Data Analysis

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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Data ReductionLadder of Analytical Abstraction

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)

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TopicInformant

AInformant

BInformant

CInformant

D

1

2

3

4

5

6

7..

Display types: Tables

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

Data dispays: Timelines

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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).

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

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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                                                         

Data displays: Process

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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.

Data displays:Table of events and outcomes

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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.

Data displays: Explanations

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

Java Application vs Browser

Source: Braa, Roland, Sanner

More examples from Miles & Huberman

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

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Til neste gang

• Lag 3 foiler:– Motivasjon (real life problem) og scope– Forskningsspørsmål– Forskningsdesign