24 Exploring the Field – Research Cycles in Qualitative Approach

N. Nakkeeran

1. Introduction

Qualitative research has evolved as an integral feature of social sciences along with the way these disciplines understood reality and what according to them constituted knowledge (Green and Thorogood 2004). Qualitative research is being increasingly seen as an important approach to research occupying a special niche that cannot be filled by alternative approaches. This is the most potent approach available for exploring new terrains of human life that assumes an imposing dimension by the sheer expanse of human experiences and the way it gets complexly reconfigured by rapid changes that the society continuously undergoes. Qualitative research has been one of the significant contributions that social sciences have made to other Sciences, equipping them with a greater variety and possibilities of enquiries (Nakkeeran 2010).

In this module we aim to bring out the following aspects: (a) nature and characteristic features of qualitative research, including a short note on data collection methods of data analysis used in this approach (b) research spiral in general and features of research cycle in qualitative research.

2. Nature of Qualitative Research

Qualitative approach to research is applied in situations that demand exploration into unknown socio-cultural terrains, either in the form of new cultures, sociological processes, or meanings of human actions and values. These researches could explore a new population, a new problem, finding new concepts, new meanings, new variables, unravel a set of local vocabulary or classifications. In other words, these inquiries can potentially encounter entirely unexpected issues (Bryman 1988) and situations. They aspire to richly capture human lives as a dynamic process rather than events, through descriptions as the primary form of research output. Importance is given to insiders’ or emic perspectives and understanding the meaning they attribute to their actions and decisions. The research procedures employed in this approach are crafted in such a manner that they support this aspiration. This underlines the need for a flexible study design, with openness in the selection of data collection methods and a responsive reflexive way of selecting study participants. Aspects associated with data collection, data analysis and inference making are expected to unfold as one proceeds into the study. As we would see, all the features of qualitative research that we are going to discuss in the paragraphs that follow immediately invariably highlight the iterative and the cyclic nature of qualitative research procedures.

2.1. Naturalism

Qualitative research aspires to study the empirical world as natural, undisturbed, unaltered or unadulterated as possible. Further, whatever thus studied is aspired to be represented as scrupulously with a claim of high “fidelity to the empirical world” (Matza 1969, cited in Bryman 1988: 58). This requires a cultural immersion, which means getting close to a community, know the participants as a real member of the community, become part of their life and observe the field unobtrusively. The situations studied are typically ‘banal’ and ‘normal’ ones reflecting the everyday life of individuals and groups. Qualitative research, hence, requires an intense and prolonged contact with the community (Nakkeeran 2006).

2.2. Importance of context and emphasis on holism

Any behaviour or process is studied located in its context and meaning of such behaviour or process is derived from and consistent with the context. Context facilities the prediction, explanation, and understanding of phenomenon (Hinds et al. 1992). It also implies that the process of inquiry, methods and tools used will be context dependent and will evolve along with the unfolding social reality and emergent themes. Holism is the other side of the same coin as that of contextualism. It implies that the Issue of concern is studied in its entirety, as a whole, interrelated with and configured by other aspects of social reality, rather than as isolated entities (Nakkeeran 2006).

2.3.  Intensive/in-depth and long term

Qualitative research chooses to study a smaller community or organization over a longer period of time. This facilitates an intensive holistic study, as natural as possible, with a scope to focus on the context in great detail. Establishing an increasingly stronger rapport with the community becomes a possibility. The data collection process is not a one-time interaction between the researcher and the participants, but is long drawn with opportunities for several meetings in different locations and from different angles. The content and the quality of data collected changes as the study progresses (Nakkeeran 2006).

2.4. Flexible and evolving study design

As the data collection process is long, the researcher need not and cannot go with a pre-decided plan of data collection and be blind to new research questions that are thrown up by emerging data. Hence, a researcher need not go with a neatly planned and rigid study design. The data collection process expected to constantly respond to new observations and research questions that emerge from the field. The researcher constantly engages with the data collected and reflexively reformulates research questions, data collection procedures, etc. Methods of data collection depend on research questions, and these questions depend on the context as it unfolds. Research rules are more like principles to follow and data collection instruments require relatively little standardisation (Nakkeeran 2006).

