Evaluación en etapa de pre uso y resultados por categorías

Qualitative studies are chronically called “labor intensive,” but the details are rarely provided.

Here, too, we rely on our experience and that of colleagues.

Who will do the work, and how much time will it take? These innocent questions mask more complexity than you often expect. We’ve said that lone researchers, new or experienced, should find a critical friend, partner, mentor, or colleague who can supply alternative perspectives, support, and protection from bias. In studies that have more than one staff member, there will always be a diversity of experiences, backgrounds, and skills.

That complexity means that the social system of the project needs attention; it will not develop

That complexity means that the social system of the project needs attention; it will not develop automatically. It is crucial to build strong relationships with research partners or within larger staffs.

We’ve found it useful, for example, to devote plenty of the initial time to work on core issues (the conceptual framework, research questions, sampling) and to more general maintenance issues, such as hopes for and worries about the project, reports of “what else is happening in my life,” and procedural guidelines for joint work. Research teams are not built in a day. Take time deliberately for the start-up of the relationship between you and your research partner, or the functioning of the research team.

One other rule of thumb we’ve found useful: Avoid sharp senior–junior divisions of labor, such as having juniors do the fieldwork and the seniors do the analysis and writing. Senior people need to be directly involved in data collection in order to have a concrete feel of what the field setting is like.

You cannot be a principal investigator in a field study without spending time in the field. Junior people will function poorly as “hired hands.” Both need to be actively and mutually engaged in thinking about the project and the meaning of emergent findings.

At the start, people rarely have all the skills they need for a study. Allow for learning time on issues such as fluency with new software, use of a new coding method, or drawing data displays.

The time estimates we use look something like this: For each day of fieldwork, expect to spend

• 2 or 3 days processing field notes (writing them up, correcting, etc.) if audio or video

recordings are being transcribed, the multiple may run from 4 to 8, depending on the fineness of detail and the transcriber’s familiarity with the content;

• 1 or 2 days coding (depending on the fineness and complexity of the evolving scheme); and

• 1 or 2 days completing displays and writing (depending on the number and type of displays).

These are multipliers for a single case. In a multiple-case study, you (a) multiply by the number of cases, (b) consider what case analyses will be carried out and what the within-case and cross-case reports will look like, and (c) make a total-days estimation.

Closure and Transition

We’ve looked at substantive moves that serve to focus the collection of data and condensing it.

These moves include systematic conceptual frameworks of variables or concepts and their interrelationships, research questions that further define the inquiry, defining the core and parameters of a study through case definition, planning for within-case and multiple-case sampling, and creating instrumentation. All these moves serve both to constrain and to support analysis. All can be done inductively and developmentally in advance of data collection. Designs may be tight or loose. Such choices depend on not only your preferred research style but also the study’s topic and goals, available theory, and the researcher’s familiarity with the settings being studied.

Added design issues that make a big difference in analysis include how qualitative data may be linked with quantitative information from the same setting, and a series of nuts-and-bolts management issues. Careful decisions about which computer software to use for what purposes need to be made. A systematic plan for data management—storage and retrieval of everything from raw data to final study reports—is equally important. Building good colleague and staff relationships is essential, as is initial and recurring time planning.

In the next chapter, we will examine the more human dimensions of fieldwork and analysis through the perspectives of the participants and our ethical obligations to them.

Note

1. When we (Miles and Huberman) had the chance to collaborate on a major field study, we leaped at it. The project was a study of the dissemination of educational innovations carried out during 1979–1983. Many of the examples in this text come from that study. (More detailed information appears in the first and second editions of this book.)

The study was nested in a larger study of school improvement, covering 145 school buildings and nearly 4,000 people throughout the United States involved in the implementation of educational innovations. Joined by two colleagues, Beverly Loy Taylor and Jo Anne Goldberg, we repeatedly visited a stratified sample of 12 field sites across the country throughout the 1979–1980 school year, with follow-up contacts the next year to verify the main findings.

The volume of data collected included 440 interviews, 85 observations, some 259 documents, and 2,713 pages of transcribed field notes. Interview and observation notes were dictated and transcribed. We developed a common set of data displays and, for each of the 12 field sites, used them to draw conclusions, resulting in a case report ranging from 70 to 140 pages, with a common format. Our subsequent cross-case analysis was built from the appropriate sections of the 12 case reports. In a second multiple-case field study, we replicated many of the techniques for collecting, condensing, and analyzing qualitative data from the school improvement study, finding that they

“traveled” quite well.

In the course of the cross-case analysis, we began another study, sponsored by the National Institute of Education. The task was to document the procedures we used for analyses, from the initial coding of site-level notes to the more explanatory cross-case analyses. Each analysis fed into a detailed self-documentation form; this exercise provided many of the illustrations and rules of thumb in the present book. We learned a great deal through teaching seminars in the United States, Canada, Western Europe, and Australia. The generic issues of qualitative data analysis become clearer as they are confronted not only across researchers but across cultures.

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