Symposium on Qualitative Research: Theory, Methods, and Applications || Methodological Issues and Practices in Qualitative Research

Methodological Issues and Practices in Qualitative ResearchAuthor(s): Jana BradleySource: The Library Quarterly, Vol. 63, No. 4, Symposium on Qualitative Research: Theory,Methods, and Applications (Oct., 1993), pp. 431-449Published by: The University of Chicago PressStable URL: http://www.jstor.org/stable/4308865 .

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METHODOLOGICAL ISSUES AND PRACTICES IN QUALITATIVE RESEARCH

Jana Bradley'

This article considers some methodological issues that arise when empirical inquiry is conducted within the framework of qualitative assumptions about the nature of reality and how we as humans can know it. These assumptions posit an empirical reality that is complex, intertwined, best understood as a contextual whole, and inseparable from the individuals-including the researchers-who know that reality. Four primary issues are considered in this article: the researcher as interpreter; the emergent nature of qualitative research; understanding the experience of others; and trustworthiness in qualitative research. Further, the article discusses methodological practices that have arisen in the context of qualitative assumptions and issues. The practices described are drawn from diverse qualitative research traditions, including participant observation, naturalistic inquiry, grounded theory, hermeneutic approaches to the interpretation of texts (and actions as texts), qualitative evaluation, and a body of methodological literature that calls itself generically "qualitative research." The goals of the article are threefold: (1) to present the internal rationale of qualitative research as issues and practices that arise within the context of assumptions about reality and what we can know about it; (2) to encourage researchers to examine the relevance of qualitative assumptions, issues, and practices to their own research problems; and (3) to point readers toward more detailed discussions of qualitative research.

This article considers methodological issues that arise when empirical inquiry is conducted within the framework of qualitative assumptions about the nature of reality and how we as humans can know it. Further, research practices that qualitative researchers use to address these methodological issues are described. Although writers articulate qualitative assumptions differently, some common underlying ideas can be identified. Some of these recurring ideas-or themes-have been described by Brett Sutton in his article in this issue [1] and are summarized in highly condensed form below to provide context for the discussion in

1. Graduate School of Library and Information Science, University of Illinois, 410 David Kinley Hall, 1407 West Gregory Drive, Urbana, Illinois 61801.

[Library Quarterly, vol. 63, no. 4, pp. 431-449 C 1993 by The University of Chicago. All rights reserved.

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432 THE LIBRARY QUARTERLY

this article. These qualitative themes center around notions that empirical reality should be approached as potentially multiple realities, constructed by perceivers, and frequently acted on as if there were one objective reality. Empirical reality-what researchers set out to capture as data and understand in terms of abstraction-is complex, intertwined, understood most fully as a contextual whole, and ultimately inseparable from the individuals "knowing" that reality.

The issues of perception, meaning, and multiple realities discussed here were not "discovered" by qualitative researchers, nor are they completely ignored by other research traditions. However, in qualitative research, these concerns move center stage. Many of the practices that have become hallmarks of qualitative research-for example, semistructured and unstructured interviewing-have arisen as ways to conduct trustworthy inquiry in a world of complex and interwoven constructed realities.

The purpose of this article is threefold. First, it attempts to present the internal rationale of qualitative research traditions as methodological issues and practices that arise from assumptions about reality and what we can know about it. All research traditions are frameworks of assumptions, issues, practices, problems, and evaluative criteria.2 To be knowledgeable about any research tradition, it is necessary to understand the relationship between practices and the ideas or assumptions that provide the context for those practices. In other words, understanding any research tradition means knowing it from the inside, as it makes sense to those who practice within it.

Questions about the legitimacy, appropriateness, and validity of any research methodology are best answered (and perhaps only answerable) in the context of a specific research problem. The second purpose of this article is to encourage researchers to examine the relevance of qualitative themes and methods to their own research questions.

Finally, the article points readers toward more detailed descriptions of qualitative research.

