationships. This example shows how to use codes to identify similarities and

differences between cases in your data.

Codes are usually notes made in the margin of interview transcripts and can take

a number of forms, including: complex system of abbreviations; systems that use

both abbreviations and numbers; and full words and short phrases. This example

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uses primarily words and phrases as codes.

It is helpful to make a distinction between two types of code: apriori codes and

empirical codes (Gibson & Brown, 2010: 132–133). Apriori codes are created prior

to research to reflect categories that are already of interest before the research

has begun. They tend to derive at least partly from the researcher’s previous

reading and are more appropriately used as part of a deductive approach.

Empirical codes are derived after the data evidence has been collected, while

reading through the collected data points of importance and commonality are

identified. Empirical codes are more likely to be used in inductive pieces of

research, where the data is examined and analysed before consideration of the

existing theory and literature. It is important to emphasise that these two forms

of coding are not entirely separate: even when using empirical codes, it is likely

that the researcher’s prior knowledge of the subject will influence decision making

to some extent. Similarly, when using apriori codes, it is almost certain that some

issues and themes will emerge that were not anticipated from the researcher’s

prior reading in the subject area. As Jamie Harding’s research was primarily

inductive, we will look at empirical coding in this example.

Data Exemplar

The interview data was collected in the Faculty of Social Sciences at a case

study university by an interviewer, under the supervision of Jamie Harding, a

Senior Lecturer at Northumbria University. This was primarily an inductive piece of

research, which meant that there was no theory to test and no research questions

to answer. However, there were a number of research objectives. This example

focuses on one of these objectives: to identify feelings about reflective practice

and methods by which it was put into practice.

The interviewee we focus on in this dataset is Thomas. Thomas is a lecturer with

previous work experience in industry. He had been employed at the university

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for a substantial period of time. This dataset will also discuss coding across the

excerpts from Thomas and another lecturer named Lewis and the full transcripts

with three other lecturers. Full transcripts are available in the Download Dataset

section.

Analysis: Coding

Jamie Harding describes how he approached the coding of Thomas’s interview

transcripts. The process of using empirical codes can be broken into four steps.

These steps are:

1. Identifying initial categories based on reading the transcripts.

2. Writing codes alongside the transcripts.

3. Reviewing the list of codes, revising the list of categories and deciding

which codes should appear in which category.

4. Looking for themes and findings in each category

Step 1: Identifying Initial Categories Based on Reading the

Transcripts

Codingshould begin with a thorough reading of the full transcripts to be analysed.

This enables you to identify categories that codes can be placed into and so

saves time in the analysis that follows. Identifying categories is a major part of

separating and sorting your data, however, it is difficult to suggest specific tactics

or techniques for creating categories. The researcher can only use their judgment

to identify broad subject areas under which the data could be grouped.

The initial list of categories will almost inevitably be modified in the course of the

analysis. However, the coding process is likely to take less time and to seem less

daunting if the researcher is able to draw up a preliminary category list at the start.

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My list of categories around reflective practice looked like this:

1. Mechanisms for undertaking reflective practice

2. Motivation for reflective practice

3. Aims of reflective practice

4. Limitations to reflective practice

It is important to note that these categories were based not just on Thomas’s

interview transcripts, but also on the data collected from other participants in the

study at the case study university. The downloadable dataset contains the full

transcripts of all the interviews should the interested reader wish to read the data

in its entirety.

Step 2: Writing Codes Alongside the Transcripts

After deciding on the initial list of categories, and the form that their codes should

take (e.g. abbreviations, words and phrases), the researcher should begin to write

the codes alongside the interview transcripts. The application of codes involves

three elements:

1. Summarising

2. Selecting

3. Interpreting

I will now use a section of an interview with a lecturer, Thomas, to show how codes

can be applied. This section is available in the dataset download and is called

Coding a Transcript: Thomas. As a reminder, the four categories for codes that

had been identified are:

1. Mechanisms for undertaking reflective practice

2. Motivation for reflective practice

3. Aims of reflective practice

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4. Limitations to reflective practice

I followed the three steps of summarising, selecting and interpreting to analyse the

data:

Reducing/summarising: This data reduction step helps the researcher to see

beyond the detail of the individual case and to identify themes. The interview

with Thomas demonstrated that points can often be made more succinctly in

written form than when they are made verbally; reducing/summarising information

through codes can often be quite a simple task.

Selecting: It is better to err on the side of caution and to limit the amount of

selection. It’s preferable to introduce codes that may need to be discarded later,

rather than risk failing to code an idea that could become an important feature of

the analysis. A key element of the inductive approach is that the development of

theory is driven by the research findings, rather than existing theory directing the

nature of data collection and analysis. A helpful guiding principle to decide what to

code is to search for commonality. The creation of categories in advance assists

with the process of selection; on Thomas’s interview transcript I knew to code any

comment about mechanisms, motivations, aims or limitations because these had

already been identified as areas discussed by a number of respondents.

