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Data analysis – qualitative data   presentation 2
 

Data analysis – qualitative data presentation 2

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    Data analysis – qualitative data   presentation 2 Data analysis – qualitative data presentation 2 Presentation Transcript

    • Qualitative Data Analysis (QDA) Presented by : Kartena Kontesta Binti Arifen 2011160899Nurul Yasmin Binti Mohamad Yusof 2011192333
    • The Nature of Qualitative Research• The term qualitative research refers to studies that investigate the quality of relationships, activities, or situations.• The natural setting is a direct source of data and the researcher is a key part of the instrumentation process.• Qualitative data are collected in the form of words or pictures and seldom involve numbers.
    • The Nature of Qualitative Research (Conti…)• Coding is the primary techniques used in data analysis.• Qualitative researchers are interested in how things occur and particularly in the perspectives of the subjects of a study.• Qualitative researchers, do not, usually, formulate a hypothesis beforehand and then seek to test it. Rather, they allow hypotheses to emerge as a study develops.
    • Techniques in Collecting Qualitative Data• Observation• Interviewing• Documents
    • What is Qualitative Data Analysis?• Qualitative Data Analysis (QDA) is the range of processes and procedures whereby we move from the qualitative data that have been collected into some form of explanation, understanding or interpretation of the people and situations we are investigating.
    • Observation• Observational data refer to the raw materials an observer collects from observations, interviews, and materials, such as reports, that others have created.• Data may be recorded in several ways: written notes, sketches, tape recordings, photographs, and videotapes.
    • What to look for when doingobservation?1.Physical setting.2. Activities.3. Human, social environment. The way in which human beings interact within the environment. This includes patterns of interactions, frequency of interactions, direction of communication patterns, decision-making patterns.4. Formal interactions.5. Informal interactions and unplanned activities.6. Nonverbal communication.
    • What are field notes?• Field notes refer to transcribed notes or the written account derived from data collected during observations and interviews.• There are many styles of field notes, but all field notes generally consist of two parts: • descriptive - in which the observer attempts to capture a word- picture of the setting, actions and conversations; • Reflective - in which the observer records thoughts, ideas, questions and concerns based on the observations and interviews.
    • Sample of Field Noteshttp://www.louisianafolklife.org/Resources/main_prog_models.html Sample Fieldnotes: Teen Memories of Grade School Traditions By Maida Owens, Louisiana Folklife Program These fieldnotes and interview transcript are provided for teachers and students as an example of how one folklorist took a research idea and developed it. It is difficult to predict exactly how a field project will develop, where ideas will come from, who will cooperate, and who wont. Teachers should note that fieldnotes are highly personal and vary among researchers. This format is similar to journaling and uses two-column, steno pad format.
    • Develop coding categories• A major step in analyzing qualitative data is coding speech into meaningful categories, enabling you to organize large amounts of text and discover patterns that would be difficult to detect by just reading observer commentary.• Always keep the original copy of observer commentary.
    • Develop coding categories(Conti…)• Next, conduct initial coding by generating numerous category codes as you read commentary, labeling data that are related without worrying about the variety of categories.• Write notes to yourself, listing ideas or diagramming relationships you notice. Because codes are not always mutually exclusive, a phrase or section might be assigned several codes.
    • Develop coding categories (Conti…)• Last, use focused coding to eliminate, combine, or subdivide coding categories and look for repeating ideas and larger themes that connect codes.• Repeating ideas are the same idea expressed by different respondents, while a theme is a larger topic that organizes or connects a group of repeating ideas.
    • Organizing Data for analysis
    • Developing your codes• Coding is a process for categorizing your data. Develop a set of codes using both codes that you predefine and ones that emerge from the data.• Predefined codes are categories and themes that you expect to see based on your prior knowledge.
    • Coding your data• Closely review and code your data. If possible, have more than one person code the data to allow for different perspectives on the data.• As you proceed you may find that your initial codes are too broad. Create subcategories of your codes as needed. Or you may find that you have created codes that are too detailed and that attempt to capture every possible idea. In that case consider how you can pull categories together into a broader idea.
