Data Analysis by Jiayi Zeng

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Transcript of Data Analysis by Jiayi Zeng

Making sense of things – Analysing data

Jiayi Zeng – with help from Johanna Höffken, and Crang & Cook (Ch. 8)

Development research surgeries at TU/e, session 3 – 03/10/2016

BackgroundFieldwork/internship•India (4 months)•Gridconnection micro Power plant•Interviews stakeholders

Analysis•Do it back home •Really exciting part

Panic – looking for order in the chaos

In general• Literature For example: Crang&Cook – doing ethnography Creswell – Research design And many more…

• Doing Enthnography, M. Crang & I. Cook, 2007 (chapter 8) - Preliminary work- Developing code - Shifting & sorting and making sense of it all

Premilinary work: What do I have?

interviewsCase document & Photos

Research diaries

Observation notes

Make word processed copies with a wide right margin

Play back the interviews- Missed sentences in transcription - Emotional flavour (emphasize on words, laughter)

Go through the other materials

Tip: keep a notebook with you/ use your phone -> you might think about it day & night

Developing codes

• Keep a notebook to note down insights and hunches while working through the materials

• Let the data guide you! (Be open minded, dont stick too much to your RQ)

• Highlight interesting part

• Write down what it is about

• Try to look for patterns and themes

What I did:

• Categories – emotions/facts/challenges/rest • When I came across a new topic/possible

code, I would write it down in the margin and on a note.

• Try to look for patterns.

An example‘they [the funders] were telling that replicability should be there’

‘In Nepal, so many similar projects are happening, micro hydro projects. They face the similar challenge of grid extension’

‘It is really challenging job, but work is waiting for you, if you can do this, already some demand has come for this technology.’

-> dissemination/upscale potential

Jiayi Zeng
de voorbeelden moet iets duidelijker, specifieker

Levels of code

• Involvement local community (empowerment activities, help with transportation)

• Lack of competent people (‘they are illiterate’, ‘there are no electricians’)

• Role of the operator (‘we will train someone from local community’, ‘this system might be complex for the operator’)

-> social challenges -> Challenges

What I did:

Summarizing the patterns

Shifting & sorting, and making sense of it all

An example:

Contradictions in your data

• Complex and simple project. • Local community is perceived as poor and will

not say too much but they did ask for more stable electricity access.

-> shifting & sorting -> I still have to deal with this.

To be continued

• I have been doing this for 2 weeks• More time is needed• Iterative process