Tag Archive | coding

Saldana: Introduction to Codes and Coding p. 1-15 (Allison)

Jul12

Codes are ways to discover, identify and label repeated evidence collected from qualitative data: surveys, interviews, observations, focus groups, etc.

Saldana states, “The is no ‘best’ way to code…” and advocates a Pragmatist Paradigm of the “right tool for the right job” (Saldana, 2008 p. 2).

29 Coding methods: a few examples (states rarely are all used, even throughout a career).

Descriptive Code: summarizes the primary topic of an excerpt.

In Vivo Code: taken directly from the participant and is indicated by quotes.

Initial Coding: an open-ended process, where first impressions are recorded

Process Code: a word or phrase that captures action

Simultaneous Coding: two or more codes within a single datum

Methods:

First Cycle: the first pass when reviewing data, a single word or phrase can be used

Second Cycle: revisit the passages and edit, reword, or regroup

Decoding: decipher the core meaning(s) from a passage

Encoding: labeling the passage

Recognizing patterns:

Patterns: have various forms

similarity

difference

frequency

sequence

correspondence

causation

Filters: how one perceives, documents and codes the data

Codifying & Categorizing: creating a systematic arrangement, even if one category might be labeled “differences”

Recoding and recategorizing: Repeat first and second cycle, are they any changes? Codes, themes, groups and categories may change

Toward Theory

As the categories, subcategories and concepts become evident, they can begin to be related to theory. Layer upon layer can be found and built upon each other.

Code vs Theme: A theme is an outcome of a coding, categorizing, and analytic reflection.

What to code? Depends…

Life happens at four coordinates: participants, activities, time, and place

screenshot

Units of social organization

  1. Cultural practices
  2. Episodes
  3. Encounters
  4. Roles
  5. Social and personal relationships
  6. Groups and Cliques
  7. Organizations
  8. Settlements and habitats
  9. Subcultures and lifestyles

Questions to consider:

  1. What coding method(s) is appropriate for your study?
  2. What method(s) have you used so far?
  3. What kinds of questions to ask that do not narrow the answer of the participant?
  4.  What is involved in the First cycle and when does one begin the Second Cycle?
  5. What is the rationale for recoding and recategorizing?
  6. How does the researcher find the emergent themes and connect them to a theory?

Chapter 9 – Coding, Memoing, and Descriptions (Bailey, 2006)

Jul9

A Guide to Qualitative Research

Bailey (2006)

Chapter 9 – Coding, Memoing, and Descriptions

Tammara Sherman

EDL 507

Coding, Memoing, and descriptions are components of qualitative data analysis. Actually, the analysis of the data begins from the onset and continues throughout the project. Once the researcher leaves the field, the arduous task of making sense of the data, breaking it down, studying its components, and investigating its importance, and interpreting its meanings begins. According to Lofland and Lofland (1984), this arduous task can take 2 to 5 times longer than the amount time taken to collect the data.  In comparison, quantitative data is analyzed using software, such as SPSS. The researcher performs statistical tests and procedures, such as t-tests, ANOVAs, etc. on the data and then the researcher makes deductions about the data. Whereas in qualitative analysis, the researcher reads pages of text multiple times, grouping and organizing the data throughout the successive reads.  At the conclusion, the researcher interprets the results based on their research questions.

Many strategies for analyzing qualitative data exist. Bailey (2006) covers 10 of these strategies.  In chapter 9, Bailey (2006) focuses on the Coding and Memoing strategies because they are essential to all qualitative data analysis strategies.

A. Coding

Bailey (2006) defines coding as the “process of organizing a large amount of data into smaller segments that, when needed, can be retrieved easily.” She distinguishes coding analysis from thematic analysis in that themes do not emerge from the data. She asserts that the themes appear at the interpretation of the researcher and the associated research questions. She describes two types of coding: initial coding and focused coding.

Initial Coding

  • Initial coding is also known as open coding.
  • During initial coding, the researcher reads and codes the data.
  • Only, the data that is relevant to the study purpose and research questions are coded.
  • An iterative process

 

Focused Coding

  • Focus coding is also known as axial coding.
  • Typically, it occurs after the initial or open coding.
  • Involves grouping coded text into larger segments which encompasses the smaller segments
  • An iterative process

Strategies for Improving Coding

  • Make connections to “research on the topic, concerns of the researcher’s discipline, or theoretical concepts”
  • Begin the process by being well grounded in the discipline
  • Read the academic literature in the area being studied
  • Discuss the research finding with other people, who are knowledgeable in the area of study or are willing to listen, exercising care not to violate the confidentiality of the study participants

 

B. Memoing

  • Writing notes to oneself regarding the coding, including reflections on the data
  • Notes could include attempts to operationalize definitions, questions, posing hypotheses, and answers revealed in the data.
  • Facilitates coding at a higher conceptual level
  • Data from this process can be used for subsequent analysis
  • An iterative process

C. Qualitative Analysis Software

Numerous software packages exist that can assist with qualitative analysis. These software packages are tools and do not replace the skill necessary to inform the study or elicit information from the data.  A researcher may choose to use software for many reasons.