    • Coding your data (Conti…)• Coding is a process of reducing the data into smaller groupings so they are more manageable.• The process also helps you to begin to see relationships between these categories and patterns of interaction.
    • Finding themes, patterns, and relationships• Step back from the detailed work of coding your data and look for the themes, patterns, and relationships that are emerging across your data.• Look for similarities and differences in different sets of data and see what different groups are saying.
    • Summarizing your data• After you have coded a set of data, such as transcripts of interviews with faculty or questionnaire responses, write a summary of what you are learning.• Similarly, summarize the key themes that emerge across a set of interview transcripts. When available, include quotations that illustrate the themes.• With your data coded and summarized you are ready to look across the various summaries and synthesize your findings across multiple data sources.
    • CONTENTANALYSIS
    • Content Analysis• An approach to identify repeated and consistent themes, images, metaphors, and other meaningful traits within documents and other communication media.• Refer to an analysis of the content of a communication.• It enables researchers to study human behavior in indirect way by analyzing communications.
    • Reasons conducting contentanalysis• To obtain descriptive information• To analyze observational and interview data• To test hypotheses• To check other research findings• To obtain information useful in dealing with educational problem
    • Steps involve in contentanalysis
    • Qualitative Data Collection• Rather than developing an instrument to use, the researcher itself is the instrument.• Collection of data: • Tape recorder • Videos • Photographic data• Interview must be transcribed.
    • Qualitative Data Analysis• The analysis is on going process.• During the organization of the data, researchers will read the data and get a sense of the whole.• The ways to interpret content analysis data are:4.Frequencies5.Coding to develop themes6.Computer analysis
    • Coding• A coding system tells how to distinguish the content from the medium.• Sections of text transcripts may be marked by the researcher in various ways (underlining in a colored pen, given a numerical reference, or bracketed with a textual code).• This section contains data which the researcher is interested in exploring and analysing further.• In the early stages of analysis, most if not all sections of the text will be marked and given different ‘codes’ depending on their content.• As the analysis progresses these codes will be refined or combined to form themes or categories of issues.
    • The Coding ProcessInitially readthrough text data Divide the text Label the segments into segments of information Reduce overlap of information with codes and redundancy Collapse codes into themes
    • Themes• A theme is generated when similar issues and ideas expressed by participants within qualitative data are brought together by the researcher into a single category or cluster.• This ‘theme’ may be labelled by a word or expression taken directly from the data or by one created by the researcher because it seems to best characterise the essence of what is being said.
    • Interviewer : What do you perceive as strengths of Greenfield as a community and how that relates to schools?Lucy : Well, I think Greenfield is a fairly close-knit community. I think people are interested in what goes on... We like to keep track of what our kids are doing, and feel a connection to them because of that. The downside of that perhaps is that kids can feel that we are looking TOO close....you said the health of the community itself is reflected in schools...I think... this is a pretty conservative community overall, and looked to make sure that what is being talked about in the school really carries out the community’s values.... “And I think there might be a tendency to hold back a little bit to much because of that idealisation of “you know, we learned the basics, the reading, the writing, and the arithmetic”). So you know, any change is threatening....sometimes that can get in the way of trying todo different things.Interviewer : In terms of looking at leadership strengths in the community, where does Greenfield set in continuum with planning process...forward thinking, visionary people...Lucy : I think there are people that have wonderful visionary skills. I would say that the community as a whole....would not reflect that...I think we have some incredibly talented people who become frustrated when they try to implement what they see as their...”
    • List of codes:1. Close-knit community2. Health of community; Category: community values The CommunityLook through your list of codes, and identify those that wouldinform this categories of ‘the community’. Then look backthrough the interview transcript and see if there are any otherreferences that you have missed.
    • Transcript
    • Discussion