Interpreting: Interpreting phenomena in their context is a key feature of qualitative

research. To correctly interpret the words of respondents, the qualitative

researcher needs to consider the context of what has been said and apply a code

that reflects the most likely meaning of the speaker. Thomas’s comment that:

‘And I think I do that given time but if you’re only teaching the same things, or

doing the same things, with little pressure you can reflect and learn and develop’

was interpreted to mean that time and teaching different subjects were limitations

on his ability to reflect on his practice. I understood that Thomas felt that time

limited his opportunities for reflection from a number of comments that he made

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elsewhere, e.g. ‘There’s not time now to sit and think about it’. However, there

were no additional comments to support my interpretation in the area of teaching

different subjects, so I relied on the context. This is the type of occasion where

a methodological memo is useful, in order to facilitate later reflection on the

judgments that were made during the analysis. I wrote this memo:

Some interpretation was needed for Thomas’ comment: ‘And I think

I do that given time but if you’re only teaching the same things,

or doing the same things, with little pressure you can reflect and

learn and develop.’ It was clear from the context of what was

said that ‘do that’ meant ‘reflect on practice’. It also seemed clear

from comments that were made elsewhere in the interview that

Thomas thought that lack of time was a factor that limited his use of

reflective practice. A further interpretation that was made, although

one with less supporting evidence, was that Thomas believed that

being asked to teach different subjects limited his ability to reflect.

The reason for this interpretation was that Thomas seemed to

be discussing the conditions under which reflection could most

easily take place – having time, teaching the same subjects, not

being under pressure – but then implying that, where any of these

conditions did not apply, reflection was more difficult. However, as

the issue of the subjects taught was not referred to elsewhere in the

interview, this was a particularly subjective interpretation.

Step 3: Reviewing the List of Codes, Revising the List of Categories

and Deciding Which Codes Should Appear in Which Category

A number of practical measures can be taken with an initial list of codes and

categories in order to make better sense of the data. These include:

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• Identifying codes which should be placed in pre-set categories.

• Creating sub-categories within the initial categories.

• Identifying new categories which can bring together a number of codes.

• Identifying codes that apply to sufficient numbers of respondents to be part

of the findings even though they stand outside any category.

• Identifying codes that stand outside any category and should be discarded

because they do not apply to sufficient numbers of respondents.

Each of these steps is demonstrated below for the data relating to reflective

practice, where the initial list of codes was long and unwieldy. The list is shown

below with the name(s) of the respondent(s) who each code applied to. Despite

its length, it is included in full, in the hope that you will not be disheartened if your

initial list looks equally unmanageable:

Complete List of Codes Used in Relation to Reflective Practice

RP important: Fern, Susan, Rachel, Lewis, Thomas

Mechanism – student feedback: Fern, Susan

Mechanism – personal reflection: Fern, Susan, Rachel, Lewis, Thomas

RP should be constant: Fern, Susan, Rachel, Lewis,

Motivation – pride: Fern

RP for both teaching and research: Fern

Lecturers who do not reflect become outdated and stale: Susan

Motivation – for students and lecturer to enjoy teaching: Susan

Internal and external motivation for RP: Susan

Mechanism – personal teaching reviews: Susan

Mechanism – comparing with practice elsewhere in the faculty: Susan

Danger of dreading teaching: Susan

Aim of RP – to excite and engage students: Susan

Accepts responsibility for students’ reaction: Lewis,

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Motivation – to teach well: Rachel

Motivation – to stay updated: Rachel

Failure to reflect leads to outdated practice: Rachel

Change of job helpful: Rachel,

Motivation internal: Rachel, Lewis, Thomas

Need for internal pressure: Rachel

Surprised by lack of external pressure for RP: Rachel, Thomas

Should be collective reflection: Lewis

Limitation to RP – time: Lewis, Thomas

Motivation – to be good at job: Lewis

Motivation – wants to communicate effectively: Lewis

RP should be informal: Lewis

Limitation to RP – teaching new subjects (implied): Thomas

RP has led to improved practice: Thomas

Mechanism – working with colleagues: Thomas

Personal reflection and working with colleagues more effective than

teaching course: Thomas

Used to be greater opportunities for RP: Thomas

Mechanism – watching the teaching of colleagues: Thomas

No opportunity to reflect on bad lecture until next year: Thomas

Delay means reflection will be less effective: Thomas

Motivation – to do the best possible job: Thomas

Motivation internal: Thomas

No oversight of quality of teaching: Thomas

Mechanism – peer review: Thomas

Peer review limited by time: Thomas

Identifying Codes Placed in Pre-Set Categories

The categories identified when first reading through the transcripts were the

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obvious starting point in seeking to identify themes. Including the name of the

category in the code makes it easy to bring the relevant codes together. In the

case of mechanisms for reflective practice, the codes that were easy to place in

this category were:

Mechanism – student feedback: Fern, Susan

Mechanism – personal reflection: Fern, Susan, Rachel, Lewis, Thomas

Mechanism – personal teaching reviews: Susan

Mechanism – comparing with practice elsewhere in the faculty: Susan

Mechanism – working with colleagues: Thomas

Mechanism – watching the teaching of colleagues: Thomas

Mechanism – peer review: Thomas

Creating Sub-Categories

A further stage of analysis may be helpful after the codes that should be placed in

a category have been identified. One method of sub-dividing commonalities is the

creation of sub-categories. It may be possible to identify common characteristics

of some codes beyond membership of the main category, meaning that a sub-

category can be created. The grouping together of codes into sub-categories

can contribute substantially to the identification of themes. For example, in the

case of the list of mechanisms for reflective practice above, all except ‘personal

reflection’ and ‘personal teaching reviews’ could be placed into a sub-category of

‘Mechanisms involving working with others’.

