Synthesizing Qualitative Research: Choosing the Right Approach (Key Concepts)


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Meta-Synthesis

Judgments about usefulness and credibility are left to the researcher and the reader. Before conducting a qualtitative study, a researcher must do three things. First, s he must adopt the stance suggested by the characteristics of the naturalist paradigm. Second, the researcher must develop the level of skill appropriate for a human instrument, or the vehicle through which data will be collected and interpreted.

Finally, the researcher must prepare a research design that utilizes accepted strategies for naturalistic inquiry Lincoln and Guba, Glaser and Strauss and Strauss and Corbin refer to what they call the "theoretical sensitivity" of the researcher. This is a useful concept with which to evaluate a researcher's skill and readiness to attempt a qualitative inquiry. Theoretical sensitivity refers to a personal quality of the researcher. It indicates an awareness of the subtleties of meaning of data.

Strauss and Corbin believe that theoretical sensitivity comes from a number of sources, including professional literature, professional experiences, and personal experiences. The credibility of a qualitative research report relies heavily on the confidence readers have in the researcher's ability to be sensitive to the data and to make appropriate decisions in the field Eisner, ; Patton, Lincoln and Guba identify the characteristics that make humans the "instrument of choice" for naturalistic inquiry.

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Humans are responsive to environmental cues, and able to interact with the situation; they have the ability to collect information at multiple levels simultaneously; they are able to perceive situations holistically; they are able to process data as soon as they become available; they can provide immediate feedback and request verification of data; and they can explore atypical or unexpected responses.

Eisner claims there is a "paucity of methodological prescriptions" for qualitative research, because such inquiry places a premium on the strengths of the researcher rather than on standardization p. Lincoln and Guba provide a fairly detailed outline for the design of naturalistic inquiry, which includes these general steps:. Determine a focus for the inquiry. Boundaries, however, can be altered, and typically are.

Determine the fit of the research paradigm to the research focus. The researcher must compare the characteristics of the qualitative paradigm with the goals of the research. Determine what the successive phases of the inquiry will be. Phase one, for example, might feature open-ended data collection, while successive phases will be more focused. Determine what additional instrumentation may be used, beyond the researcher as the human instrument.

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Plan data collection and recording modes. This must include how detailed and specific research questions will be, and how faithfully data will be reproduced. Steps one and two have been addressed in previous sections; the remaining steps will be addressed below. In quantitative inquiry, the dominant sampling strategy is probability sampling, which depends on the selection of a random and representative sample from the larger population.

The purpose of probability sampling is subsequent generalization of the research findings to the population. By contrast, purposeful sampling is the dominant strategy in qualitative research. Purposeful sampling seeks information-rich cases which can be studied in depth Patton, Patton identifies and describes 16 types of purposeful sampling. These include: extreme or deviant case sampling; typical case sampling; maximum variation sampling; snowball or chain sampling; confirming or disconfirming case sampling; politically important case sampling; convenience sampling; and others , pp.

According to Lincoln and Guba , the most useful strategy for the naturalistic approach is maximum variation sampling. This strategy. For small samples a great deal of heterogeneity can be a problem because individual cases are so different from each other. The maximum variation sampling strategy turns that apparent weakness into a strength by applying the following logic: Any common patterns that emerge from great variation are of particular interest and value in capturing the core experiences and central, shared aspects or impacts of a program Patton, , p.

Maximum variation sampling can yield detailed descriptions of each case, in addition to identifying shared patterns that cut across cases. See Hoepfl for an illustration of this strategy applied to technology education research. Several examples of studies employing case sampling can also be found in the technology education literature see Brown, ; Hansen, ; and Lewis, and In spite of the apparent flexibility in purposeful sampling, researchers must be aware of three types of sampling error that can arise in qualitative research.

The first relates to distortions caused by insufficient breadth in sampling; the second from distortions introduced by changes over time; and the third from distortions caused by lack of depth in data collection at each site Patton, The two prevailing forms of data collection associated with qualitative inquiry are interviews and observation. Qualitative interviews may be used either as the primary strategy for data collection, or in conjunction with observation, document analysis, or other techniques Bogdan and Biklen, Qualitative interviewing utilizes open-ended questions that allow for individual variations.

Patton writes about three types of qualitative interviewing: 1 informal, conversational interviews; 2 semi-structured interviews; and 3 standardized, open-ended interviews.