Multiple Traditions in Qualitative Research

Any discussion of "qualitative research" is complicated by the diversity of discourse and research practice claiming the label "qualitative." Be-

2. Thomas S. Kuhn first introduced this general approach to understanding research methodologies under the rubric of a "paradigm" [2]. Kuhn's revised concept of a paradigm applied to research in the sciences and referred specifically to an exemplar or procedure for solving a problem and its associated assumptions, techniques, issues, and so forth. Since Kuhn, the notion that research processes in the social sciences can



METHODOLOGICAL ISSUES AND PRACTICES 433

cause of this diversity, a description of a single, prototypical qualitative method is not possible or desirable. This article will discuss practices from diverse qualitative research traditions, including participant observation, naturalistic inquiry, grounded theory, hermeneutic approaches to the interpretation of texts (and action as text), qualitative evaluation, and a body of methodological literature that calls itself generically "qualitative research." This approach is designed to present to the reader a range of practices that fly under the qualitative banner. For a classification of qualitative research traditions, and systematic explication of individual traditions, readers are referred to Renata Tesch [5] and William L. Miller and Benjamin F. Crabtree [6].

Four issues that underlie much qualitative research practice will be introduced briefly, and then the qualitative research process will be considered in more detail, with attention to research practices.

The Researcher as Interpreter

Within the context of the qualitative themes mentioned above, the idea of an "objective" researcher is suspect. To be human in this world is to interpret: to assign meaning to experience and view that meaning as objective. Many theorists discuss various aspects of this "social construction of reality." Peter L. Berger and Thomas Luckmann's The Social Construction of Reality is a classic explication of the way that individual humans acting together produce shared constructions of reality, which are then passed on to other individuals through the processes of social- ization [7]. Another classic, Symbolic Interaction by Harold Blumer, focuses on interaction between people as a continuing process of interpretation and construction of reality [8].

Many qualitative issues and practices arise within the context of the inescapable interpretive activity of all humans including researchers. The emphasis in naturalistic inquiry on understanding reality as the participant sees it-the participants' interpretation-is an example of one such qualitative issue. The sharing of interview transcripts with the participants is an example of a practice that addresses this issue, by allowing the participants an opportunity to see and react to their own interpretation.

be grouped together based on common sets of assumptions, definitions of problems, techniques for solving them, and evaluative criteria has become widespread. Many writers continue to use the term "paradigm." I prefer the term "research tradition," used by Paul Diesing [3] and many others. "Perspective" is another term for the same general idea, as in Gareth Morgan's excellent presentation of multiple research perspectives in Beyond Method [4].




The concepts of "preunderstanding" and "understanding," taken from hermeneutics, can help conceptualize the researcher's interpretive activity. "Preunderstanding" is the fusion of knowledge, training, experience, interpretation, and ways of thinking and articulating that individuals bring to any situation. The preunderstanding of the researcher can be viewed as the sum of what the researcher brings to the inquiry [9].

"Understanding" is the knowledge and insight that the researcher develops during the research process. That understanding then becomes preunderstanding for the next round of seeking new understanding, an iterative process described as the "hermeneutic circle" or "hermeneutic spiral." The relationship between preunderstanding and understanding is well put by a hermeneutic maxim: "No understanding without preunderstanding" [9, p. 61]. In other words, all understanding develops from preunderstanding.

Emergent Nature of Qualitative Research

Qualitative research practices vary greatly in the amount of predefined, or prespecified, structure and strategy that shapes the research process. These prespecified structures and strategies range from theory, constructs, and operational definitions guiding data collection to analytical methods driving data analysis. In much qualitative research, these structures and strategies are viewed as suggestive and tentative rather than as directive and rigid. Understanding is expected to emerge as part of the research process and guide the modification of prespecified constructs and strategies or the creation of new ones. The process is an iterative one, where tentative understandings-sometimes called "hypotheses"-are formulated and then "tested" against the data. Testing and extending these new understandings may also involve a return to the field for additional data.

Understanding the Experience of Others

Much qualitative work attempts to understand the experience of others. Michael Quinn Patton articulates clearly a fundamental distinction between indigenous meanings-the meanings that phenomena have for the people being studied-and analyst-constructed meanings-the concepts and other abstractions that researchers bring to the data or de- velop from the data in the form of analysis [10]. A study of public services staff in an academic library illustrates these differences [11].




Using unstructured and semistructured interviews, the researcher elicited the indigenous meanings held by public services staff relating to the rules and regulations in public services units. Through an analysis of the patterns of shared meaning that was guided by a model adapted from coorientation theory [12], the researcher developed what Patton would call "an analyst-constructed typology of the indigenous shared meanings." David Ellis's article in this issue describes the development of an analyst-constructed model of information-seeking patterns of academic researchers using qualitative data [13].