2.5. Study of social life as processes

A holistic and intensive study also provides qualitative studies with a potential to study a phenomenon as a process. As Bryman (1988: 65) points out, there is an “implicit longitudinal element build into much qualitative research” hence they become most suitable to study social life as a process rather than as time-frozen events (Nakkeeran 2006).

2.6. Insider’s perspective

Qualitative research tries to interpretatively understand insider’s (emic) perspective than explain events or processes from outside. It aims to understand the meaning attributed by members of the community embedded within their worldview to any event or process. Context specific meanings are the aspiration rather than universal de-contextualised explanations for human behaviour.

2.7. Data Collection methods

Data collected in qualitative studies are usually in the form of narratives and descriptions. In-depth interviews and participant observations are the principal methods of data collection used in qualitative research. Other methods include textual analysis, focus group discussion and participatory methods. Ethnography and case study are composite methods that use a combination of methods listed above. Ethnography is considered as the qualitative method par excellence, which typically involves a researcher residing in the community that is being studied for over a period of time, immersing herself/himself in that culture and studying it holistically. It combines in-depth unstructured interview and participant observation. Case study is a study of one. It could be study of one culture, one organisation or an event in entirety. A case can be studied for its intrinsic value or as instrumental to understand a class of phenomena of which the chosen case is a typical representative. Typically, in case study, the number of variables studied far outstrips the number of data points (which is usually one). Case study as method is most frequently used in situations where phenomenon studied is too complex, without a clear boundary, without a clear disconnect with its context. Interviews used are unstructured and informal. These interviews lack structure or control, an informant is free to treat a question as s/he likes, usually with no written set of questions, conducted in natural settings. One gets more than one chance to interview an informant. Thus, a researcher may start the first encounter as a casual chat to get introduced, gain rapport, and get a feeling about the community or group. Progressively, the researcher may infuse a sense of purpose, order and rigour into this process. In the subsequent encounters, the researcher comes out with a clear purpose in her/his mind, may feel free to jot down points or electronically record them, and could even come prepared with a checklist or an interview guide.

These interviews are combined with observation. A researcher, after gaining acceptance and rapport in the community, is able to observe the happening in the community or group without creating strong reactions or resentment from their members. Notwithstanding her/his presence in the community, the members may remain ‘natural’ and unperturbed. Hence, the researcher is able to observe the behaviour and interactions of individuals in as natural a setting as possible.

2.8. Data analysis

Data analysis in qualitative research is preferred to be a concurrent process taking place along with data collection (see Figure 5B). This is because data collection is usually a protracted process. A researcher has the opportunity to look at the data and to read, re-read and grapple with the field notes continuously throughout the period of data collection. Gaps in the data, when identified, are sought to be filled with further data collection. New patterns and explanations are arrived at, and tested back in the field. Thus, the researcher moves back and forth between the field and the field-notes. Through this continuous process of reflexive, iterative engagement with the field and the data, the researcher starts to have a rudimentary understanding of the community, arrives at categories and concepts, and develops rudimentary explanations; all of which in turn are expected to lead to a higher level of explanation or theory. The specific practical aspects of qualitative data analysis have been brought out in many different ways by different scholars (Glaser and Strauss 1967, Miles and Huberman 1994; Ritchie and Spencer 1994). Whatever may be the approach to analysis, all of them essentially involve a cycle of three fundamental interrelated components viz., noticing, collecting and thinking (See Figure 4) (Seidel 1998).

Self-check exercise – I

1.  What are the key characteristics of qualitative research

Qualitative research aspires to study the empirical world as natural, undisturbed, unaltered or unadulterated as possible. Any behaviour or process is studied located in its context and meaning of such behaviour or process is derived from and consistent with the context. Any issue of concern is studied in its entirety, as a whole, interrelated with and configured by other aspects of social reality, rather than as isolated entities. Qualitative research chooses to study a smaller community or organization over a longer period of time. Establishing an increasingly stronger rapport with the community is emphasised. The data collection process is not a one-time interaction but is long drawn with opportunities for several meetings with participant in different locations and from different angles. The data collection process is open, flexible and is expected to constantly respond to new observations and research questions that emerge from the field. Research rules are more like principles to follow and data collection instruments require relatively little standardisation. A phenomenon is studied as a process rather than as a time-frozen shot. Qualitative research tries to interpretatively understand insider’s (emic) perspective than explain events or processes from outside.

