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Evaluation Design Considerations when Using Qualitative Data Analysis Software

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Coded data into conceptual categories. Merged researcher codes for team review ... Code tree must shift/evolve with project. Code structure should not be stagnant ... – PowerPoint PPT presentation

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Title: Evaluation Design Considerations when Using Qualitative Data Analysis Software


1
Evaluation Design Considerations when Using
Qualitative Data Analysis Software
  • Dan Kaczynski, Ph.D.University of West
    Floridadkaczyns_at_uwf.edu

2
Types of Qualitative Data
3
Components of Data Analysisan interactive
model(Miles Huberman, 1994)
4
Approaches to Data Analysis
5
Approaches to Data Analysis
  • Whichever of these approaches are taken by
    researchers, they face a choice of using either
    manual and/or computer assisted methods in their
    data analysis.
  • (Welsh, 2002)

6
Qualitative Data Analysis Software (QDAS)
  • Facilitates efficient data management
  • Provides tools to strengthen rigor and
    credibility
  • Consistent use of code structures
  • Searchable layered inquiry
  • Enables methodological transparency
  • Supports simultaneous deduction and induction

7
How Evaluation Teams Used NVivo
  • Processed open-ended interviews, site documents,
    and field observations
  • Managed data sources and reports
  • Coded data into conceptual categories
  • Merged researcher codes for team review
  • Enhanced depth of analysis for reports

8
Example 1 Factors that Shaped Emergent Code
Structure
EvolvingProgram Model
EgalitarianTeam Management
Open AccessImmersion
Continuation of Funding Dependent upon Findings
9
Emergent Code Structure
10
Example 2 Factors that Shaped Predetermined Code
Structure
StructuredParticipation
HierarchicalTeam Management
RigidProgram Model
Continuation of Funding Dependent upon Findings
11
Predetermined Code Structure
12
Maintaining Consistencyand Allowing for
ExpandingCode Structure
13
Theory BuildingRelating raw data to findings
  • QDAS enables the evaluator to
  • Address complex questions through structured
    searches
  • Use data searches to generate and test theories
  • Explain meanings by explicitly connecting data

14
Design Strategies to Consider
  • Design should align with orientation
  • Code tree must shift/evolve with project
  • Code structure should not be stagnant
  • Team must consistently apply code meanings
  • Team members need software training

15
NVivo 7
16
NVivo 7 More Features
17
NVivo 7 Even More Features
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