Pre-finals

• "Any Researchers who desires to become expert at doing qualitative analysis must learn to code well and easily. The quality of the researchers rests largely on the excellence of Coding" Strauss (1987)
• Qualitative Data Analysis

  1. Transcribing
  2. Coding
  3. Categorizing
  4. Formulating Themes
  5. Data verification
• Transcription - involves close observations of data through repeated careful listening (and/or watching), and this is an important first step in Data Analysis.
• Code - Identifying concepts from collected (raw) data
• Coding Concepts:

  1. Descriptive Coding
  2. Process Coding
  3. In Vivo Coding
  4. Pattern Coding
  5. Simultaneous Coding
• Descriptive Coding - summarizes that primary topic of excerpt
• Process Coding - a word or phrase that captures action
• In Vivo Coding - using the participant's own language
• Pattern Coding - coding for patterns in the data
• Simultaneous Coding - applying multiple codes to the same text
• Categorizing - linking codes to create a unit or a category
• Pattern - Identifying repeated units (a pattern from categories)
• Themes - generated when similar issues and ideas expressed by participants within qualitative data are brought together by researcher into a single category or cluster
• Process in Qualitative Analysis

  1. Know your data
  2. Focus your analysis
  3. Do coding
  4. Clean your data
  5. Identify meaningful patterns and themes
  6. Interpret your data
• Conclusion - the aim is to intergrade them to come up a comprehensive, logical, and smart answer or explanation or the research question
• Conclusion - Inferences, deductions, abstractions, implications, interpretations, general statements and/or generalizations based upon the finding. It should also answer the questions that was raised in the first part of the research
• Recommendation - a suggestion that improves the study for future research to be conducted on the field