Module D: Data analysis (Codes)
Iterative data: Easier than grounded theory, employs both inductive and
deductive logic. You are cycling between what you see in the data and
literature.
Steps for Iterative Qualitative Analysis:
1) Preparing raw data: Assign pseudonyms to names of specific people in
your data, organize the data in the order you plan to analyze:
- Chronologically
- By type (interview vs. observation)
- By source (employee vs. manager)
2) Primary cycle: Data immersion:
- Read interviews of teammates
- Laid backstage, start processing data.
- Discuss with teammates.
3) Create a codebook: Your codebook is your map to help you navigate
through your coded data.
4) Secondary Cycle Coding: Secondary cycle coding is in between deductive
and inductive. Organize, synthesize, and categorize your open codes into
interpretive concepts.
5) Revisit the scholarly literature.
6) Create relationships between the categories.
Codebook: Code instances and research questions Asses your codes against your
initial research question create definitions and choose an exemplar quote that
represents each code
The Turing machine: It is seen as a basis for modern computing; therefore,
computers are sometimes referred to as Turing Machines. Invented by Alan Turing in
1936 (called it an a-machine, automatic machine)
Two main ways in which computers can help:
1) Automating the (very old) processes of Indexing
2) Automating the (very old) processes of Cross-referencing
The query function lets you retrieve sections of the text that are associated with
codes that you have made. Means that you can gather all sections of your data that
you have associated with a particular code.
Hyperlinks: Used for electronic cross references. By pressing a button, the user of a
textual database can jump between the text passages which are linked together.
, Standard hyperlink relations:
- Continued by
- Contradicts
- Criticizes
- Discusses
- Expands
- Explains
- Justifies
- Supports
Human interpreter - hyperlink 3 steps:
1) Structuring: Structure material with the help of common-sense concepts or
abstract theoretical concepts.
2) First level coding: A systematic comparison of text passages; text
segments are retrieved and analyzed in order to discover dimensions which
can be used as a basis for comparing different cases.
3) Construction of concepts, types, and categories: Form the building blocks
of an emerging theory.
Tracy (2013); QRM
Open coding: Suggests that in these initial cycles you are trying to open up
meaning in the data.
Primary-cycle codes: Answer the question “what’s going on here?” –
providing a summary of data content.
Constant comparative method: Compares the data applicable to each code
and modify code definitions to fit new data, to make modifications in the
coding scheme and to create new codes.
Secondary-cycle coding: Researchers categorize first-level codes into larger
axial codes that serve as conceptual bins for emergent claims. They also
devise analytic codes that may employ disciplinary or theoretical concepts.
Prospective conjecture: When researchers consider novel theoretical
juxtapositions and borrow from other fields, models, and assumptions for
developing second-level codes.
Axial coding: The process of reassembling data that were fractured during
open coding, which can also be called hierarchical coding.
Hierarchical coding: Includes systematically grouping together various codes
under a hierarchical umbrella category that makes conceptual sense.
Iterative data: Easier than grounded theory, employs both inductive and
deductive logic. You are cycling between what you see in the data and
literature.
Steps for Iterative Qualitative Analysis:
1) Preparing raw data: Assign pseudonyms to names of specific people in
your data, organize the data in the order you plan to analyze:
- Chronologically
- By type (interview vs. observation)
- By source (employee vs. manager)
2) Primary cycle: Data immersion:
- Read interviews of teammates
- Laid backstage, start processing data.
- Discuss with teammates.
3) Create a codebook: Your codebook is your map to help you navigate
through your coded data.
4) Secondary Cycle Coding: Secondary cycle coding is in between deductive
and inductive. Organize, synthesize, and categorize your open codes into
interpretive concepts.
5) Revisit the scholarly literature.
6) Create relationships between the categories.
Codebook: Code instances and research questions Asses your codes against your
initial research question create definitions and choose an exemplar quote that
represents each code
The Turing machine: It is seen as a basis for modern computing; therefore,
computers are sometimes referred to as Turing Machines. Invented by Alan Turing in
1936 (called it an a-machine, automatic machine)
Two main ways in which computers can help:
1) Automating the (very old) processes of Indexing
2) Automating the (very old) processes of Cross-referencing
The query function lets you retrieve sections of the text that are associated with
codes that you have made. Means that you can gather all sections of your data that
you have associated with a particular code.
Hyperlinks: Used for electronic cross references. By pressing a button, the user of a
textual database can jump between the text passages which are linked together.
, Standard hyperlink relations:
- Continued by
- Contradicts
- Criticizes
- Discusses
- Expands
- Explains
- Justifies
- Supports
Human interpreter - hyperlink 3 steps:
1) Structuring: Structure material with the help of common-sense concepts or
abstract theoretical concepts.
2) First level coding: A systematic comparison of text passages; text
segments are retrieved and analyzed in order to discover dimensions which
can be used as a basis for comparing different cases.
3) Construction of concepts, types, and categories: Form the building blocks
of an emerging theory.
Tracy (2013); QRM
Open coding: Suggests that in these initial cycles you are trying to open up
meaning in the data.
Primary-cycle codes: Answer the question “what’s going on here?” –
providing a summary of data content.
Constant comparative method: Compares the data applicable to each code
and modify code definitions to fit new data, to make modifications in the
coding scheme and to create new codes.
Secondary-cycle coding: Researchers categorize first-level codes into larger
axial codes that serve as conceptual bins for emergent claims. They also
devise analytic codes that may employ disciplinary or theoretical concepts.
Prospective conjecture: When researchers consider novel theoretical
juxtapositions and borrow from other fields, models, and assumptions for
developing second-level codes.
Axial coding: The process of reassembling data that were fractured during
open coding, which can also be called hierarchical coding.
Hierarchical coding: Includes systematically grouping together various codes
under a hierarchical umbrella category that makes conceptual sense.