2. Name important methods of qualitative data collection

Informal, unstructured, in-depth interviews, focus group discussion, case study, participant observation are some of the important qualitative methods of data collection. Ethnography typically combines informal unstructured interview and participant observation.

3. How is qualitative data analysis different from quantitative data analysis

Data analysis in qualitative research is preferred to be a concurrent and iterative process taking place along with data collection. Through this continuous process of reflexive, iterative engagement with the field and the data, the researcher progressively develops explanations of increasing levels of robustness. Quantitative data analysis on the other hand is most often a terminal process that starts after data collection is over. It is a distinct stage and designed not to be influenced by the kind of data getting collected and vice versa.

3. Knowledge generation as an iterative process

Synthesis of new knowledge in any field is best understood as an iterative cyclic process. A set of individual, empirical observations may lead to the formation of a corpus of knowledge, having an explanatory relevance, which in due course may evolve and solidify into a theory. This theory may get challenged by further observations thus getting further refined into a more robust and rigorous one. This theory assumes a degree of tenacity, stands relevant over a longer period and hence forms the basis for deducing explanations for further observations. This cycle continues with the theory evolving to be more robust and at the same time the reality that the theory aspires to explain also dynamically varying. In other words, knowledge generation over a period of time happens through a cyclic process alternating between induction – hypotheses formation – deduction – prediction – observation – test of prediction – induction and so on.

It may be useful here to recall the idea of ‘hermeneutic cycle’ as “the foundational law of all” interpretation, “understanding and knowledge”, which essentially refers “to find the spirit of the whole through the individuals, and through the whole to grasp the individual” (Friedrich Ast 1808, cited in Mantzavinos 2009: 300)

Different sciences and methodological approaches within each discipline may emphasise different phases of this cycle depending upon the way these disciplines / approaches look at reality, the part of the reality they choose to study and the kind of problems they may choose to address. Unlike in disciplines like mathematics or physics, social sciences like sociology or anthropology do not have any invariant law or theories that hold good over time and across all societies. Hence, they cannot fall back on any such laws to deduce an explanation for a new observation. Instead, these disciplines continuously induct newer observations into a body of evolving explanation to arrive at a relatively more robust explanation for a set of related observations. However, as the reality studied is dynamically varying across societies and time, there is always a need for increasingly refined, altered or nuanced explanations (Nakkeeran 2006) and hence the cycle continues.

4. Research Spiral

Individually, every research is also usually understood as a cyclic or spiral process. For different scholars and in different disciplines this cycle may be represented slightly in different ways, but more or less the fundamental set of stages of research could be enumerated as follows: exploring the conceptual field, arriving at research problem, designing the study, collecting data, analysing the data, coming up with findings and to make inferences that perhaps would feed into new research questions and so on.

Though these stages of research are usually considered to be sequential in nature, some of the stages within this cycle could be iterative in nature rather than as one shot activities. Further, it is also possible that at any stage a loop back to any previous stage is potentially possible and is frequently the case. Having said this, it may be useful to make a distinction between two research approaches that are fundamentally different from each other and the way the respective research cycles could be construed viz., quantitative and qualitative.Quantitative  approach to research prescribes a priori design and structure to the process of inquiry. This approach primarily aims at arriving at the facts that have scope for standardisation or broad generalisations.This approach, by intent and design, advocates a linearly linked stages of research that are neatly separated from each other and not porous to allow corruption of one stage by another, unless or otherwise ordained in the a priori design. For instance, within a single research data collection and data analysis are two distinct stages of activities and as a norm data analysis begins after the process of data collection is completed (see Figure 5A). Further, the exact manner in which the research will be executed, including finer details is desired to be meticulously planned and explicitly stated in advance as part of the ‘study design’. This sort of disciplining and standardisation are required as the purpose of such researches is to arrive at universally relevant facts on distribution, association, causation, effectiveness, efficiency etc. of any aspect of concern. Most quantitative research fall in this group, although one has to add a caveat that not all quantitative studies by default fall into this category.