The extent to which people share the same meanings is a complex issue. One view assumes that meanings are objective, that the meaning of phenomena exist in the phenomena themselves. Meanings are thus constant, and differences in understanding of the meaning of specific phenomena arise from ignorance or misunderstanding. For example, "information" as an objective phenomenon is conceptualized as "some- thing that has constant meaning and some element of absolute corre- spondence to reality" [14, p. 13].

Another view assumes that meanings are in some part subjective and emphasizes individual interpretation and the way people make their own sense out of the phenomena around them. Brenda Dervin's concept of "information2," is an example of a subjective view of information: "information2" is defined as "ideas, the structures or pictures imputed to reality by people" [15, p. 22]. Maxine H. Reneker's article in this issue explores the ways in which members of an academic community understand their own information needs [16].

The term "intersubjective" refers to subjective meanings that are shared by groups of people. This concept is discussed by Alfred Schutz [17]. The processes by which shared meaning develops are further ex- plicated in Berger and Luckmann [7]. As an example of intersubjective meaning, librarians sometimes characterize themselves as "information professionals." Individuals outside the library profession, having different individual or intersubjectively shared understandings of this phrase, may encounter it without understanding that it is referring to librarians.

Shutz suggests that people generally assume that meaning is shared until they encounter obvious evidence that others have different meanings. When people act on this assumption of intersubjectivity, they are acting as if meaning were objective, although intellectually they might agree that the assumption of objective meaning is questionable. So, for example, librarians may realize intellectually that people outside the profession may not identify librarians as information professionals, and yet they still act as if everyone understood the meaning of this phrase.

It is useful for all researchers to assess the extent to which participants mean the same thing when they respond in similar ways-by checking




off categories or marking a scale or by using similar words in an open- ended response. An additional question involves the extent to which potential differences in meanings are important in addressing the research question. If the researcher decides that issues of meaning are important, then he or she will want to design data collection in a way that allows similarities and differences to emerge. Barbara M. Wildemuth's article in this issue describes a positivist study designed to analyze the online searching behaviors of students and a qualitative study conducted concurrently to understand more fully the students' reasoning while searching [18].

Trustworthiness in Qualitative Research

All researchers are concerned about the link between the abstractions they posit and their observations of the empirical world that form the basis of these abstractions. In a classic analysis intended to demonstrate that criteria for evaluating research arise from within research traditions and make sense primarily in the terms of those traditions, Yvonna S. Lincoln and Egon G. Guba argue that the criteria suitable for quantitative traditions arise from positivist assumptions [19]. They examine in detail how these assumptions are inappropriate for judging research that is conducted within paradigms that have different assumptions, such as the naturalistic paradigm.

Much writing about qualitative research concerns itself with the criteria that are appropriate for evaluating qualitative research. Lincoln and Guba propose four "trustworthiness" criteria for qualitative research: credibility, transferability, dependability, and confirmability [19, p. 301-28].

Credibility refers to the adequate representation of the constructions of the social world under study and can be assessed both in terms of the process used in eliciting those representations and in terms of the credibility of those representations for the community under study. Lin- coln and Guba's list of activities that work toward credibility include a prolonged stay in the field, persistent observation, triangulation, the search for negative cases, the establishment of referential adequacy by setting aside some portion of the data for testing of conclusions, discussions or debriefing with peers, and checks of results with members of the community under study.

Transferability refers to the extent that the researchers' working hypotheses about one context apply to another. This is a judgment that can be made only by comparing the two contexts, the burden of which falls not on the researcher but on those who wish to make the compari-




son. The researcher's responsibility is to provide enough data, through rich, ample description, to allow these judgments to be made.

The third criterion, dependability, refers both to the coherence of the internal process, addressed by Lincoln and Guba primarily through the concept of an internal audit, and to the way the researcher accounts for changing conditions in the phenomena. Lincoln and Guba's fourth criterion, confirmability, refers to the extent to which the characteristics of the data, as posited by the researcher, can be confirmed by others who read or review the research results.

Catherine Marshall and Gretchen B. Rossman suggest explicit criteria for judging how adequately the research process is documented in written reports of qualitative research: explicitness of data collection methods; analytic constructs documented by data; negative instances dis- played and accounted for; personal, professional, and theoretical biases discussed; analysis strategies articulated; and documentation of the field decisions that altered research strategies [20, p. 148].