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An interview guide or "schedule" is a list of questions or general topics that the interviewer wants to explore during each interview. Although it is prepared to insure that basically the same information is obtained from each person, there are no predetermined responses, and in semi-structured interviews the interviewer is free to probe and explore within these predetermined inquiry areas. Interview guides ensure good use of limited interview time; they make interviewing multiple subjects more systematic and comprehensive; and they help to keep interactions focused.


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In keeping with the flexible nature of qualitative research designs, interview guides can be modified over time to focus attention on areas of particular importance, or to exclude questions the researcher has found to be unproductive for the goals of the research Lofland and Lofland, Recording Data.

A basic decision going into the interview process is how to record interview data. Whether one relies on written notes or a tape recorder appears to be largely a matter of personal preference. For instance, Patton says that a tape recorder is "indispensable" , p. Lincoln and Guba base their recommendation on the intrusiveness of recording devices and the possibility of technical failure.

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Recordings have the advantage of capturing data more faithfully than hurriedly written notes might, and can make it easier for the researcher to focus on the interview. The classic form of data collection in naturalistic or field research is observation of participants in the context of a natural scene. Observational data are used for the purpose of description-of settings, activities, people, and the meanings of what is observed from the perspective of the participants.

Observation can lead to deeper understandings than interviews alone, because it provides a knowledge of the context in which events occur, and may enable the researcher to see things that participants themselves are not aware of, or that they are unwilling to discuss Patton, A skilled observer is one who is trained in the process of monitoring both verbal and nonverbal cues, and in the use of concrete, unambiguous, descriptive language.

Sours' study of teaching and learning styles provides a good example of descriptive language applied to the technology classroom. There are several observation strategies available. In some cases it may be possible and desirable for the researcher to watch from outside, without being observed. Another option is to maintain a passive presence, being as unobtrusive as possible and not interacting with participants.

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A third strategy is to engage in limited interaction, intervening only when further clarification of actions is needed. Or the researcher may exercise more active control over the observation, as in the case of a formal interview, to elicit specific types of information. Finally, the researcher may act as a full participant in the situation, with either a hidden or known identity.

Each of these strategies has specific advantages, disadvantages and concerns which must be carefully examined by the researcher Schatzman and Strauss, The presence of an observer is likely to introduce a distortion of the natural scene which the researcher must be aware of, and work to minimize. Critical decisions, including the degree to which researcher identity and purposes will be revealed to participants, the length of time spent in the field, and specific observation techniques used, are wholly dependent on the unique set of questions and resources brought to each study.

In any case, the researcher must consider the legal and ethical responsibilities associated with naturalistic observation. Field researchers rely most heavily on the use of field notes, which are running descriptions of settings, people, activities, and sounds. Field notes may include drawings or maps. Acknowledging the difficulty of writing extensive field notes during an observation, Lofland and Lofland recommend jotting down notes that will serve as a memory aid when full field notes are constructed.

This should happen as soon after observation as possible, preferably the same day. In addition to field notes, researchers may use photographs, videotapes, and audio tapes as means of accurately capturing a setting. Based on their experience with naturalistic research, Lofland and Lofland believe that researchers are more likely to gain successful access to situations if they make use of contacts that can help remove barriers to entrance; if they avoid wasting respondents' time by doing advance research for information that is already part of the public record; and if they treat respondents with courtesy.

Because naturalistic researchers are asking participants to "grant access to their lives, their minds, [and] their emotions," it is also important to provide respondents with a straightforward description of the goals of the research p. Another source of information that can be invaluable to qualitative researchers is analysis of documents. Such documents might include official records, letters, newspaper accounts, diaries, and reports, as well as the published data used in a review of literature.

In his study of technology teachers in training, Hansen analyzed journal entries and memos written by participants, in addition to interviews. Hoepfl , in her study of closure of technology teacher education programs, used newspaper reports, university policy documents, and department self-evaluation data, where available, to supplement data gained through interviews.

There are some specialized forms of qualitative research which rely solely on analysis of documents.

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For example, Gagel used a process known as hermeneutic inquiry to investigate the literature on both literacy and technology. Patton provides a good overview of the various theoretical orientations that inform the "rich menu of alternative possibilities within qualitative research" p. Qualitative researchers have few strict guidelines for when to stop the data collection process. Criteria include: 1 exhaustion of resources; 2 emergence of regularities; and 3 overextension, or going too far beyond the boundaries of the research Guba, The decision to stop sampling must take into account the research goals, the need to achieve depth through triangulation of data sources, and the possibility of greater breadth through examination of a variety of sampling sites.