5. Research Cycles in Qualitative Approach

In light of the purpose of using qualitative research and its key features the research cycles in this approach is relatively more complex. Although the broad stages of research, enlisted in Figure 2, remains more or less the same it requires further elaboration. To explore and to capture unexpected findings, the study design is expected to be open, flexible and evolving rather than pre-decided at the outset. To capture reality as a stream of processes and to gain insiders’ perspective, data collection process is protracted with an inbuilt longitudinality (Bryman 1988) and aims to gain access to peoples’ life gradually. Every stage of research in this approach becomes iterative in nature and celebrates interlocking of one stage of research into others in order to enrich the process of inquiry.

The qualitative research cycle suggested by Hennink, Hutter, and Bailey (2011) captures this complexity to a great extent. They conceive the research process in three distinct but interrelated sub-cycles circumscribed within a larger cycle. The three sub-cycles include the design cycle, the ethnographic cycle and the analytic cycle (See Figure 3). The design cycle captures the entire process of conceptualization up to arriving at a broad design of the study, roughly what is captured by the first three blocks in our Figure 2 starting from ‘exploring the conceptual field’ along with the backward loops.

The ethnographic cycle represents the process of qualitative data collection. It shows the iterative nature of data collection moving between designing the instrument, identifying study participants, data collection, and making inferences in a cycle. This underlines that the data collection is not a one-time activity, but a protracted one. One starts with an initial set of informants; but as the study proceeds a new set of informants are progressively identified informed by the data that gets collected, explanations and new questions that emerge from the field. Accordingly, the data collection instruments are altered and refined to meet the challenges posed by the field.

The analysis cycle captures the component of data analysis with sub-elements of “developing codes, description and comparison, categorizing and conceptualizing data and theory development” in an interlinked cyclic manner. Similar exclusive treatment of data analysis is undertaken by Ritchie and Spencer (1994) in their model of ‘framework analysis’ where analysis is seen in terms of a series of steps after data collection, viz., familiarisation, identifying a thematic framework, indexing, charting, mapping and interpretation. A much simpler representation of qualitative data analysis is given by Seidel in a cycle of three fundamental interrelated components, viz., noticing (familiarization, indexing, coding), collecting (sorting, sifting, categorization, making code-families) and thinking (leading to lists, types, classes, sequences, patterns, processes, relationships, concepts) (Seidel, op cit) (See Figure 4)

Figure 4: Essential components of qualitative data analysis

Apart from conceiving the qualitative research in the form multiple sub-cycles, Hennink et al. (2011) emphasise three significant points in their idea of qualitative research cycle. One, within each sub-cycle the activities listed are not only interlinked and iterative but they could also happen simultaneously. Two, the three sub-cycles representing the process of conceptualising the research, data collection and analysis are strongly interconnected and they feed forward and backward into one another. Three, while qualitative research is usually considered to be primarily inductive in nature, Hennink et al emphasize that “the process of induction continuously alternates with deductive reasoning” (ibid. 4). This implies that at every stage a body of knowledge emerges from the field through the process of induction, but that body is used as a reservoir of knowledge to deduce from for further refinement of the exploratory and explanatory processes. This reflects our understanding of data collection, data analysis and theory building as enunciated in classical ‘grounded theory’ through the processes of ‘analytical induction’, ‘constant comparison’ and ‘theoretical sampling’ (Glaser and Strauss 1967).

One key point, although implied in Hutter-Hennink qualitative research cycle, but not sufficiently highlighted and brought is the possibility of simultaneity of occurrence of all the three cycles. In qualitative research literature, the simultaneity of especially data collection and analysis has been strongly emphasised. In fact, these stages of research could happen concurrently or even they may coalesce with each other. This is popularly represented as shown in Figure 5B and differentiated from terminal analysis (Figure 5A). The first figure (5A) represents the sequential and distinct processes of data collection followed by data analysis. The second picture (5B) shows data collection and data analysis as concurrent processes. In the initial days of field work data collection is more intensive compared to data analysis; but even at this state the process of analysis gets started. As the field work proceeds, progressively the intensity of data analysis increases in proportion to the intensity of data collection and towards the end of the fieldwork, data analysis becomes highly intensive, but data collection too continues at a minimum level.

