Approaches to qualitative data analysis

1. Approaches to qualitative data analysis • DrAyazAfsar

2. Introduction • Qualitative data analysis involves organizing, accounting for and explaining the data; in short, making sense of data in terms of the participants’ definitions of the situation, noting patterns, themes, categories and regularities. In this lecture I will discuss several forms of qualitative data analysis. There is no one single or correct way to analyse and present qualitative data; how one does it should abide by the issue of fitness for purpose. Further, qualitative data analysis, as we shall see here, is often heavy on interpretation, and one has to note that there are frequently multiple interpretations to be made of qualitative data – that is their glory and their headache! In abiding by the principle of fitness for purpose, the researcher must be clear what he or she wants the data analysis to do as this will determine the kind of analysis that is undertaken. The researcher can set out, for example:

3. Cont…Introduction • to describe • to portray • to summarize • to interpret • to discover patterns • to generate themes • to understand individuals and idiographic features • to understand groups and nomothetic features (e.g. frequencies, norms, patterns, ‘laws’) • to raise issues to prove or demonstrate • to explain and seek causality • to explore

4. Cont…Introduction • to test • to discover commonalities, differences and similarities • to examine the application and operation of the same issues in different contexts. • The significance of deciding the purpose is that it will determine the kind of analysis performed on the data. This, in turn, will influence the way in which the analysis is written up. The data analysis will also be influenced by the kind of qualitative study that is being undertaken. • For example, a biography and a case study may be most suitably written as descriptive narrative, often chronologically, with issues raised throughout.

5. Cont…Introduction • An ethnography may be written as narrative or stories, with issues raised, but not necessarily conforming to a chronology of events, and including description, analysis, interpretation and explanation of the key features of a group or culture. A grounded theory and content analysis will proceed through a systematic series of analyses, including coding and categorization, until theory emerges that explains the phenomena being studied or which can be used for predictive purposes. • The analysis will also be influenced by the number of data sets and people from whom data have been collected. Qualitative data often focus on smaller numbers of people than quantitative data, yet the data tend to be detailed and rich. Researchers will need to decide, for example, whether to present data individual by individual, and then, if desired, to amalgamate key issues emerging across the individuals, or whether to proceed by working within a largely predetermined analytical frame of issues that crosses the individuals concerned.

6. Cont…Introduction • Some qualitative studies (e.g. Ball 1990; 1994a; Bowe et al. 1992) deliberately focus on individuals and the responses of significant players in a particular scenario, often quoting verbatim responses in the final account; others are content to summarize issues without necessarily identifying exactly from whom the specific data were derived. Later on here we discuss methods to be used with respect to people and issues. • Some studies include a lot of verbatim conversations; others use fewer verbatim data. • Some researchers feel that it is important to keep the flavour of the original data, so they report direct phrases and sentences, not only because they are often more illuminative and direct than the researchers’ own words, but also because they feel that it is important to be faithful to the exact words used. Indeed, as reported in the example later, direct conversations can be immensely rich in data and detail. Ball (1990) and Bowe et al. (1992) use a lot of verbatim data, not least because those whom they interviewed were powerful people and justice needed to be done to the exact words that they used.

7. Cont…Introduction • By contrast Walford (2001: 92), commenting on the ‘fetish of transcription’, admits that he ‘rarely fully transcribed more than a few interviews for any of [his] research studies’, not least because of the time that it took for transcription (Walford suggests a ratio of five to one – five hours to transcribe one hour of interviews, though it can take much longer than this). • At a practical level, qualitative research rapidly amasses huge amounts of data, and early analysis reduces the problem of data overload by selecting out significant features for future focus. • Miles and Huberman (1984) suggest that careful data display is an important element of data reduction and selection. ‘Progressive focusing’, according to Parlett and Hamilton (1976), starts with the researcher taking a wide angle lens to gather data, and then, by sifting, sorting, reviewing and reflecting on them, the salient features of the situation emerge. • These are then used as the agenda for subsequent focusing. The process is akin to funnelling from the wide to the narrow.

