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Qualitative Analysis: Coding and Categorizing Philip Adu, Ph.D. Methodology Expert National Center for Academic & Dissertation Excellence (NCADE) The Chicago School of Professional Psychology

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  • Qualitative Analysis: Coding and Categorizing Philip Adu, Ph.D. Methodology Expert National Center for Academic & Dissertation Excellence (NCADE) The Chicago School of Professional Psychology
  • Outline Codes 1. 2. 3. 4. Reducing data Creating concepts Capturing essence Developing theory Categories Themes Theory 1. 2. 3. 4. 5. 6. 7. 8. 9. Meaning of coding Essence of coding Coding process Coding strategies/methods Research question and coding methods Coding cycles Memoing Researchers Influence Presenting findings (writing chapter 4)
  • Meaning of Coding Assigning labels to Data 1. Interview transcripts 2. Documents 3. Artifacts 4. Field notes A code is a word, phrase, or sentence that represents aspect(s) of a data or captures the essence or feature(s) of a data (Saldana, 2013)
  • Essence of coding 1. Reducing data Not losing the meaning of the data Capturing the significant ideas or issues 2. Understanding phenomenon 3. Developing construct Developing categories and themes Constructs/conceptual variables: [They] are the mental definitions of properties of events of objects that can vary. [They] are often expressed in general, theoretical, qualitative, or subjective terms Read more: Conceptual Variables - Constructs in Science 4. Developing theory (Hani, 2009; Saldana, 2013)
  • Coding Process Sorting Coding Synthesizing Theorizing Abstract or General Real or Particular Codes Categories Themes Theory (Saldana, 2013)
  • Coding Strategies/Methods Coding Sorting Synthesizing Theorizing First Cycle Coding methods 1. Attribute coding 2. Descriptive coding 3. Emotion coding 4. Evaluation coding 5. In Vivo coding 6. Magnitude coding 7. Narrative coding 8. Process coding 9. Values coding 10. Themeing data Post-Coding Techniques 1. Code Mapping 2. Code Landscaping 3. Operational Model Diagramming Second Cycle Coding Methods 1. 2. 3. 4. Pattern coding Focused coding Axial coding Theoretical coding Abstract or General (Saldana, 2013)
  • Types of Research Questions and Coding Methods Type of Research Question Ontological question Epistemological question Meaning Examples Coding Methods (1st Cycle Coding) Related to studying the nature of participants realities What is the nature of? What are the lived experiences of? What is it like being? Attribute Emotion In Vivo Narrative Process Values Themeing Related to knowing and an understanding of the phenomenon of interest How does? What does it mean to be? What factors influence? Descriptive Evaluation Magnitude Narrative Process Themeing (Saldana, 2013, p.61)
  • First Cycle Coding Methods Related to Ontological Research Questions Coding Methods Function Examples Attribute Coding features of research site(s), participant(s), and material(s) being studied Coding Participants age, gender, & educational level Emotion Coding Coding participants sentiments, feelings, reactions, excitements and sensations From participants viewpoint From researcher's standpoint In Vivo Coding Coding by using participants own words Never again Pay back time No mercy Value Coding Coding participants values [V], attitudes [A], and beliefs [B] (p. 268) [V] Education [A] Sense of uncertainty [B] Existence of discrimination Narrativ e coding Coding participants stories including their interaction with others and retelling them. They can be structured as follows: Hopelessness Anxiety Pessimism Denial (1)Abstract [summary], (2) Orientation [characters, setting & time] (3) Complicating action [response/reaction] (4) Evaluation [essence] (5) Results [consequence] (6) Coda [lessons & conclusion] (p. 133)
  • First Cycle Coding Methods Related to Epistemological Research Questions Coding Methods Functions Examples Descriptive coding Assigning topics to aspects of the data Normally nouns For social environments (p. 262) Churches, Schools, Playing ground, Banks, Public library, and Recycle bins Evaluation coding Assign[ing] judgments (p. 119) (-) Foreign to them (-) Not part of program planning (+) Sense of independence (+) Increase in family income (-) increase in domestic violence Magnitude coding Assigning intensity, frequency, direction, presence, or evaluative content to code(s) High, Moderate & low income Present & absent motivation More & less determined Process Coding Also called action coding Coding observable activity and/or conceptual action (p. 96) Walking Cooking breakfast Checking emails Making calls Enjoying music Reflecting Themeing data Using phrase or sentence to describe or capture the meaning of an aspect of a data Ability to take care of their children Ability to pay bills Ability to have time with their children (Saldana, 2013)
  • Post-Coding Techniques 1. Code Mapping 2. Code Landscaping 3. Operational Model Diagramming Code Mapping Thoughtful and systematic process of sorting codes into: Categories Themes/concepts Categories Codes Themes
  • Code Landscaping Visual display of participants transcripts Word counts = Font sizes = Font color Source: http://www.wordle.net/create
  • Operational Model Diagramming Illustrating the relationship among codes, categories themes, and/or concepts Cmap: http://ftp.ihmc.us/
  • Second Cycle Coding Methods Coding Methods Functions Pattern coding Examining initial codes Identifying trends, patterns, relationships Assigning labels (they could be categories or themes) Focused coding Identifying the most frequent or significant initial codes (p. 264) Building categories around them Axial coding Identifying core category (Core phenomenon) and related categories Examining the features and dimensions of categories Causal conditions Core phenomenon Strategies Intervening conditions Consequence (Creswell, 2013, p. 86) Theoretical or Selective coding Connecting the core category and related categories to create a storyline The narrative (proposition/theory) should explain a phenomenon (Saldana, 2013)
  • Memoing Personal reflections and impressions Data collection phase Documenting your thoughts about: What you are observing in the field Your interaction with participants Your experience during the data collection process Data Analysis phase Documenting your thoughts about: Data analysis process Codes and their respective meanings Relationship among codes, categories, and themes
  • Researchers Influence Factors influencing the data analysis process Background Beliefs and biases Interests Philosophical paradigm
  • Presenting Findings (in Chapter 4) Providing background information about participants or the observed (especially the first cycle coding: attribute coding) To better understand what they said or you observed Presenting the number of codes, categories and themes emerged Having a findings summary table (Findings at a glance Saldana, 2013, p. 254) Category or Theme Theme 1 Theme 2 Meaning Evidence from the data
  • Presenting Findings (in Chapter 4) Creating diagram to show the relationship between themes Systematically presenting the finding i. ii. iii. Stating the theme Describing what the theme stands for (i.e. meaning of the theme) Supporting the theme with an evidence from the data (e.g. Quote from participants) Showing how the findings address the research question(s)
  • Coding is like using Lego bricks to make an art: it always starts with using meaningless pieces of bricks to create meaningful piece of art ~Philip Adu By Nathan Sawaya
  • CAQDAS (Computer-Aided Qualitative Data Analysis Software) ATLAS.ti: www.atlasti.com MAXQDA: www.maxqda.com NVivo: www.qsrinternational.com HyperRESEARCH: http://www.researchware.com Nvivo: http://www.qsrinternational.com/products_nvivo.aspx QDA Miner: http://provalisresearch.com/ Qualrus: www.qualrus.com Transana: www.transana.org Weft QDA: www.pressure.to/qda/ (Saldana, 2013, p. 29)
  • References Creswell, J. W. (2013). Qualitative Inquiry and Research Design: Choosing Among Five Approaches (3rd). Thousand Oaks, CA: Sage. Hani (2009,January 20). Conceptual Variables. Retrieved from Explorable website: http://explorable.com/conceptual-variables Saldana, J. (2013). The coding manual for qualitative researchers. London: Sage