Creating New Categories

This is often more difficult than creating sub-categories and may require some

more conceptual thinking. While it may be obvious from the researcher’s list of

codes that some should go together, in other cases they may need to think a little

further about a common factor that could justify the creation of a new category. It

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may be reassuring to know that this is a skill, like many others in qualitative data

analysis, which develops with practice.

Identifying Codes That Apply to Sufficient Numbers of Respondents

to be Part of the Findings Although They Stand Outside Any Category

Despite their best efforts to fit as many codes as possible into categories,

qualitative researchers tend to find that they have some codes that simply do not

have much in common with any others. They then have to make an important

decision. Should the codes be retained, because they can contribute to the

findings on their own, or should they be discarded? There is no easy answer to

this question but the simplest method of deciding is by looking at the number of

respondents that the code applies to: I might choose a ‘threshold’ of one quarter

of the respondents.

Identifying Codes That Stand Outside Any Category and Do Not

Apply to Sufficient Numbers of Respondents to Be Considered to

Constitute a Theme

This action is closely related to the previous one. Using the threshold of one

quarter of respondents in this case meant that any code which stood outside a

category and which applied to only one respondent should be eliminated from the

analysis. The codes that were eliminated because they did not fit into any category

and only applied to one respondent were:

RP for both teaching and research: Fern

Used to be greater opportunities for RP: Thomas

No opportunity to reflect on bad lecture until next year: Thomas

Step 4: Looking for Themes and Findings in Each Category

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Three pieces of advice are offered when identifying findings:

1. Remember the purpose of thematic analysis

Identifying findings, like every part of thematic analysis, should be guided by

the aims identified by Gibson and Brown (2009: 128–129), i.e. examining

commonality, examining differences and examining relationships. However, not

every dataset, or issue within a dataset, allows for the examination of

relationships, so it may be that only the first two of these aims can be achieved.

Examining relationships is associated more with conceptual findings and building

theory. For the new researcher, identifying similarities and differences within the

data is a very worthwhile first goal of analysis.

2. Be content with simple findings

If the process of creating and modifying categories and codes has been effective,

then identifying findings becomes quite straightforward. Indeed, it is a common

experience for the qualitative researcher to feel disappointed that their findings

are simple and do not seem to be saying anything particularly profound. The skills

that you develop through the analysis will be invaluable when examining more

complex data, which may have a more complicated story to tell.

3. Find ways of expressing trends that avoid the use of numbers

It is rare for qualitative findings to be expressed in terms of specific numbers.

Instead, other words are found to provide indications of trends within the data.

The qualitative researcher must find their own language with which to identify

trends – findings are often expressed in terms such as ‘some’, ‘the majority’ and

‘a number’.

The above three pieces of advice were taken into account when identifying

some of the findings in relation to reflective practice. There were some obvious

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commonalities between respondents, which could be simply stated. However,

the findings in relation to some of the other codes – including those in the sub-

category of ‘Mechanisms involving working with others’ – needed a little more

detail when they were noted:

• Several respondents discussed methods of involving colleagues in seeking

to identify best practice. The methods discussed were both formal (e.g. peer

review) and informal (e.g. watching the teaching of colleagues).

• A small number of respondents discussed incorporating student feedback

into their reflective practice.

Reflective Questions

1. Using the template in the downloadable data, code the section of

Jamie’s interview with the lecturer, Lewis, relating to reflective practice.

2. Identify which codes from the list provided should be placed in the

category of motivation for reflective practice. Then sort them into sub-

categories and identify findings in relation to the theme of motivation.

3. This data example has focused on Jamie’s aim to identify feelings

about reflective practice. Another of Jamie’s objectives was to get

lecturers to discuss different types of students and the experience of

teaching them. With this second objective in mind and using the full

interview transcripts available in the download, follow Jamie’s steps to

categorise and code the data.

Further Reading

Charmaz, K. (2006). Constructing Grounded Theory. London: Sage.

Dey, I. (1993). Qualitative Data Analysis. Abingdon: Routledge. The notes made

are considerably longer than the ones that are used in this chapter but they are

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helpful as an illustration.

Gibson, W. J, & Brown, A. (2009). Working with Qualitative Data. London: Sage.

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Documents

Identifying Themes and Coding Interview Data: Reflective