Bogdan and Biklen define qualitative data analysis as "working with data, organizing it, breaking it into manageable units, synthesizing it, searching for patterns, discovering what is important and what is to be learned, and deciding what you will tell others" , p. Qualitative researchers tend to use inductive analysis of data, meaning that the critical themes emerge out of the data Patton, Qualitative analysis requires some creativity, for the challenge is to place the raw data into logical, meaningful categories; to examine them in a holistic fashion; and to find a way to communicate this interpretation to others.

Sitting down to organize a pile of raw data can be a daunting task. It can involve literally hundreds of pages of interview transcripts, field notes and documents. The mechanics of handling large quantities of qualitative data can range from physically sorting and storing slips of paper to using one of the several computer software programs that have been designed to aid in this task see Brown, , for a description of one of these programs.

Analysis begins with identification of the themes emerging from the raw data, a process sometimes referred to as "open coding" Strauss and Corbin, During open coding, the researcher must identify and tentatively name the conceptual categories into which the phenomena observed will be grouped. The goal is to create descriptive, multi-dimensional categories which form a preliminary framework for analysis. Words, phrases or events that appear to be similar can be grouped into the same category. These categories may be gradually modified or replaced during the subsequent stages of analysis that follow.

As the raw data are broken down into manageable chunks, the researcher must also devise an "audit trail"-that is, a scheme for identifying these data chunks according to their speaker and the context. The particular identifiers developed may or may not be used in the research report, but speakers are typically referred to in a manner that provides a sense of context see, for example, Brown, ; Duffee and Aikenhead, ; and Sours, Qualititative research reports are characterized by the use of "voice" in the text; that is, participant quotes that illustrate the themes being described.

The next stage of analysis involves re-examination of the categories identified to determine how they are linked, a complex process sometimes called "axial coding" Strauss and Corbin, The discrete categories identified in open coding are compared and combined in new ways as the researcher begins to assemble the "big picture.

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Therefore, causal events contributing to the phenomenon; descriptive details of the phenomenon itself; and the ramifications of the phenomenon under study must all be identified and explored. During axial coding the researcher is responsible for building a conceptual model and for determining whether sufficient data exists to support that interpretation.

Finally, the researcher must translate the conceptual model into the story line that will be read by others.

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Ideally, the research report will be a rich, tightly woven account that "closely approximates the reality it represents" Strauss and Corbin, , p. Many of the concerns surrounding the presentation of qualitative research reports are discussed in the section "Judging Qualitative Research" which follows. Although the stages of analysis are described here in a linear fashion, in practice they may occur simultaneously and repeatedly. During axial coding the researcher may determine that the initial categories identified must be revised, leading to re-examination of the raw data.

Additional data collection may occur at any point if the researcher uncovers gaps in the data.

Synthesizing Qualitative Research: Choosing the Right Approach (Key Concepts) Synthesizing Qualitative Research: Choosing the Right Approach (Key Concepts)
Synthesizing Qualitative Research: Choosing the Right Approach (Key Concepts) Synthesizing Qualitative Research: Choosing the Right Approach (Key Concepts)
Synthesizing Qualitative Research: Choosing the Right Approach (Key Concepts) Synthesizing Qualitative Research: Choosing the Right Approach (Key Concepts)
Synthesizing Qualitative Research: Choosing the Right Approach (Key Concepts) Synthesizing Qualitative Research: Choosing the Right Approach (Key Concepts)
Synthesizing Qualitative Research: Choosing the Right Approach (Key Concepts) Synthesizing Qualitative Research: Choosing the Right Approach (Key Concepts)
Synthesizing Qualitative Research: Choosing the Right Approach (Key Concepts) Synthesizing Qualitative Research: Choosing the Right Approach (Key Concepts)
Synthesizing Qualitative Research: Choosing the Right Approach (Key Concepts) Synthesizing Qualitative Research: Choosing the Right Approach (Key Concepts)
Synthesizing Qualitative Research: Choosing the Right Approach (Key Concepts) Synthesizing Qualitative Research: Choosing the Right Approach (Key Concepts)

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