CHAPTER 20: Analizing and Interprating Data

Data analysis and interpretation: definition and purpose

involves

summarizing data

requieres

the researcher be patient and reflective

including

field notes

interviews, questionnaires, maps

is an attemp

find meaning in the data

are critical steps

explore every possible angle

techniques outlined

guideposts and prompts

Data analysis during data collection

the researcher

should try to narrow

topic

gathering data, examining data

answer two questions

Is your research question still answerable and worth answering?

Are your data collection techniques catching
the kind of data you want and filtering out
the data that you don’t want?

pausing during the research

allows you to reflect on what you are attending

avoid premature actions

Data analysis after data collection

researcher

examine each piece of information

starts with a large set of data

small and important groups of key data

constructs meaning by identifying patterns

. Avoid premature judgment.

Read and reread

watch and rewatch

Steps in analyzing Qualitative research data

Qualitative data analysis

is a cyclical, iterative process

three iterative steps

reading

memoing

describing

classifying research data

writing notes in the field note

thorough and comprehensive descriptions

Classifying small pieces

into general categories

make sense and find connections

Field notes and transcripts

small pieces of data

pieces are integrated into categories

more general patterns.

Data Analysis Strategies

Identifying themes

identification of ideas

from the review of literature

data collection

Coding

process of marking units

text with codes or labels

indicate

patterns and meaning in data

Asking key questions

seeking answers

organizational review

understand the school

vision and mission, goals and objectives

Concept mapping

create a visual display

identification of consistencies

Analyzing antecedents and consequences

map the causes and effects

Displaying findings

matrixes, charts, concept maps, graphs, etc

Stating what’s missing

reflect and identify any questions

computer programs are available

Data interpretation strategies

Data interpretation

connections, common aspects

Interpretation

cannot

be meaningfully accomplished

aim

answer four questions

What is important in the data?

Why is it important?

What can be learned from it?

So what?

Extending the analysis

data interpretation strategy

raises questions

study, noting implications

Connecting findings

personal experience

personalize interpretations

Contextualizing

findings of the study

related literature

Turning to theory

link their findings

increase levels of abstraction

Ensuring credibility in your study

check the credibility

researchers

ask themselves

Are the data based on one’s own observation or on hearsay?

Are observations corroborated by others?

In what circumstances was an observation made or reported?

How reliable are those providing the data?

What motivations may have influenced a participant’s report?

What biases may have influenced how an observation was made or reported?

YADIRA PILA 4TH "A"