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Merriam ch 8 5.26.10
 

Merriam ch 8 5.26.10

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    Merriam ch 8 5.26.10 Merriam ch 8 5.26.10 Presentation Transcript

    • Merriam Chapter 8 Qualitative Data Analysis Jeff Yund and Heather White
    • Beginning Analysis During Data Collection
      • Ten Helpful Suggestions:
      • Force yourself to make decisions that narrow the study.
      • “ You must discipline yourself not to pursue everything…or else you are likely to wind up with data too diffuse and inappropriate what you decide to do”
    • Beginning Analysis During Data Collection
      • Ten Helpful Suggestions:
      • Force yourselft to make decisions concerning the type of study you want to accomplish.
      • “ You should try to make clear in your own mind, for example, whether you want to do a full description of a setting or whether you are interested in generating theory about a particular aspect of it.”
    • Beginning Analysis During Data Collection
      • Ten Helpful Suggestions:
      • Develop Analytical Questions:
      • “ Some researches bring general questions to a study. These are important because they give focus to data and help organize it as you proceed.”
    • Beginning Analysis During Data Collection
      • Ten Helpful Suggestions:
      • Plan data collection sessions according to what you find in previous observations.
      • “ Review notes as you go along and plan to pursue specific leads in you next data-collection session.”
    • Beginning Analysis During Data Collection
      • Ten Helpful Suggestions:
      • Write many “observers comments” as you go.
      • “ The idea is to stimulate critical thinking about what you see and to become more than a recording machine.”
    • Beginning Analysis During Data Collection
      • Ten Helpful Suggestions:
      • 6. Write memos to yourself about what you are learning.
      • “ These memos can provide a time to reflect on issues raised in the setting and how they relate to larger theoretical, methodological, and substantive issues.”
    • Beginning Analysis During Data Collection
      • Ten Helpful Suggestions:
      • Try out ideas and themes on participants.
      • “ Ask what they think about some pattern or theme you are beginning to detect in the data…key informants, under appropriate circumstances, can help advance your analysis, especially fill in holes of description.”
    • Beginning Analysis During Data Collection
      • Ten Helpful Suggestions:
      • Begin exploring the literature while you are in the field.
      • “ After you have been in the field for a while, going through the substantive literature in the area you are studying will enhance analysis.”
    • Beginning Analysis During Data Collection
      • Ten Helpful Suggestions:
      • Pay with metaphors, analogies, and concepts.
      • “ Ask the question, What does this remind me of?”
    • Beginning Analysis During Data Collection
      • Ten Helpful Suggestions:
      • 10. Use visual devices.
      • “… can range from primitive doodling to sophisticated computer-generated models.”
    • Beginning Analysis During Data Collection
      • Key Questions for the researcher:
      • When should you stop data collection and begin intensive data analysis?
      • How do you know you have collected enough data?
    • Managing Your Data:
      • Coding: assigning shorthand designation so you can easily retrieve specific pieces of the data (words, letters, numbers, phrases, colors, or a combination of these).
      • Keep track of your thoughts, musings, speculations and hunches.
      • Create an inventory for your entire data set (organized and labeled according to an organizing scheme)
      • Keep an extra copy of your data
      • Use software to manage data or mix manual and computer management
    • How to Analyze Qualitative Data
      • The Step-By-Step Process of Analysis:
      • Category Construction:
        • Assigning codes to pieces of data is the way you begin to construct categories.
        • Compare codes from data sets to look for similar themes and recurring patterns.
      • Sorting Categories and Data
        • Some original categories will become subcategories
        • Sort all evidence for a theme into categories
      • Naming the Categories
        • Sources: researcher, participants, outside sources
    • How to Analyze Qualitative Data
      • Criteria for Categories : Categories should be…
      • responsive to the purpose of the research (categories are the answers to your research question)
      • exhaustive (enough categories to encompass all relevant data)
      • mutually exclusive: all relevant data can be placed in only one category)
      • as sensitive to the data as possible (the more exacting in capturing the meaning of the phenomenon the better)
      • Conceptually congruent (all categories on the same conceptual level)
    • How to Analyze Qualitative Data
      • How Many Categories?
      • The number should be manageable
      • Cresswell (2007, p.152) “reduce and combine them into the five or six themes that I will use to write my narrative.”
    • Levels of Data Analysis
      • Basic - Data is organized chronologically and presented in a descriptive narrative
      • Abstract - Uses concepts to describe phenomena
      • Inferential - Involves making inferences, developing models, or generating theories
    • Theorizing
      • “… is a step toward developing a theory that explains some aspect of practice or allows a researcher to draw inferences about future activity.” (Merriam, 2009, p. 188)
      • Making inferences or theorizing can be a difficult task for qualitative researchers
      • Many times, researchers are unable to shift into a speculative mode of thinking
    • Ongoing Challenges…
      • It is difficult to move from phenomenon to abstraction, from description of what occurred to interpretation, and from our need for linear, ordered statements of cause and effect.
    • Continuing Data Analysis
      • Researchers often find that category schemes do not tell the whole story and that there is more to be understood
      • This often leads to trying to link the categories together in a meaningful way
      • One of the most successful ways is to visualize how the categories work together is either by using a model or diagram
    • Visualizing the Categories
      • Models and diagrams are an effective way to capture the interaction or relatedness of how the categories/findings can be linked together in a meaningful way
      • See Exhibit 8.3 (page 190) for example
    • Computers & Qualitative Analysis
      • Excellent capacity for organizing massive amounts of data, facilitating analysis, and assisting in communication among members of a research team
    • What is CAQDAS?
      • CAQDAS stands for Computer Assisted Qualitative Data Analysis Software
      • This software assists in organizing and categorizing data
      • This software does not do the analysis for the researcher
      • There are a variety of computer software programs to assist in qualitative data analysis
    • Data Analysis & Types of Qualitative Research
      • Phenomenological Analysis
      • Grounded Theory
      • Ethnographic Analysis
      • Narrative Analysis
      • Case Studies
      • Content Analysis & Analytic Induction
    • Phenomenological Analysis
      • Attends to searching out the truth or basic structure of a phenomenon
      • Several techniques such as epoche, bracketing, phenomenological reduction, horizontalization, and so on are used to analyze this experience
    • Grounded Theory
      • The basic strategy of this method is to do just what the name implies – constantly compare
      • A grounded theory consists of categories, properties, and hypotheses
    • Ethnographic Analysis
      • Ethnographic studies focuses on the culture and social regularities of everyday life
      • Rich, thick description is a defining characteristic of this type of analysis
      • Ethnographic Analysis presents description, analysis, and interpretation
    • Narrative Analysis
      • The study of experience through stories
      • Emphasis is placed on stories people tell and how these stories are communicated
      • First person accounts of experiences written in narrative form
    • Case Studies
      • Intensive, holistic, description and analysis of a single bounded unit
      • Data is usually derived from interviews, observations, & documents
      • Attention to data management is particularly important
    • Content Analysis & Analytic Induction
      • Both techniques are lesson common
      • Content analysis- studies the content of communication
      • Analytic Induction- a systematic examination of similarities between various social phenomena in order to develop concepts or ideas
      • Analytic Induction has specific steps to guide process (see p. 206)