Margot Ely provides a description of the ways qualitative researchers strive for trustworthiness that moves beyond procedures:

Being trustworthy as a qualitative researcher means at the least that the processes of the research are carried out fairly, that the products represent as closely as possible the experiences of the people who are studied. The entire endeavor must be grounded in ethical principles about how data are collected and analyzed, how one's own assumptions and conclusions are checked, how participants are involved and how results are communicated. Trustworthiness is more than a set of procedures. To my mind, it is a personal belief system that shapes the procedures in process. [21, p. 93]

As more researchers work within qualitative traditions, the criteria for trustworthy research are being explored, refined, and continually de- bated. Seeking to conduct research in trustworthy ways that are demon- strable and understandable to others is an on-going process in qualitative traditions, as it is in other research traditions.

The four issues discussed above-the researcher as interpreter, the emergent characteristics of qualitative research, understanding the experience of others, and establishing the trustworthiness of qualitative research-are relevant in all stages of the qualitative research process and influence the practices that have developed and are developing under the rubric of "qualitative research." Issues and practices in various stages of the qualitative research process will now be considered.

Design of the Research Process

Given the qualitative assumption that the "knower" cannot be separated from what that person knows, "who the researcher is"-the sum of his




or her preunderstanding-conditions his or her selection of the area of research focus and of the research question or problem. The influence of individual factors, such as personality, gender, experience, and education, on the conduct of inquiry has been the subject of considerable theory and research.3

For the researcher, clarifying his or her own preunderstanding is an important early step in the design of qualitative research. As part of this clarifying process, Evert Gummesson suggests paying attention to personal beliefs and views that can influence the selection of research problems, as well as articulating the more traditional grounding of one's inquiry in theory and previous research [9]. Carolyn M. Evertson and J. Green provide a practical framework for identifying various elements of preunderstanding. Their advice is intended for education researchers and is phrased in terms of classroom observation, but the framework can be used to clarify a researcher's preunderstanding in other contexts [221.

Implicit in any research design is an expectation of what can be learned from inquiry. The broad goals of qualitative research are somewhat different from the goals in quantitative research. Given the impor- tance of context and the assumption of the existence of multiple realities, much qualitative research seeks understanding of specific situations and communicates that understanding through description. The goals of establishing generalizability across situations and seeking lawlike reg- ularities are not priorities for qualitative researchers, and, in some qualitative research traditions, such goals are suspect in the light of qualitative assumptions about the primacy of context.

To assert that qualitative research produces knowledge that is context- bound is not to deny the possibility of understanding many contexts or of developing abstractions that may apply across contexts. But such understanding must be built inductively, from the ground up, establishing relationships that hold for specific situations and then using these to guide inquiry into other situations. The qualitative research tradition of grounded theory, for example, focuses on the development of abstractions from empirical observation and has systematic procedures for collecting data from multiple situations in order to establish boundaries of the theory. The article by Ellis in this issue illustrates the progressive use of cases to check and elaborate theoretical constructs [13]. Purpose- ful sampling, a technique discussed below, is often used to extend the boundaries of theory across contexts. The purpose of such extension is not to establish statistical generalizability but to broaden the scope of situations investigated in detail by the researcher and thus widen the scope of understanding.

3. See [3, pp. 273-99] for an introduction to this literature.




Designing a qualitative research project includes initial specification of many elements of the research design, with the expectation that emerging understanding may suggest alterations to the plan. Typically, the following elements are identified: the setting, including people, places, activities, and temporal duration; the sources of data and the ways in which data will be captured in an initial record; the ways that record will be augmented by interpretation and additional data and shared with others; and the processes by which the trustworthiness of the results can be assessed. Marshall and Rossman provide an excellent guide to designing a qualitative research project, with particularly good advice on communicating qualitative design to those from quantitative research traditions [20]. Ely's guide to all aspects of the qualitative research process, including design, is both unusual and helpful in its use of a descriptive (and very qualitative) approach to discussing qualitative research [21].

