Making Sense of It All: Analyzing Qualitative Data
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Transcript of Making Sense of It All: Analyzing Qualitative Data
Making Sense of It All: Analyzing Qualitative Data
Presenters: George Hayhoe & James Conklin
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Our purpose today
• To briefly define qualitative research and provide examples of qualitative methods
• To focus on a technique called content analysis and its value in analyzing qualitative data
• To do the above in a highly interactive and participative manner
Session Agenda• Theory review (definitions, background, common
uses)
• Capturing data
• Organizing and analyzing data
• Small team workshop
• Comparison of results
• Q&A
Session Agenda• Theory review (definition, background, common
uses)
• Capturing data
• Organizing and analyzing data
• Small team workshop
• Comparison of results
• Q&A
Qualitative research• A technique for gathering information about
practices, attitudes, interests, and other human behavior that cannot be easily quantified
• Types of qualitative data– interview or focus-group transcripts– workplace artifacts or other types of documents– responses to questionnaires and open-ended
surveys, etc.– journals, diaries, or logs
The data can be used to ...• Provide input into a decision
• Provide guidance for the development of a product or program
• Offer insights into important issues—customer or employee satisfaction, strategic planning, morale, technical literacy, productivity barriers, training or information needs, quality improvement plans, policy formation ...
Session Agenda• Theory review (definitions, background, common
uses)
• Capturing data
• Organizing and analyzing data
• Small team workshop
• Comparison of results
• Q&A
Capturing data
• If possible, use more than one method• Common data-capture techniques:– Memory– Field notes (pen and paper)– Flipcharts– Transcript of online discussions, e-mails, etc.– Video or audio recording– Paper or electronic copies of documents
Session Agenda• Theory review (definitions, background, common
uses)
• Capturing data
• Organizing and analyzing data
• Small team workshop
• Comparison of results
• Q&A
The Analysis Process, 11. Familiarize yourself with the data
2. Focus your analysis
• By question, topic, time period, or event
• By case, individual, or group
3. Categorize the information
• Identify topics, themes, or patterns
• Organize them into preset or emergent categories
The Analysis Process, 24. Identify patterns and connections within and
between categories
• Summarize or compare data within categories
• Create super categories that combine categories
• Count the number of times a category is mentioned or the number of individuals who mention it
• Discover relationships between categories
5. Interpret the data, attaching meaning and significance to the analysis
Organization Strategies1. Does the excerpt fit an existing topic?– If yes, go to 3.– If no, go to 2.
2. Does the excerpt fit a new topic?– If yes, create the topic and move the excerpt into it.– If no, go to 3.
3. Does excerpt say something important about the topic?– If yes, tape to newsprint page for the appropriate topic.– If no, set aside.
• Is the excerpt like something that you have already seen?– If yes, start grouping like excerpts, making categories of like
things.– If no, start a separate group.
Alternative techniques• Use a program such as The Ethnograph or NUD*IST to
code documents• Use Word to code documents– Code passages using the indexing function– Create index and copy into new document– Shift to Outline view and create categories tagged Heading
3– Cut and paste index entries under categories– Create Heading 2 categories and roll up Heading 3
categories under them– If needed, create Heading 1 categories and roll up Heading
2 categories under them
Session Agenda• Theory review (definitions, background, common
uses)
• Capturing data
• Organizing and analyzing data
• Small team workshop
• Comparison of results
• Q&A
Now let’s do a quick exercise in data analysis.
First quickly read the Sample Data handout individually.
Then let’s brainstorm in small groups to determine several common themes repeated in the data supplied there.
Session Agenda• Theory review (definitions, background, common
uses)
• Capturing data
• Organizing and analyzing data
• Small team workshop
• Comparison of results
• Q&A