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Action Research Workshop Data Analysis
GI Group April 2011
Bendik BygstadInstitute of Informatics, UiO
Norwegian School of IT
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Data analysis in the research process
Observed events and objects
Constructs,variables
Concepts
Method
Theories
Epistemology
Values, world view
Records
Findings
Results
Interpretationsexplanations
Knowledge claims
Value claims
Research review
Research design
Datacollection
Dataanalysis
Discussion
Internal validity
External validity
Investi-gativelens
Episte-mologicallens
Researchquestion
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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
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Qualitative Data Analysis: Miles and Huberman
Data Collection
Data Display
Data Reduction
Conclusions: drawing/verifying
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Data ReductionLadder of Analytical Abstraction
3. Identifying patterns and proposing explanations
2. Identifying themes and trends
1. Summarizing interviews and technical documents
After Carney (1990), Miles and Huberman (1994)
Climbing the ladder is a process of transformation. From a validity perspective each step constitutes a threat
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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
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Display types: Tables (data matrix)
TopicInformant
AInformant
BInformant
CInformant
D
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7..
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Display types: Tables
Orlikowski, 1993, CASE Tools as Organizational Change: Investigating Incremental and Radical Changes in Systems Development, MISQ 17(3)
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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).
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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.
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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
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Data displays: Process
Hagmann, J. R., E. Chuma, K. Murwira, M. Connolly, and P. Ficarelli. 2002. Success factors in integrated natural resource management R&D: lessons from practice. Conservation Ecology 5(2): 29.
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Data displays:Table of events and outcomes
Period Implementation strategy
Actual use User satisfaction
Individual impact
Organizational impact
1993-94 Software Engineering Medium Low Low Low
1994-97Elephant Method
Team development
High High High High (but variable)
1995-98 Giraffe Project
Organization development
Medium Medium Variable Medium (and variable)
1998-2000 Voluntary, individual use
Medium Medium Variable Low
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.
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Data displays: Explanations
Orlikowski, 1993, CASE Tools as Organizational Change: Investigating Incremental and Radical Changes in Systems Development, MISQ 17(3)
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Working with data displays
After M&H fig 5.4
Display Findings
1. Summarize3. See themes/patters/clusters
5. Discover relationships7. Develop explanations
8. Suggest re-analysis6. Integrate/elaborate
4. Suggest comparisons2. Make sense