Our Cycle

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Our Cycle
Observe
Power Points
Create an Intervention
Focus
Data Analysis
Literature Review
Data Collection select/ develop collect
data
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What does it all mean?
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5 Data Analysis
Analysis means to break things down or add
things up so they can be understood. In action
research we analyze and organize our data so we
and others can understand the reality of what is
gong on.
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The ultimate goal of Action Research is to make
data based decisions - to see what is happening
by using data. Data tell us if our initial
ideas (hunches) were right/wrong, and it leads
us to where to look for effective change.
Data tells us what path we need to take
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Ways to Analyze Your Data
Identify themes Code Collate Concept
map Categorize - number - effect
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Analyzing Data
You can use quantitative or qualitative
analysis
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To analyze quantitative data Look at the data
and explain them in quantity (numbers and
statistics) Describe your findings with clear
concise facts graphs - visuals work
well Percents - 50 of the students agreed
that The average score on the test was His
report card grade was 95 On a Standardized test
her G.E. score was 4.5 The running record
showed This type of analysis is typically
numerical, clear, and straightforward
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Ways to Visually Display Your Data
Mills Appendix C page 209
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Thought Bubble Picture
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Math Face and Math Bubble Crosstabulation
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Another way look at the data qualitatively
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To analyze qualitative data (interviews,
observations, etc.) Analyze carefully. Look for
patterns, themes, categories, inconsistencies, or
paradoxes that emerge. It can take much sifting,
sorting, categorizing, close reading, and
decision making.
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Describe your findings with thick description and
illustrations QUOTES, WORK SAMPLES, PICTURES
help describe the way things are Be clear,
explain it richly and provide examples - in
other words Analyze long enough and deep
enough - help others see what you found
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No matter how you analyze your data (quant or
qual)
Just as you wanted your data collection
methods to be reliable and valid - you want the
same for your analysis. Credible - valid -
analysis/conclusions are trustworthy - we can
believe your conclusions Dependable - reliable -
if you or someone else does it again the same
results will occur results are consistent
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To achieve credibility put aside your
assumptions and listen to the data - the voices
of the children, teachers, in your study.
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The Story by William V. Haney
After the businessman turned off the lights in
the store when a man appeared and demanded money.
The owner opened a cash register. The contents of
the cash register were scooped up and the man
sped away. A member of the police force was
notified immediately. Take the Test
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Uncritical Inference Test
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• What does the Uncritical Inference test tell us?
• We approach situations ready to use our
  assumptions to help us make sense and to help us
  see what is going on. That is not a bad thing
  but as researchers we
• are using our assumptions - we
• have certain biases
• need to be aware that many of our biases
• are so ingrained they have gone
• underground
• We need to take these ideas into account when we
  analyze our data.

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How do we put aside our assumptions?
Our goal is to be honest, to find ways to bring
our biases and assumptions to the surface
(triangualtion, critical friends - member checks,
theory) Read and reread Listen and
relisten Watch and rewatch If we use these we
can guard against biases and unwarranted
assumptions
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Credibility and dependability can come from
triangulation
see
say
do