8. Cont…Introduction • At a theoretical level, a major feature of qualitative research is that analysis often begins early on in the data collection process so that theory generation can be undertaken (LeCompte and Preissle 1993: 238). • Researchers should set out the main outlines of the phenomena that are under investigation. They should then assemble blocks or groups of data, putting them together to make a coherent whole (e.g. through writing summaries of what has been found). Then they should painstakingly take apart their field notes, matching, contrasting, aggregating, comparing and ordering notes made. The intention is to move from description to explanation and theory generation.

9. Tabulating data • I outline several examples of data analysis and presentation in this session. The first of these illustrates simple summary and clear, tabulated data presentation and commentary. It derives from a doctorate thesis. • Chinese children learning English: an example of analysing and presenting interview data. • The interview data are presented question by question. In what follows, where the data for respondents in each age phase are similar they are grouped into a single set of responses by row; where there are dissimilar responses they are kept separate. The left-hand column in each table indicates the number of the respondent (1–12) and the level which the respondent taught (e.g. P1,F3 etc.), so, for example, ‘1–3: P 1 means the responses of respondents 1–3, who taught P1 classes; the right-hand column indicates the responses. In many cases it can be seen that respondents all gave similar responses in terms of the actual items mentioned and the coverage of items specified. A brief summary comment is provided after each table.

10. Cont…Tabulating data • The data here derive from a doctorate thesis concerning the problems that school children experience in learning English in China. The data set reproduced is incomplete and has been selected for illustrative purposes only. Note that the data are not verbatim, but have already been summarized by the researcher, i.e. what is presented here is not the first stage of the data analysis, as the first stage would be transcription. • The coding is as follows: P1–P6 = Primary forms (1–6), P1 = Year One, P2 = Year Two etc. F1–F5 = Secondary forms (1–5), F1 = Form One (first year of secondary school), F2 = Form Two (second year of secondary school etc.)

11. The effectiveness of English teaching

12. Cont…Tabulating data • The numbers preceding each letter in the left hand column refer to the number ascribed to the teacher (Box 1). There were twelve teachers in all, six from primary and six from secondary schools. • English teaching and learning at school have not really achieved their intended purposes.Students are poor at understanding written or spoken English, speaking, reading, listening and writing; this limits their abilities, regardless of the number of years of learning English; low-level memorization model leads to superficial learning; teaching and learning are poor; students can enter university, even though their standard is poor, as there are many universities to take students; students do not require English to gain employment.

13. Cont…Tabulating data • Comment: the primary English teachers had a wider range of views than the secondary teachers; there was greater unanimity between the primary teachers in comparison with the secondary teachers; all the Form Three secondary teachers were unanimous in their comments, and all the Form Five secondary teachers had different views. • Box 2 indicates that the strengths of English teaching were that students start to learn English very young, and schools had autonomy over the design of syllabuses. • The weaknesses in English teaching were that insufficient emphasis was placed on understanding, students were too young to learn English, and syllabuses were unrealistic in their demands, being too rich, leading teachers to a ‘spoon-feeding’ mentality in their teaching. • Also undue pressure was put on teachers and students because of the demands of the syllabus and English had to compete with other languages for curriculum space. Hence students did not learn well, despite years of learning English.

14. Cont…Tabulating dataThe strengths and weaknesses of English language teaching

15. Cont…Tabulating data • Comment: apart from one primary teacher, the other eleven teachers, drawn from both primary and secondary schools, were unanimous in the comments they gave. • It was clear that high class size (between 30 and 50 students, rising to 60) and tight syllabuses exerted a significant impact on teaching methods and restrictions of class activities, because of control issues (Box 3). • The nature of this influence is to adopt largely didactic and grammar-translation methods, with little extended recourse to using or ‘thinking in’ English. • Teaching utilized some group activity, but this was very limited. • Teachers used Chinese to explain English.

16. Teaching methods

17. Teaching methods • Comment: all the teachers here were unanimous in their comments which fell mainly into two sets of points. • Students contributed significantly to their own success or failure in learning English (Box 4). • They were shy, afraid of making mistakes and of losing face, and had little interest in learning at all, let alone English; they were overloaded with other subjects, a situation exacerbated by their poor time management; they held negative attitudes to the bookish nature of learning English and its unrelatedness to other curriculum subjects, had too many other distractions and had limited abilities in English; they had little incentive to learn fast as they could repeat courses, gave little priority to English, had poor foundations for learning English and had limited motivation or positive attitudes to learning English; they were given limited direction in their learning and had limited incentive to learn English well, as universities required only a low standard of English.