Reasons for using software

  1. Taking notes in the field
  2. Transcribing or writing up field notes
  3. Editing
  4. Coding
  5. Storage
  6. Search and retrieval
  7. Linking data
  8. Memoing
  9. Content analysis (counting frequencies, sequencing and locating words or phrases)
  10. Data visualization
  11. Drawing conclusions
  12. Building theory
  13. Creating diagrams
  14. Preparing interim and final reports (p. 134)

Qualitative Software

Atlas.ti, HyperRESEARCH, MAXqda2, NVivo, N6, CDC EZ-text, Qualrus, QDA Miner, and Ethnograph

Manual vs. Software

Some researchers prefer traditional methods for analyzing qualitative data. In this case, these researchers may:

  • Print, cut, and past hard copies of the data and code it with colored pencils or highlighters
  • Use word processing software, such as MS Word, or spreadsheet software, such as MS Excel to code data
  • Use adhesive notes, such as 3M Post-Its, in different  colors to code

 

Trade-offs

  Manual Software
Learning Curve Minimal Depends on the software, can be steep
Cost Minimal Can be costly
Flexibility Limited Medium to High, depending on the features available
Functionality Limited, requires using other mediums or software Medium to High, depending on the features available

D. Descriptions

Descriptions facilitate contextualizing the data. It involves recording detailed descriptions of the setting, interactions, and observations over the duration of the study. They are likened to answering a “reporter’s questions.” As such, the descriptions should answer the 5 W’s (what, why, when, where, and who) and how. Suffice it to say, descriptions need not include every detail, such as every object in the room, but characteristics or qualities that visualize the concept being conveyed. Descriptions can be thick or thin as asserted by Geertz (1973). Additionally, descriptions should relate to the research questions.

Thick Descriptions

Thick descriptions provide concrete detail about a phenomenon or concept. They are a necessity for research in the field. They provide strong visual images for the reader to conceptualize the context or concept. An example of thick description is:

Ana is between 30 and 40. Her brown hair lies limp and greasy against her head.  Her eyes tend not to focus on any one thing. Her skin is riddled with pockmarks suggesting years of drug usage. She scratches her arms or head constantly.  Although the weather is cold, she is wearing a tube-top and shorts. She is shoe-less and her feet are covered with soot and grime.

 

Thin Descriptions

On the other hand, thin descriptions provide less detail.  For example,

Ana has brown hair and is in her thirties.

Research Questions

The decision to use descriptions should depend on the research questions. Some details may appear “sexy” or exciting but may not inform the study. In such case, those details should be omitted. The purpose of using thick or thin description to facilitate the visualization of the contextual complexity of the subject being studied.

Summary

Descriptions help the readers “see the participants and the setting.”  Thick descriptions are an important element of the final report. More importantly, it allows the readers to understand the importance of the concept within the context.

Discussion Questions

  1. How would you characterize coding, art or science, and why?
  2. What strategies would you use to improve your coding practices?
  3. How would you use research to inform your coding strategy?
  4. If you were learning how to code qualitative data, how would you begin?
  5. How would you use Memoing to inform your qualitative data analysis?

Key Terms

Term Definition
Axial Coding See focused coding
Coding Organizing data into smaller units that are retrieved easily, when needed
Descriptions Recording detailed descriptions of the setting, interactions, and observations over the duration of the study. Answer 5 W’s and How.
Focused Coding Process of grouping coded text into larger segments which encompasses smaller segments
Initial Coding Process of breaking up pages of text into smaller segments that can be grouped and used in the later stages of analysis
Memoing Writing notes to oneself regarding the coding, including reflections on the data
Open Coding See initial coding
Thick Descriptions Provide concrete details about a phenomenon or concept.
Thin Descriptions Provide detail about a phenomenon or concept with less detail

Coding

Aug11

Coding is Analysis

•Codes are tags or labels for assigning units of meaning to the descriptive or inferential information compiled

•It is the meaning that matters
•Codes are used to retrieve and organize the chunks of information, so you can quickly find, pull out, and cluster the segments relating to a particular topic

Four stages of analysis (Glaser and Strauss).

Stage Purpose
Codes Identifying anchors that allow the key points of the data to be gathered
Concepts Collections of codes of similar content that allows the data to be grouped
Categories Broad groups of similar concepts that are used to generate a theory
Theory A collection of explanations that explain the subject of the research

Types of Codes (Miles & Huberman, 1994)

Descriptive: attributing a class of phenomena to a segment of text (e.g., room description) [INDEXING]

Interpretive: include a more complex, underlying meaning (e.g., roles)

Pattern: inferential and explanatory; group codes into a smaller number of themes or constructs; analogous to factor analysis in statistics (e.g., ideology) [CODING]

There are several key analytic strategies (Trochim)

Coding is a process for both categorizing qualitative data and for describing the implications and details of these categories. Initially one does open coding, considering the data in minute detail while developing some initial categories. Later, one moves to more selective coding where one systematically codes with respect to a core concept.

Memoing is a process for recording the thoughts and ideas of the researcher as they evolve throughout the study. You might think of memoing as extensive marginal notes and comments. Again, early in the process these memos tend to be very open while later on they tend to increasingly focus in on the core concept.

Integrative diagrams and sessions are used to pull all of the detail together, to help make sense of the data with respect to the emerging theory. The diagrams can be any form of graphic that is useful at that point in theory development. They might be concept maps or directed graphs or even simple cartoons that can act as summarizing devices. This integrative work is best done in group sessions where different members of the research team are able to interact and share ideas to increase insight.

-Saldana, J (2008) The Coding Manual for Qualitative Researchers. SAGE Publications, Chapter 1, located here: http://www.gobookee.net/get_book.php?u=aHR0cDovL3d3dy5zYWdlcHViLmNvbS91cG0tZGF0YS8yNDYxNF8wMV9TYWxkYW5hX0NoXzAxLnBkZgpBbkludHJvZHVjdGlvbnRvQ29kZXNhbmRDb2RpbmcgLSBTQUdFIC0gdGhlIG5hdHVyYWwgaG9tZSBmb3IgLi4u

AnIntroductiontoCodesandCoding – SAGE – the…