1. Data Analysis

2. Data analysis in the research process
Values,
world view
Value claims
Research
question
Epistemology
Knowledge claims
Research
review
Discussion
Interpretations
explanations
Theories
Concepts
Results
External
validity
Episte-
mological
lens
Method
Findings
Data
analysis
Research
design
Constructs,
variables
Records
Internal
validity
Investi-
gative
lens
Observed events
and objects
Data
collection

3. Qualitative Data Analysis
How to make sense of the “raw information”
Material is unstructured: interviews, field notes, documents, photographs...
Want to find patterns and explanations, while retaining sense of original accounts and observations
What does it all mean?
Fundamental tasks are: defining, categorising, mapping, exploring, explaining, theorising...
Will it help you to use a software package, such as Atlas TI?
Yes, it will help you to keep track of data
No, it will not do the analysis for you

4. Qualitative Data Analysis: Miles and Huberman
Data Collection
Data Display
Data Reduction
Conclusions: drawing/verifying

5. Data Reduction Ladder of Analytical Abstraction
3. Identifying patterns and
proposing explanations
2. Identifying themes and
trends
1. Summarizing interviews
and technical documents
Climbing the ladder is a
process of transformation.
From a validity perspective
each step constitutes a threat
After Carney (1990), Miles and Huberman (1994)

6. Data Reduction Ladder of Analytical Abstraction

7. Key tool: Data Displays
Display: A visual format that presents information systematically, in to order to help the researcher to identify findings.
”You know what you display” (p. 91.)
Viewing the condensed ”full data set” in one view
It is creative and fun to make good data displays!
They are also very useful in publications

8. Display types: Tables (data matrix)
Topic
Informant A
Informant B
Informant C
Informant D 1 2 3 4 5 6
7..

9. Display types: Tables
Orlikowski, 1993, CASE Tools as Organizational Change: Investigating Incremental and Radical Changes in Systems Development, MISQ 17(3)

10. Data dispays: Timelines
Moens, Broerse and Munders (2008). Evaluating a participatory approach to information and communication technology development: The case of education in Tanzania. International Journal of Education and Development using ICT, 4(4).

11. Data displays: Networks
SHEPPARD, B. & J. BROWN. " Meeting the challenge of information technology through educational partnerships: A case study ", International Electronic Journal for Leadership in Learning, 2(11), 1998.

12. Display types: Networks
This arrived by way of Stanley Wasserman at the SOCNET Listserv (from the International Network of Social Network Analysts) – The NYT’s Social Network analysis of who Academy Awards                                                         

13. Data displays: Process
Hagmann, J. R., E. Chuma, K. Murwira, M. Connolly, and P. Ficarelli Success factors in integrated natural resource management R&D: lessons from practice. Conservation Ecology 5(2): 29.

14. Data displays: Table of events and outcomes
Period
Implementation strategy
Actual use
User satisfaction
Individual impact
Organizational impact
Software Engineering
Medium
Low
Elephant Method
Team development
High
High (but variable)
Giraffe Project
Organization development
Variable
Medium (and variable)
Voluntary, individual use
Table 3: Summarizing the project, using DeLone and McLean's key concepts.
Bygstad, B. (2003) The Implementation Puzzle of CRM Systems in Knowledge Based Organizations. Information Resources Management Journal. Nov 2003.

15. Data displays: Explanations
Orlikowski, 1993, CASE Tools as Organizational Change: Investigating Incremental and Radical Changes in Systems Development, MISQ 17(3)

16. Java Application vs Browser
Source: Braa, Roland, Sanner

17. More examples from Miles & Huberman

18. Working with data displays
8. Suggest re-analysis
6. Integrate/elaborate
4. Suggest comparisons
2. Make sense
Display
Findings
1. Summarize
3. See themes/patters/clusters
5. Discover relationships
7. Develop explanations
After M&H fig 5.4

19. Til neste gang Lag 3 foiler: Motivasjon (real life problem) og scope
Forskningsspørsmål
Forskningsdesign