18. Student-related factors

19. Cont…Tabulating data • Comment: there was a great variety of comments here. There were degrees of agreement: the teachers of the younger primary children agreed with each other; the teachers of the older primary children agreed with each other; and the teachers of the older secondary children agreed with each other. The teachers of the younger secondary children raised different points from each other. • However, the four groups of teachers (younger primary, older primary, younger secondary and older secondary) raised different points from each other. • …

20. Summary of the interview data • The issues that emerge from the interview data are striking in several ways. What characterizes the data is the widespread agreement of the respondents on the issues. For example: There was absolute unanimity in the responses to questions 9, 12. • There was very considerable, though not absolute, unanimity on question 11. In addition to the unanimity already observed, there was additional unanimity among the primary teachers in respect of question 11. • In addition to the considerable, though not absolute, unanimity already observed, there was much unanimity among the primary teachers concerning question 6. • Such a degree of unanimity gives considerable power to the results, even though, because of the sampling used, they cannot be said to be representative of the wider population. • However, the sample of experienced teachers was deliberately selected to provide an informed overview of the key issues to be faced. It must be remembered that, though the unanimity is useful, the main purpose of the interview data was to identify key issues, regardless of unanimity, convergence or frequency of mention. That the respondents articulated similar issues, however, signals that these may be important elements.

21. Cont…Summary of the interview data • Further, the issues themselves are seen to lie in a huge diversity of fields, such that there is no single or simplistic set of problems or solutions. Hence, to complement the considerable unanimity of voice is a similar consensus in identifying the scope of the problem, yet the range of the problems is vast. • Both singly and together, the issues of English language teaching, learning and achievement in Macau are complex. The messages are clear in respect of Form Five students and their English teaching and learning. First, English performance is weak in all its aspects – reading, writing, speaking and listening – but it is particularly weak in speaking and writing. Second, local cultural factors exert an influence on learning English:

22. Cont…Summary of the interview data • Students do not wish to lose face in public (and the Chinese emphasis on gaining and maintaining face is powerful). • Students are shy and afraid of making mistakes. • The pressure of examination success is universal and severe. • The local culture is not English; it is Chinese and, if anything else, is Portuguese rather than English, although this latter is very limited; there is little need for people to speak or use English at present;

23. Cont…Summary of the interview data • In some quarters, knowledge of English culture is seen to be an important element in learning English; this was refuted by the teachers in this sample. • The third main message is that English is seen instrumentally, but this message has to be qualified, as many students gain employment and university entrance even though their English is weak. The fact of English being an international language has limited effect on student motivation or achievement. • Finally, poor teaching and learning are significant contributors to poor performance, in several areas:

24. Cont…Summary of the interview data • There is great emphasis on drill, rote learning and memorization. • There is a predominance of passive rather than active learning, with teaching as the delivery of facts rather than the promotion of learning and understanding. • Traditional didactic methods are used. • There is reliance on a very limited range of teaching and learning styles. • The limited subject and pedagogical knowledge of English teachers are compounded by the lack of adequate initial and post-initial teacher education. • Frequently the careful laying of foundations of English teaching and learning is absent. • Students use so much Chinese during English lessons that they have little chance to think in English – they translate rather than think in English.

25. Cont…Summary of the interview data • From the interview data it can be seen that the size of the problems and issues to be faced in English language teaching and learning is vast. In this example, tables are carefully laid out to draw together similar sets of responses. • The tables enable the reader to see, at a glance, where similarities and differences lie between the two groups of respondents. Note also that after each table there is a summary of the main points to which the researcher wishes to draw the reader’s attention, and that these comprise both substantive and overall comments (e.g. on the topic in hand and on the similarities and differences between the groups of respondents respectively). • Finally, note that an overall summary of ‘key messages’ has been provided at the end of all the tables and their commentaries. This is a very abridged and selective example, and justice has not been done to the whole of the data that the original researcher used. • Nevertheless the point is clearly illustrated here that summarizing and presenting data in tabular form can address the twin issues of qualitative research: data reduction through careful data display and commentary.