Collection of Data

In qualitative research, as in other research traditions, data are collected from the empirical world. Those data then form the basis for conclusions about the empirical world. Any set of data is, in fact, a subset of possible data about any phenomenon, and many of the key issues in data collection across all research traditions address problems inherent in using a subset as a stand-in for a larger data universe. Some approaches to these issues in qualitative research traditions are discussed below.

Prespecification of Data to Be Collected Prespecification, or the identification in advance of structures and strategies that will guide research, has been discussed as an issue important to all phases of the research process. While qualitative research traditions differ in the extent to which data collection plans and instrumenta- tion are determined in advance of actual data collection, the willingness to alter preexisting plans and let data collection strategies emerge in response to developing understanding is a characteristic of much qualitative data collection.

Qualitative Sampling The decisions about whom to collect data from-sampling decisions- are initially made as part of the design phase but can be modified during data collection and also during analysis as new understanding suggests new dimensions of the topic. Patton discusses sampling within qualitative traditions as purposeful to distinguish it from probabilistic sam-




pling in quantitative traditions, where the probability of members of the population being included in the sample is determined as part of the sampling plan. In purposeful sampling, members of the sample are deliberately chosen based on criteria that have relevance to the research question rather than criteria of randomness of selection [10, pp. 169-861.

Sample sizes in qualitative research are often small, especially when compared to samples in quantitative research traditions. Michael Patton describes a number of strategies for the purposeful selection of samples, which are listed here to suggest a range of possibilities. Researchers may, for reasons that relate to their research question, select cases on the following bases: extreme or deviant cases; intensive or information-rich cases; cases providing maximum variation; homogenous cases; typical cases; cases stratified along a particular dimension; critical cases; cases identified through snowball or chain methods; cases selected on the basis of theories or constructs; or cases selected on the basis of opportunity, political considerations, or convenience.

Generally, sample sizes are not governed by steadfast rules. Patton suggests that, in qualitative research, information richness is often the most important factor in the selection of samples. Because the selection of participants serves the purposes of an inquiry that often changes as it progresses, the numbers and types of participants involved in a study are often fluid. A frequently used guideline for knowing when to stop sampling is referred to as "saturation"-continuing to sample until the responses consistently provide no new or conflicting information.

Qualitative Data Sources People are the source, directly or indirectly, of qualitative data. People are the direct sources of data when the researchers interact with them first-hand, such as when people talk to the researchers, take part in activities in the presence of the researchers, or participate in activities of the researchers' design. People are the source of data indirectly when the researcher examines the products of peoples' activities and interactions, like artifacts, documents, citations, and trace evidence like search logs and the physical layout of rooms.

Different data sources provide different slants on phenomena. Devel- oping a sensitivity to the perspectives of data sources is a valuable skill across traditions, and the combination of multiple data sources (one type of triangulation) is often a powerful way of obtaining a fuller understanding of phenomena. An extended example will illustrate the process of considering the perspective that different data sources bring to an inquiry.

In the study of public service units in an academic library cited earlier,




library policies concerning the answering of questions. were of interest [ 1 1]. The document containing the written policy embodied a manifesta- tion of the meaning of the policy to the staff who wrote it several years previously. Current library staff members, including staff in various departments and in various supervisory and nonsupervisory positions, were sources for the meaning of the policy as they understood it. The staff's actions as observed by the researcher were also sources of data. Although not included within the scope of this study, the actions and the meanings held by users interacting with staff who answer or refer questions are also potential sources of data.

The choice of sources of data obviously shapes what will be learned. This decision can only be made by considering which perspectives are needed to illuminate the questions being asked and to achieve the goals of the research. In the above example, the framework of preunderstanding of the researcher toward what constitutes "policy"-by shaping both the question and the research design-also shapes what sources are considered relevant. The researcher who views policy as the written document or as the views of "management" or specific managers is likely to select different data sources from those selected by the researcher who views policy as a composite of actions taken by staff in the name of policy.

In the context of a particular research question, researchers may wish to use multiple data sources to provide views from different perspectives. They may choose to make the differences among perspectives the focus of empirical investigation, as Bradley did in investigating the similarities and differences in the way public services librarians and circulation desk staff understood the meaning of "directional question" [11]. As another alternative, researchers may choose to select only one data source. The single source decision is best made when that source provides the only perspective relevant to a consciously chosen question and framework of preunderstanding, not because the distinctions among possible frameworks of preunderstanding or perspectives of the sources remain unacknowledged or ignored.

