Paulus, P. B., & Nijstad, B. A. (2003). Group creativity: Innovation through collaboration. Oxford: New York.
Miles, M. B., Huberman, A. M., & Saldana, J. (2013). Qualitative data analysis: A methods sourcebook (3rd edition). Thousand Oaks, CA: SAGE.
We strongly advise analysis concurrent with data collection. It helps the fieldworker cycle back and forth between thinking about the existing data and generating strategies for collecting new, often better, data. We advise interweaving data collection and analysis from the very start.
Data forms (focus on words):
The basic, raw data (scribbled field notes, recordings) must be processed before they are available for analysis. Field notes must be converted into expanded write-ups. Raw field notes may contain private abbreviations. They are also sketchy. A formal write-up usually will add back some of the missing content because the raw field notes stimulate the field-worker to remember things that happened at the time that are not in the notes. A write-up is an intelligible product for anyone. It can be read, edited for accuracy, commented on, coded, and analyzed .
First cycle coding-->second cycle or pattern codes-->the process of deriving even more general themes through jottings and analytic memoing-->assertion and proposition development.
Codes are labels that assign symbolic meaning to the descriptive or inferential information complied during a study. Codes usually are attached to data "chunks" of varying size and can take the form of a straightforward, descriptive label or a more evocative and complex one. Codes are primarily, but not exclusively, used to retrieve and categorize similar data chunks so the researcher can quickly find, pull out, and cluster the segments relating to a particular research question, hypothesis, construct, or theme. Clustering and the display of condensed chunks then set the stage for further analysis and drawing conclusions.
The conceptual frameworks and research questions are the best defense against overload of information. Codes are prompts or triggers for deeper reflection on the data's meanings. Coding is thus a data condensation task that enables you to retrieve the most meaningful material, to assemble chunks of data that go together, and to further condense the bulk into readily analyzable units.
Codes are first assigned to data chunks to detect reoccurring patterns. From these patterns, similar codes are clustered together to create a smaller number of categories or pattern codes. The interrelationships of the categories with each other then are constructed to develop higher level analytic meanings for assertion, proposition, hypothesis, and/or theory development.
There are 3 elemental methods that serve as foundation approaches to coding:
3 affective methods that tap into the more subjective experiences:
One literary and language method, dramaturgical coding, explores human action and interaction through strategic analysis of people's motives.
Dramaturgical coding: This method applies the terms and conventions of character, play script, and production analysis onto qualitative data. For character, these terms include items such as participant objectives (OBJ), conflicts (CON), tacitcs (TAC), attitudes (ATT), emotions (EMO), and subtexts (SUB). Dramaturgical coding is appropriate for exploring intrapersonal and interpersonal participant experiences and actions in case studies, power relationships, and the processes of human motives and agency.
3 exploratory methods, make preliminary or global coding assignments, based on what the researcher deductively assumes may be present in the data before they are analyzed.
2 procedural methods utilize specific rather than open-ended ways of coding data:
4 grammatical methods play a role in the mechanic of coding:
Whether codes are created and revised early or late is basically less important than whether they have some conceptual and structural unity. Codes should relate to one another in coherent, study-important ways; they should be part of a unified structure.
An operative coding scheme is not a catalog of disjointed descriptors but rather a conceptual web, including larger meanings and their constitutive characteristics. CAQDAS is especially helpful in displaying the structure of coding schemes, either in hierarchical form or in a network.
Saldana, J. (2012). The coding manual for qualitative researchers. Thousand Oaks, CA: SAGE.
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Main Library: LB 1028.5 S696 2006