26. Five ways of organizing and presentingdata analysis • We present five ways of organizing and presenting analysis as follows: the first two methods are by people, and the next two methods are by issue, and the final method is by instrument. • One can observe in the example of teaching English in Macau that the data have been organized and presented by respondents, in response to particular issues. Indeed, where the respondents said the same, they have been organized by groups of respondents in relation to a given issue. • The groups of respondents were also organized by their membership of different strata in a stratified sample: teachers of younger primary children, older primary children, younger secondary children and older secondary children. • This is only one way of organizing a qualitative data analysis – by groups. The advantage of this method is that it automatically groups the data and enables themes, patterns and similar to be seen at a glance. • While this is a useful method for summarizing similar responses, the collective responses of an individual participant are dispersed across many categories and groups of people, and the integrity and coherence of the individual respondent risks being lost to a collective summary.

27. Cont…Five ways of organizing and presentingdata analysis • Further, this method is often used in relation to a single-instrument approach, otherwise it becomes unwieldy (for example, trying to put together the data derived from qualitative questionnaires, interviews and observations could be very cumbersome in this approach). So, researchers may find it helpful to use this approach instrument by instrument. • A second way of organizing the data analysis is by individuals. Here the total responses of a single participant are presented, and then the analysis moves on to the next individual. • This preserves the coherence and integrity of the individual’s response and enables a whole picture of that person to be presented, which may be important for the researcher. • However, this integrity exacts its price, in that, unless the researcher is interested only in individual responses, it often requires him or her then to put together the issues arising across the individuals (a second level of analysis) in order to look for themes, shared responses, patterns of response, agreement and disagreement, to compare individuals and issues that each of them has raised, i.e. to summarize the data.

28. Cont…Five ways of organizing and presentingdata analysis • While approaches that are concerned with people strive to be faithful to those involved in terms of the completeness of the picture of them qua people, unless case study approaches are deemed to be driving the research, they are usually accompanied by a second round of analysis, which is of the issues that arise from the people, and it is to the matter of issues that I turn now. • A third way of organizing data is to present all the data that are relevant to a particular issue. This is the method that was used in the example of Chinese students learning English. • While it is economical in making comparisons across respondents (the issue of data reduction through careful data display, mentioned earlier), again the wholeness, coherence and integrity of each individual respondent risks being lost.

29. Cont…Five ways of organizing and presentingdata analysis • The derivation of the issue for which data are gathered needs to be clarified. For example, it could be that the issue has been decided pre-ordinately, in advance of the data collection. Then all the relevant data for that issue are simply collected together into that single basket – the issue in question. While this is an economical approach to handling, summarizing and presenting data, it raises three main concerns: • The integrity and wholeness of each individual can be lost, such that comparisons across the whole picture from each individual is almost impossible. • The data can become decontextualized. This may occur in two ways: first, in terms of their place in the emerging sequence and content of the interview or the questionnaire (e.g. some data may require an understanding of what preceded a particular comment or set of comments), and second, in terms of the overall picture of the relatedness of the issues, as this approach can fragment the data into relatively discrete chunks, thereby losing their interconnectedness.

30. Cont…Five ways of organizing and presentingdata analysis • Having had its framework and areas of interest already decided pre-ordinately, the analysis may be unresponsive to additional relevant factors that could emerge responsively in the data. It is akin to lowering a magnet onto data – the magnet picks up relevant data for the issue in question but it also leaves behind data not deemed relevant and these risk being lost. The researcher, therefore, has to trawl through the residual data to see if there are other important issues that have emerged that have not been caught in the pre-ordinate selection of categories and issues for attention. • The researcher, therefore, has to be mindful of the strengths and weaknesses not only of pre-ordinate categorization (and, by implication, include responsive categorization), but also the researcher must decide whether it is or is not important to consider the whole set of responses of an individual, i.e. to decide whether the data analysis is driven by people/respondents or by issues.