Data Collection Techniques It is useful to make a distinction between the sources of data and the means of both elicting and recording data in order to keep straight the way each shapes what becomes data. The choice of techniques for eliciting and for recording data should be a thoughtful one, grounded in an assessment of what data best address the research questions. Miller and Crabtree provide a useful beginning discussion of qualitative data- gathering techniques and references for further reading [6].

Qualitative techniques for eliciting data from sources include observa-




tion, interviewing, and collecting or gaining access to documents, artifacts, or environments. Miller and Crabtree (following Patton) have a useful short discussion about two key issues in observation: the extent to which the observer participates and the extent to which the observation is structured [6]. They also provide a useful categorization and brief discussion of types of structured observation: mapping, category systems, checklists, and rating scales.

Qualitative interviewing is a complex subject, around which an extensive literature is developing. Good introductory discussions are found in Lincoln and Guba [19], Patton [10], and I. Earl Seidman [23]. Miller and Crabtree again provide a useful categorization of dimensions in interviewing: who is interviewed (individual or groups), the structure of the interview (unstructured, semistructured, and structured), and what information is sought [6].

Data as Stand-ins: The Shaping Effects of Techniques An important and complex issue across all research traditions involves the ways in which the techniques and tools chosen to elicit and record data determine the nature of the data that ultimately is used by the researcher as a "stand-in" for the meaning held by the source. Because the methods used condition the data that are collected, triangulation of data collection methods is valuable. The article by Lorraine J. Hari- combe in this issue illustrates how two data collection methods-a survey and interviews-yield different types of data, both of which provide important insights into the research problem [24].

Each data collection method shapes the data in characteristic ways. In interviewing, for example, it is-or should be-an axiom across traditions that the way the question is asked conditions the response. The value of using structures (like categories, for example) is that they focus and standardize responses; and the danger of using categories is also precisely that they focus and standardize responses. The trade-offs can only be decided in the context of specific research questions and goals, where the researcher consciously decides that the shaping provided by the chosen techniques advances rather than hinders inquiry.

Becoming sensitive to the potential of data-gathering practices to condition responses is a valuable skill that can be developed through training and practice. It is useful, and somewhat sobering, to review transcripts of interviews, looking for ways the interviewer's words might have guided responses, both intentionally and inadvertently. Nondirec- tive interviewing is both a skill and an art and takes considerable practice.

Another issue in data collection concerns the extent to which the subset of data that is elicited and recorded is representative of the relevant meanings held by the data source. These questions touch on issues of




the stability of the data source's meaning, the post hoc assignment of meaning to actions and events, and the role of memory. For example, Martin J. Packer and Richard B. Addison argue, following Paul Ricoeur, that intention is a lost event and that an actor's current view of a past action is necessarily a reconstruction in the current moment [25, p. 284].

Issues of the relationship of elicited and recorded data to the meanings held by the data source are fundamental to the trustworthiness of all research. Many qualitative approaches tend to address these issues by the collection of extensive, information-rich data, often over time. An important premise of much qualitative work is that more clues provide greater potential for more complete understanding.

Analysis of Data

Data analysis in all research traditions involves developing both aggrega- tions of the data and abstractions from it. In qualitative traditions, the masses of data are usually broken down into smaller units and then reassembled to call attention to patterns, themes, and concepts. Robert Bogdan and Steven J. Taylor define data analysis in the following way: "A process which entails an effort to identify formal themes and to construct hypotheses (ideas) as they are suggested by the data and an attempt to demonstrate support for those themes and hypotheses" [26, p. 79].

Tesch provides an extensive examination of qualitative data analysis that attempts to draw order out of the plurality of analytic styles and the tangle of terminology [5, pp. 103-34]. Two of her principal distinctions will be mentioned here, and the reader is referred to her excellent discussion for more detail. First, Tesch distinguishes between "structural analysis," where "the analysts assume that the structure is actually inherent or contained in the data and the researcher's job is to uncover it," and "interpretational" approaches, where the "researcher overlays a structure of her/his own making on the data, as a device for rendering the phenomena under study easier to grasp" [5, p. 103]. Within the interpretational style, Tesch identifies two purposes of qualitative research: descriptive analysis and theory building. Again, the reader is referred to Tesch's categorization of techniques for each purpose [5, pp. 114-34]. The overview of data analysis that follows will raise common issues and indicate a variety of practices that include both purposes, but this discussion will not attempt to reproduce Tesch's analysis of the differences.

