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S'està carregant… Qualitative Data Analysis: An Expanded Sourcebook(2nd Edition) (edició 1994)de Matthew B. Miles, Michael Huberman
Informació de l'obraQualitative Data Analysis: An Expanded Sourcebook de Matthew B. Miles
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The Third Edition of Miles & Huberman′s classic research methods text is updated and streamlined by Johnny Saldaña, author of The Coding Manual for Qualitative Researchers. Several of the data display strategies from previous editions are now presented in re-envisioned and reorganized formats to enhance reader accessibility and comprehension. The Third Edition′s presentation of the fundamentals of research design and data management is followed by five distinct methods of analysis: exploring, describing, ordering, explaining, and predicting. Miles and Huberman′s original research studies are profiled and accompanied with new examples from Saldaña′s recent qualitative work. The book′s most celebrated chapter, "Drawing and Verifying Conclusions," is retained and revised, and the chapter on report writing has been greatly expanded, and is now called "Writing About Qualitative Research." Comprehensive and authoritative, Qualitative Data Analysis has been elegantly revised for a new generation of qualitative researchers. No s'han trobat descripcions de biblioteca. |
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Google Books — S'està carregant… GèneresClassificació Decimal de Dewey (DDC)300.723Social sciences Social Sciences; Sociology and anthropology Social sciences Education And Research Social sciences--research Social sciences--descriptive researchLCC (Clas. Bibl. Congrés EUA)ValoracióMitjana:
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This book seems to be the seminal work in its field. The authors share their wisdom and experiences in this accessible textbook, now in a fourth edition. They cover the entire process from design and data collection to building a theory. They talk at length about coding as well as how to present your data. They even have a chapter on writing, with many encouragements to not be boring!
The graphics and illustrations in this book are excellent and inspirational. I am always interested in creating visualizations to communicate research data effectively, and this book provided many muses in that regard. They talked about converting written accounts into concept maps and linking those to address “influences and affects” of a weak sort of causality. This book helped slow my mind down about the many moving parts in qualitative research so that I can focus more on a work’s reality and substance.
This book is obviously geared towards researchers, whether new or old. The writing and presentation are accessible enough so that graduate students would be well-served by reading this work. Practitioners, of course, can benefit as well, but they likely would have read one of the prior three editions of this book. Those who, like me, are involved in other parts of the research enterprise can learn about their colleagues’ work, too. Finally, those who spend significant time building visuals to communicate concepts can learn from these authors’ analytical techniques.
After finishing this work, I’m inspired about the myriad of ways non-quantitative data can be analyzed and concisely communicated to readers – especially in ways that aren’t written prose. Poetry, artful presentations, summarizing graphics, and matrix-tables together can create a mosaic to comport meaningful and accurate understanding to readers. My personal bar has been raised, and I suspect many other readers’ bars will be, too. ( )