31. Cont…Five ways of organizing and presentingdata analysis • A fourth method of organizing the analysis is by research question. This is a very useful way of organizing data, as it draws together all the relevant data for the exact issue of concern to the researcher, and preserves the coherence of the material. • It returns the reader to the driving concerns of the research, thereby ‘closing the loop’ on the research questions that typically were raised in the early part of an inquiry. In this approach all the relevant data from various data streams (interviews, observations, questionnaires etc.) are collated to provide a collective answer to a research question. • There is usually a degree of systematization here, in that, for example, the numerical data for a particular research question will be presented, followed by the qualitative data, or vice versa. This enables patterns, relationships, comparisons and qualifications across data types to be explored conveniently and clearly.

32. Cont…Five ways of organizing and presentingdata analysis • A fifth method of organizing the data is by instrument. Typically this approach is often used in conjunction with another approach, e.g. by issue or by people. Here the results of each instrument are presented, e.g. all the interview data are presented and organized, and then all the data from questionnaires are presented, followed by all the documentary data and field notes, and so on. • While this approach retains fidelity to the coherence of the instrument and enables the reader to see clearly which data derive from which instrument, one has to observe that the instrument is often only a means to an end, and that further analysis will be required to analyse the content of the responses – by issue and by people. • Hence if it is important to know from which instrument the data are derived then this is a useful method; however, if that is not important then this could be adding an unnecessary level of analysis to the data. • Further, connections between data could be lost if the data are presented instrument by instrument rather than across instruments.

33. Cont…Five ways of organizing and presentingdata analysis • In analysing qualitative data, a major tension may arise from using contrasting holistic and fragmentary/atomistic modes of analysis. The example of teaching English in Macau is clearly atomistic, breaking down the analysis into smaller sections and units. It could be argued that this violates the wholeness of the respondents’ evidence, and there is some truth to this, though one has to ask whether this is a problem or not. • Sectionalizing and fragmenting the analysis can make for easy reading. On the other hand, holistic approaches to qualitative data presentation will want to catch the wholeness of individuals and groups, and this may lead to a more narrative, almost case study or story style of reporting with issues emerging as they arise during the narrative! Neither approach is better than the other; researchers need to decide how to present data with respect to their aims and intended readership.

34. Systematic approaches to data analysis • Data analysis can be very systematic. Becker and Geer (1960) indicate how this might proceed: • comparing different groups simultaneously and over time • matching the responses given in interviews to observed behaviour • analysing deviant and negative cases • calculating frequencies of occurrences and responses • assembling and providing sufficient data that keeps separate raw data from analysis.

35. Systematic approaches to data analysis • In qualitative data the analysis here is almost inevitably interpretive, hence the data analysis is less a completely accurate representation (as in the numerical, positivist tradition) but more of a reflexive, reactive interaction between the researcher and the decontextualized data that are already interpretations of a social encounter. Indeed reflexivity is an important feature of qualitative data analysis. The issue here is that the researcher brings to the data his or her own preconceptions, interests, biases, preferences, biography, background and agenda. As Walford (2001: 98) writes: ‘all research is researching yourself’. In practical terms it means that the researcher may b selective in his or her focus, or that the research may be influenced by the subjective features of the researcher. Robson (1993: 374–5) and Lincoln and Guba (1985: 354–5) suggest that these can include:

36. Cont…Systematic approaches to data analysis • data overload (humans may be unable to handle large amounts of data) • first impressions (early data analysis may affect later data collection and analysis) • availability of people (e.g. how representative these are and how to know if missing people and data might be important) • information availability (easily accessible information may receive greater attention than hard-to-obtain data) • positive instances (researchers may over-emphasize confirming data and under emphasize disconfirming data). • internal consistency (the unusual, unexpected or novel may be under treated). • uneven reliability (the researcher may overlook the fact that some sources are more reliable or unreliable than others). • missing data (that issues for which there is incomplete data may be overlooked or neglected) • revision of hypotheses (researchers may over-react or under-react to new data)

37. Cont…Systematic approaches to data analysis • confidence in judgement (researchers may have greater confidence in their finaljudgements than is tenable) • co-occurrence may be mistaken for association • inconsistency (subsequent analyses of the same data may yield different results); a notable example of this is Bennett (1976) and Aitkin et al. (1981). • The issue here is that great caution and self- awareness must be exercised by the researcher in conducting qualitative data analysis, for the analysis and the findings may say more about the researcher than about the data. • For example, it is the researcher who sets the codes and categories for analysis, be they pre-ordinate or responsive (decided in advance of or in response to the data analysis respectively). It is the researcher’s agenda that drives the research and the researcher who chooses the methodology.