There are no firm rules or procedures for qualitative analysis as there are for some quantitative analytic methods, as Patton [10] and Matthew




B. Miles and Michael A. Huberman [27] point out. Numerous guidelines for analysis are available, some describing practices common to a particular tradition, some advocating a specific approach, and others at- tempting to describe a generic "qualitative" approach. Guidelines and advice for data analysis cover conceptual issues underlying the breaking down and reassembling of data to reveal patterns as well as the procedural issues that focus on activities that accomplish this regrouping. Tesch provides not only an overview of both conceptual and procedural issues but also a useful description of computer tools available to assist with the procedural aspects [5].

Iterative Nature of Data Collection and Analysis In much qualitative research, data analysis is not rigidly separated from data collection, as in some quantitative methods. Analytic activities go on actively during fieldwork. The hermeneutic circle or spiral conceptu- alizes the internal process by which new understanding becomes part of the researcher's mental apparatus and shapes his or her reaction to future information. This progressive development of understanding is familiar to every qualitative researcher. Specific techniques, many adapted from the fieldwork methods of anthropology, assist in captur- ing the progressive development of the researcher's understanding. Such techniques include writing up field notes immediately after an event or interaction; keeping track of one's insights via journals, diaries, or marginal notes; and a process called "memoing," where a researcher writes periodic summaries of an issue or a problem in a memo to himself or herself.

Although analysis of data goes on during fieldwork, intensive analysis usually takes place after the researcher leaves the research site. Data analysis involves moving back and forth from abstractions-such as categories-to the data, through questioning, comparing, and searching for anomalous cases. Many qualitative traditions encourage returning to the field when more data are needed to illuminate new issues and understandings.

The Analytic Process The quantity of data produced by qualitative studies is voluminous. It comes in the form of records of conversations with individuals often gathered at different times and at different locations, notes from the researchers' observations, and documents and other trace evidence. In addition, traditions such as participant observation and naturalistic inquiry encourage researchers to keep extensive records of their process of observation and analysis.

The analytic process, in general, can be described as breaking down




the data into smaller pieces by identifying meaningful units, grouping these together in categories, and developing relationships among the categories in such a way that patterns in the data are made clear. The relationships that evolve may be presented through description or through the development of conceptual and theoretical statements.

Tesch defines a meaningful unit as "a segment of text that is compre- hensible by itself and contains one idea, episode or piece of information" [5, p. 116]. Guidance for identifying meaningful units may come from prespecified frameworks that are more or less explicit. These frameworks may have been solidified before beginning data collection or may have emerged during it. Other qualitative traditions emphasize the emergence of meaningful units from close examination of the data, guided by the researcher's emergent understanding and by techniques such as questioning and systematic comparison among data elements. Another group of methods is described by Miller and Crabtree as im- mersion or crystallization methods [6]. In these methods researchers immerse themselves as completely as possible in the experience of the participants; as understandings crystallize, they share them with participants. Richard B. Addison's exploration of what it was like to be a medi- cal student and his identification of survival as a pivotal theme informing that experience is a useful example of this type of qualitative research [28].

The grouping together of units in formal or informal categories also proceeds in several ways. Again, the amount of prespecification of categories varies. Preunderstandings, such as formal theory or constructs, can guide the formation of categories, or ideas for categories can emerge from observation. For example, in an exploratory study of interactions between public services staff and library users cited earlier, the category of knowledge loosely characterized as "knowledge of policies and procedures" existed as a concept going into the study, alerting the researcher to look for evidence that these were meaningful to participants in terms of interactions with users [11]. In the first phase of fieldwork, then, the indigenous meaning of "the way things are supposed to be done" emerged as a persistent theme and became a primary category directing both data collection and subsequent analysis. Barney G. Glaser and Anselm L. Strauss [29], Strauss and Judith Corbin [30], and Strauss [31] exemplify methods for grouping meaningful units into categories.

In both interpretation and theory-building analysis, the researcher usually works with some combination of indigenous and analyst-constructed meanings. It is important for researchers to be aware of this distinction and of the way they combine the two types of meanings in their own work.

