About: Grounded theory is a research topic. Over the lifetime, 22046 publications have been published within this topic receiving 1060622 citations.
Papers published on a yearly basis
12 Oct 2017
TL;DR: The Discovery of Grounded Theory as mentioned in this paper is a book about the discovery of grounded theories from data, both substantive and formal, which is a major task confronting sociologists and is understandable to both experts and laymen.
Abstract: Most writing on sociological method has been concerned with how accurate facts can be obtained and how theory can thereby be more rigorously tested. In The Discovery of Grounded Theory, Barney Glaser and Anselm Strauss address the equally Important enterprise of how the discovery of theory from data--systematically obtained and analyzed in social research--can be furthered. The discovery of theory from data--grounded theory--is a major task confronting sociology, for such a theory fits empirical situations, and is understandable to sociologists and laymen alike. Most important, it provides relevant predictions, explanations, interpretations, and applications. In Part I of the book, "Generation Theory by Comparative Analysis," the authors present a strategy whereby sociologists can facilitate the discovery of grounded theory, both substantive and formal. This strategy involves the systematic choice and study of several comparison groups. In Part II, The Flexible Use of Data," the generation of theory from qualitative, especially documentary, and quantitative data Is considered. In Part III, "Implications of Grounded Theory," Glaser and Strauss examine the credibility of grounded theory. The Discovery of Grounded Theory is directed toward improving social scientists' capacity for generating theory that will be relevant to their research. While aimed primarily at sociologists, it will be useful to anyone Interested In studying social phenomena--political, educational, economic, industrial-- especially If their studies are based on qualitative data.
12 Jan 1994
TL;DR: This book presents a step-by-step guide to making the research results presented in reports, slideshows, posters, and data visualizations more interesting, and describes how coding initiates qualitative data analysis.
Abstract: Matthew B. Miles, Qualitative Data Analysis A Methods Sourcebook, Third Edition. The Third Edition of Miles & Huberman's classic research methods text is updated and streamlined by Johnny Saldana, 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 Saldana'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. Johnny Saldana, The Coding Manual for Qualitative Researchers, Second Edition. The Second Edition of Johnny Saldana's international bestseller provides an in-depth guide to the multiple approaches available for coding qualitative data. Fully up-to-date, it includes new chapters, more coding techniques and an additional glossary. Clear, practical and authoritative, the book: describes how coding initiates qualitative data analysis; demonstrates the writing of analytic memos; discusses available analytic software; suggests how best to use the book for particular studies. In total, 32 coding methods are profiled that can be applied to a range of research genres from grounded theory to phenomenology to narrative inquiry. For each approach, Saldana discusses the method's origins, a description of the method, practical applications, and a clearly illustrated example with analytic follow-up. A unique and invaluable reference for students, teachers, and practitioners of qualitative inquiry, this book is essential reading across the social sciences. Stephanie D. H. Evergreen, Presenting Data Effectively Communicating Your Findings for Maximum Impact. This is a step-by-step guide to making the research results presented in reports, slideshows, posters, and data visualizations more interesting. Written in an easy, accessible manner, Presenting Data Effectively provides guiding principles for designing data presentations so that they are more likely to be heard, remembered, and used. The guidance in the book stems from the author's extensive study of research reporting, a solid review of the literature in graphic design and related fields, and the input of a panel of graphic design experts. Those concepts are then translated into language relevant to students, researchers, evaluators, and non-profit workers - anyone in a position to have to report on data to an outside audience. The book guides the reader through design choices related to four primary areas: graphics, type, color, and arrangement. As a result, readers can present data more effectively, with the clarity and professionalism that best represents their work.
01 Jan 1998
TL;DR: Theoretical Foundations and Practical Considerations for Getting Started and Techniques for Achieving Theoretical Integration are presented.
Abstract: Part I: Introduction to Grounded Theory of Anselm Strauss Chapter 1: Inspiration and Background Chapter 2: Theoretical Foundations Chapter 3: Practical Considerations for Getting Started Chapter 4: Prelude to Analysis Chapter 5: Strategies for Qualitative Data Analysis Chapter 6: Memos and Diagrams Chapter 7: Theoretical Sampling Chapter 8: Context Chapter 9: Process Chapter 10: Techniques for Achieving Theoretical Integration Chapter 11: The Use of Computer Programs in Qualitative Data Analysis Part II: Research Demonstration Project Chapter 12 Open Coding: Identifying Concepts Chapter 13: Developing Concepts in Terms of Their Properties and Dimensions Chapter 14: Analyzing Data for Context Chapter 15: Bringing Process Into the Analysis Chapter 16: Integrating Categories Part III: Finishing the Research Project Chapter 17: Writing Theses, Monographs, and Dissertations, and Giving Talks About Your Research Chapter 18: Criteria for Evaluation Chapter 19: Student Questions and Answers
01 Jan 2008
TL;DR: In this paper, the authors present strategies for qualitative data analysis, including context, process and theoretical integration, and provide a criterion for evaluation of these strategies and answers to student questions and answers.
Abstract: Introduction -- Practical considerations -- Prelude to analysis -- Strategies for qualitative data analysis -- Introduction to context, process and theoretical integration -- Memos and diagrams -- Theoretical sampling -- Analyzing data for concepts -- Elaborating the analysis -- Analyzing data for context -- Bringing process into the analysis -- Integrating around a concept -- Writing theses, monographs, and giving talks -- Criterion for evaluation -- Student questions and answers to these.
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