38. Cont…Systematic approaches to data analysis • As the researcher analyses data, he or she will have ideas, insights, comments, reflections to make on data. These can be noted down in memos and, indeed, these can become data themselves in the process of reflexivity (though they should be kept separate from the primary data themselves). Glaser (1978) and Robson (1993: 387) argue that memos are not data in themselves but help the process of data analysis. • This is debatable: if reflexivity is part of the data analysis process then memos may become legitimate secondary data in the process or journey of data analysis. Many computer packages for qualitative data analysis (discussed later) have a facility not only for the researcher to write a memo, but also to attach it to a particular piece of datum.

39. There is no single nature or format of a memo; it can include subjective thoughts about the data, with ideas, theories, reflections, comments, opinions, personal responses, suggestions for future and new lines of research, reminders, observations, evaluations, critiques, judgements, conclusions, explanations, considerations, implications, speculations, predictions, hunches, theories, connections, relationships between codes and categories, insights and so on. Memos can be reflections on the past, present and the future, thereby beginning to examine the issue of causality. • There is no required minimum or maximum length, though memos should be dated not only for ease of reference but also for a marking of the development of the researcher as well as of the research.

40. Cont…Systematic approaches to data analysis • Memos are an important part of the self-conscious reflection on the data and have considerable potential to inform the data collection, analysis and theorizing processes. They should be written whenever they strike the researcher as important – during and after analysis. They can be written any time; indeed some researchers deliberately carry a pen and paper with them wherever they go, so that ideas that occur can be written down before they are forgotten. • The great tension in data analysis is between maintaining a sense of the holism of the data – the text – and the tendency for analysis to atomize and fragment the data – to separate them into constituent elements, thereby losing the synergy of the whole, and often the whole is greater than the sum of the parts. • There are several stages in analysis, for example:

41. Cont…Systematic approaches to data analysis • generating natural units of meaning • classifying, categorizing and ordering these units of meaning • structuring narratives to describe the contents • interpreting the data. These are comparatively generalized stages. Miles and Huberman (1994) suggest twelve tactics for generating meaning from transcribed data: • counting frequencies of occurrence (of ideas, themes, pieces of data, words) • noting patterns and themes (Gestalts), which may stem from repeated themes and causes or explanations or constructs • seeing plausibility: trying to make good sense of data, using informed intuition to reach a conclusion • clustering: setting items into categories, types, behaviours and classifications • making metaphors: using figurative and connotative language rather than literal and denotative language, bringing data to life, thereby reducing data, making patterns, decentring the data, and connecting data with theory

42. Cont…Systematic approaches to data analysis • splitting variables to elaborate, differentiate and ‘unpack’ ideas, i.e. to move away from the drive towards integration and the blurring of data • subsuming particulars into the general (akin to Glaser’s (1978) notion of ‘constant comparison’:– a move towards clarifying key concepts • factoring: bringing a large number of variables under a smaller number of (frequently) unobserved hypothetical variables • identifying and noting relations between variables • finding intervening variables: looking for other variables that appear to be ‘getting in the way’ of accounting for what one would expect to be strong relationships between variables • building a logical chain of evidence: noting causality and making inferences • making conceptual/theoretical coherence: moving from metaphors to constructs, to theories to explain the phenomena.

43. Cont…Systematic approaches to data analysis • This progression, though perhaps positivist in its tone, is a useful way of moving from the specific to the general in data analysis. Running through the suggestions from Miles and Huberman (1994) is the importance that they attach to coding of data, partially as a way of reducing what is typically data overload from qualitative data. Miles and Huberman (1994) suggest that analysis through coding can be performed both within-site and cross-site, enabling causal chains, networks and matrices to be established, all of these addressing what they see as the major issue of reducing data overload through careful data display. • Content analysis involves reading and judgement; Brenner et al. (1985) set out several steps in undertaking a content analysis of open-ended data:

44. Cont…Systematic approaches to data analysis • briefing: understanding the problem and its context in detail • sampling: of people, including the types of sample sought • Associating: with other work that has been done • Hypothesis development • hypothesis testing • Immersion: in the data collected, to pick up all the clues • Categorizing: in which the categories and their labels must reflect the purpose of the research, be exhaustive and be mutually exclusive • Incubation: e.g. reflecting on data and developing interpretations and meanings • Synthesis: involving a review of the rationale for coding and an identification of the emerging patterns and themes • Culling: condensing, excising and even reinterpreting the data so that they can be written up intelligibly • Interpretation: making meaning of the data • Writing: including giving clear guidance on the incidence of occurrence; proving an indication of direction and intentionality of feelings; being aware of what is not said as well as what is said – silences; indicating salience (to the readers and respondents) Rethinking.

45. Cont…Systematic approaches to data analysis • Content analysis requires researchers to address several factors: • Understand the research brief thoroughly. • Evaluate the relevance of the sample for the research project. • Associate their own experiences with the problem, looking for clues from the past. • Develop testable hypotheses as the basis for the content analysis. • Test the hypotheses throughout the interviewing and analysis process. • Stay immersed in the data throughout the study. • Categorize the data in the Concept Book, creating labels and codes. • Incubate the data before writing up. • Synthesize the data in the Concept Book, • looking for key concepts.

46. Cont…Systematic approaches to data analysis • Cull the data; being selective is important because it is impossible to report everything that happened. • Interpret the data, identifying its meaning and implication. • Write up the report. • Rethink and rewrite: have the research objectives been met?

47. Cont…Systematic approaches to data analysis • Hycner (1985) sets out procedures that can be followed when phenomenologicallyanalysing interview data. The phenomenologist advocates the study of direct experience taken at face value and sees behaviour as determined by the phenomena of experience rather than by external, objective and physically described reality. Hycner (1985) points out that there is a reluctance on the part of phenomenologists to focus too much on specific steps in research methods for fear that they will become reified. The steps suggested by Hycner, however, offer a possible way of analysing data which allays such fears. As he himself explains, his guidelines ‘have arisen out of a number of years of teaching phenomenological research classes to graduate psychology students and trying to be true to the phenomenon of interview data while also providing concrete guidelines’ (Hycner 1985). In summary, the guidelines are as follows:

48. Brief view of guidelines • Transcription: having the interview tape transcribed, noting not only the literal statements but also non-verbal and paralinguistic communication. • Bracketing and phenomenological reduction: this means ‘suspending (bracketing) as much as possible the researcher’s meaning and interpretations and entering into the world of the unique individual who was interviewed’. • The researcher thus sets out to understand what the interviewee is saying rather than what the researcher expects that person to say. • Listening to the interview for a sense of the whole: this involves listening to the entire tape several times and reading the transcription a number of times in order to provide a context for the emergence of specific units of meaning and themes later on. • Delineating units of general meaning: this entails a thorough scrutiny of both verbal and non-verbal gestures to elicit the participant’s meaning. ‘It is a crystallization and condensation of what the participant has said, still using as much as possible the literal words of the participant’ (Hycner 1985).

49. Cont…Brief view of guidelines • Delineating units of meaning relevant to the research question: once the units of general meaning have been noted, they are then reduced to units of meaning relevant to the research question. • Training independent judges to verify the units of relevant meaning: findings can be verified by using other researchers to carry out the above procedures. Hycner’s own experience in working with graduate students well trained in this type of research is that there are rarely significant differences in the findings. • Eliminating redundancies: at this stage, the researcher checks the lists of relevant meaning and eliminates those clearly redundant to others previously listed. • Clustering units of relevant meaning: the researcher now tries to determine if any of the units of relevant meaning naturally cluster together; whether there seems to be some common theme or essence that unites several discrete units of relevant meaning.

50. Cont…Brief view of guidelines • Determining themes from clusters of meaning: the researcher examines all the clusters of meaning to determine if there is one (or more) central theme(s) which expresses the essence of these clusters. • Writing a summary of each individual interview: it is useful at this point, Hycner suggests, to go back to the interview transcription and write up a summary of the interview incorporating the themes that have been elicited from the data. • Return to the participant with the summary and themes, conducting a second interview: this is a check to see whether the essence of the first interview has been accurately and fully captured.