Working with indigenous units, categories, and relationships raises




issues such as the extent to which meanings are shared by participants, the extent to which they perceive that the meanings are shared, the stability of meanings, and the extent to which the full complexity of the meanings held by data sources have been reflected in the collected data. Analytic techniques can focus on developing the categories of meaning, comparing meanings among participants, understanding participants' perceptions of the objectivity of these meanings, and so forth. In the study of interactions among library staff and library users in an academic library mentioned above [1 1], the indigenous meanings of the phrase "directional question" for members of a public services depart- ment were explored using participant observation and semistructured interviewing. Analysis involved exploring different dimensions of the phrase for all staff members and comparing these meanings among individuals and also within groups. Shared patterns of meaning were found for circulation desk workers that differed from the pattern of meaning shared by librarians.

Working with analyst-constructed units, categories, and relationships focuses primary attention on the correspondences between the analyst's framework of meaning and the data from the empirical world. Activities involve identifying categories, exploring characteristics and dimensions of the categories, positing connections and relationships among them, and testing the categories against the full range of data. Techniques for this activity focus on asking questions and comparing. Other strategies involve formulating hypotheses about the categories and looking for disconfirming evidence or negative cases. Tesch [5], Patton [10], Strauss [31], Bogdan and Taylor [26], Miles and Huberman [27], and Constance Mellon [32] can be consulted for additional discussion and guidelines on the complex topic of identifying meaningful patterns in qualitative data.

"Writing up" Qualitative Studies

Qualitative researchers do a lot of "writing up" in all phases of the research process. Informal "writing up" serves both to articulate one's thoughts and to record them for review later. Whether these informal write-ups take the form of a formal journal, as recommended by Lincoln and Guba and others; memos, notes, or questions to oneself; or prelimi- nary reports to share with peers, they are a tangible way of marshaling current thinking and available evidence and of planning next steps.

When researchers come to the place where they are ready to write up the qualitative study for publication, a new element is introduced: that of a potentially wide audience. The expectations of the scientific




community for the structure of a research article are well established, and most articles from quantitative traditions in the social sciences follow that format. The formats for presenting the results of qualitative work are not nearly so fixed, although different traditions and qualitative research communities have their expectations and criteria for effective reporting. Researchers in the field of library and information science who are adapting qualitative techniques from other disciplinary traditions will want to look both at the methodological advice and at typical examples in qualitative work that are closest to their preferred approach. Almost all the methodological guides mentioned in this review treat the writing up of qualitative work for publication.

Several dimensions of qualitative research report writing are useful to mention. The first dimension relates to Tesch's classification of the purpose of qualitative analysis as description or theory building. Both descriptions of the data and the elucidation of abstractions developed from them are almost always present in all qualitative accounts, but the purpose of the research directs that balance of the presentation.

A second dimension can be characterized as stylistic. Qualitative studies can be reported in a more or less narrative style or in a style that is organized more or less around the research process itself, identifying purpose, theoretical frameworks, methods, and results. There is much leeway within this approach, and any of the parts can assume a domi- nating proportion.

An important problem in writing up qualitative studies involves how to demonstrate adequately to the audience the connections between the researcher's abstractions and the data on which those abstractions are based. Qualitative data are often so diverse and cumbersome that it is difficult to present large arrays of raw data to the audience. Numerous ways around this dilemma have been developed. Elaborated and extensive description is one technique. The use of typical examples is another, and the identification and explanation of negative cases or anomalies is a third approach. Each qualitative writer works out the best way to demonstrate to the reader the fidelity between the data from empirical observation and the abstract patterns and themes that the researcher is presenting as essential for understanding those data.

Summary

This article has discussed some qualitative issues and practices that address the difficulties of trying to comprehend an empirical reality that is complex, intertwined, best understood as a contextual whole, and inseparable from the individuals-including researchers-who "know"




that reality. While these qualitative assumptions, like the assumptions underlying other research traditions, are probably resistant to both proof and conclusive refutation, it is possible, and highly desirable in the interests of methodological pluralism, to explore assumptions that underlie all research in the context of their usefulness in understanding particular research problems. Active discussion of what we know, in light of how we produced that knowledge, can only extend our understanding of problems and issues in library and information science.

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Symposium on Qualitative Research: Theory, Methods, and Applications || Methodological Issues and Practices in Qualitative Research