Self-check exercise – 2

1.  What is a hermeneutic cycle

Hermeneutic cycle is an approach for interpretation and understanding that beliefs that the whole should be understood through studying the individuals and individuals have to be interpreted through studying the whole. The first use of this term is attributed to Friedrich Ast, in 1808. One may

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appreciate importance of this idea while we discuss the ideas around induction-deduction cycle and research spiral.

2.   Explain the cycle of ‘noticing’, ‘collecting’ and ‘thinking’ cycle.

This cycle is useful to understand stages of qualitative data analysis. Noticing refers to that stage in which a researcher involves in familiarization, indexing, and or coding of data. Collecting involves sorting, sifting, and or categorization of data/quotations and thinking refers to mapping and charting of data that may lead lists, types, classes, sequences, patterns, processes, relationships, or concepts. This is a simplistic representation of stages of qualitative data analysis given by Seidel.

3.   Explain ‘Framework analysis’

This a strategy of qualitative data analysis popularised by Ritchie and Spencer (1994). According to this model qualitative data analysis is seen in terms of five steps after data collection, viz., familiarisation, identifying a thematic framework, indexing, charting, mapping and interpretation.

6.  Key points

·         Use: Strongest approach for exploring new socio cultural terrain, gaining interpretative understanding of meanings attributed by participants to their actions derived from their worldview

·         Naturalism: Aims to study and represent the empirical world as natural as possible with high fidelity, requiring cultural immersion by the research and become part of community’s everyday life.

·         Importance of context and emphasis on holism: A behaviour or process is studied located in its context and their meaning derived from the context. An issue of concern is studied in its entirety as interrelated with other aspects of social reality.

·         Intensive/in-depth and long term: Studies a smaller community over long time, intensely. This facilitates holistic, naturalist study with a scope for a high degree of rapport and greater focus on the context. Provides opportunities for several meetings with participants in different situations.

·         Flexible and evolving study design: Longer data collection process provides scope for iterative engagement with the field reflexively reconfiguring the research questions and data collection processes as a response to emerging data.

·         Study of social life as processes: There is an inbuilt ‘longitudinality’ (Bryman 1988), hence are most suitable to study social life as a process rather than as events.

·         Data Collection methods: Data is usually in the form of non-numerical descriptive format. The key feature of data collection methods put emphasis on undeterred sharing by participants. In-depth informal, unstructured interviews, participant observations, focus group discussion are key ‘building-block’ methods used. Ethnography and case study are composite methods that use a combination of methods listed above. Ethnography is considered as the qualitative method par excellence.

·         Data analysis: Is a concurrent process often taking place along with data collection. Involves moving back and forth between the field and the field-note to gain a progressively better understanding, arrives at categories, concepts and leading to higher levels of explanations.

·         Induction – deduction cycle of knowledge generation – Knowledge generation happens through a cyclic process, alternating between induction and deduction flowing between specific observations and a set of general principles. Social sciences like sociology and anthropology continuously induct newer observations into a body of evolving explanation to arrive at a relatively more robust

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explanation for a set of related observations. As the reality studied is dynamically varying, there is always a need for dynamically varying and increasingly nuanced explanations.

·         Research Spiral – Every research progresses as cyclic or spiral process, involving the following stages: exploring the conceptual field, arriving at research problem, designing the study, collecting data, analysing the data, coming up with findings, making inferences that perhaps would feed into new research question and hence the new cycle.

·         Two fundamentally distinct approaches to research: Quantitative and qualitative.

·         Quantitative approach – It aims at arriving at universally relevant facts on distribution, association, causation, effectiveness, efficiency etc. Prescribes a priori design and structure to the process of inquiry, advocates a linearly linked stages of research that are neatly separated from each other.

·         Research Cycle in Qualitative Approach – Every stage of research is cyclic in nature and interlocking with other is celebrated. Hennink, Hutter, and Bailey (2011) represent this in the form three distinct but interrelated sub-cycles – viz., design, ethnographic and analytic cycles – circumscribed within a larger cycle. There is a possibility of simultaneous of occurrence of all the three cycles. These stages of research could happen concurrently or even coalesce with each other.

7.  References

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