Mills Chapter 06

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Mills
Action Research: A Guide for the Teacher Researcher, 5e
© 2014 Pearson Education, Inc. All rights reserved.
Action Research
Geoffrey E. Mills
Fifth Edition
© 2014, 2011, 2007, 2003, 2000
Pearson Education, Inc. All rights reserved.
A Guide for the Teacher Researcher

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Chapter 6
Data Analysis and Interpretation

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Ongoing Analysis & Reflection
 Is your research question still
answerable and worth answering?
 Are your data collection techniques
catching the kind of data you want
and filtering out unwanted data?
 Conduct interim analysis
 Avoid premature action

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Analysis & Interpretation
 Data analysis
 summary of data
 technique determined by type of
data
 Data interpretation
 finding meaning in the data

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Organizing Qualitative Data
 Reading/Memoing
 record initial thoughts
 Describing
 include context, actions,
interactions
 Classifying
 develop themes

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Data Analysis Techniques
 Identify themes
 work inductively
 Code surveys, interviews,
questionnaires
 try to find patterns, meaning
 Analyze interviews
 annotate and identify themes
 Ask key questions

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 Organizational review
 vision & mission, goals & objectives,
structure of organization, operation,
problems, issues, & concerns
 Develop a concept map
 Analyze antecedents, consequences
 identify causal relations

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 Concept map

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 Display findings
 matrixes, charts, concept maps,
graphs, figures, audiovisual media
 State what’s missing
 avoid making unwarranted assertions

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Choosing Analysis Software
 Are you analyzing large amounts of
data?
 Are you adequately trained?
 Do you have resources to purchase
a program?
 Do you plan to capture specific
quotes from a large database?

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Computer Software for Data
Analysis
 Handy, extremely fast labeling &
retrieval tools
 NVivo 9.0
complex data
 The Ethnograph v6
text files
 HyperRESEARCH 3.0
text, graphics, audio, video

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Preparing Quantitative Data
for Analysis
 Scoring procedures
 Tabulation and Coding Procedures

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Analyzing & Interpreting
Quantitative Data
 Descriptive statistics
 shorthand way of giving lots of
information about a range of
numbers
 count what counts!
 be careful not to over interpret

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Analyzing & Interpreting
Quantitative Data
 Descriptive statistics
 central tendency
mean (average)
median (middle)
mode (most frequent)
 variability
standard deviation (spread)

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Analysis in Mixed Methods
Designs

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Qualitative Data
Interpretation
 Extend the analysis
 raise questions
 note implications that might be
drawn, without actually drawing them
 Connect findings with personal
experience
 Seek advice of “critical” friends
 take time to build relationships

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Qualitative Data
Interpretation
 Contextualize findings in literature
 Turn to theory
 link to broader issues
 search for abstraction
 provide rationale, sense of meaning
 Know when to say “when”
 if you don’t feel comfortable offering
an interpretation, don’t!

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Sharing Interpretations Wisely
 Connect interpretations closely to
data and analysis
 Avoid being evangelical

Mills Chapter 06

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Mills Chapter 06