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MTE 3113ACTION RESEARCH 1
(PRIMARY MATHEMATICS)METHODOLOGY
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Educational ResearchProcedure
1. Choosing a research problem2. Determining the research objective3. Determining the research questions4. Determining the research hypotheses5. Reviewing the literature6. Planning the research design7. Determining the sampling procedure8. Constructing the research instrument9. Constructing the validity and reliability
of the instrument10. Determining the data collection
procedure11. Collecting data12. Analyzing and interpreting the data13. Reporting the results and findings
Chapter 1 Introduction
Chapter 2 Lit. review
Chapter 3 Methodology
Chapter 4 Findings
Chapter 5 Conclusion
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Things arent always what we think!
Six blind men go to observe an elephant. One feels the side and thinks theelephant is like a wall. One feels the tusk and thinks the elephant is a like aspear. One touches the squirming trunk and thinks the elephant is like asnake. One feels the knee and thinks the elephant is like a tree. One
touches the ear, and thinks the elephant is like a fan. One grasps the tail andthinks it is like a rope. They argue long and loud and though each was partlyin the right, all were in the wrong.For a detailed version of this fable see:http://www.wordinfo.info/words/index/info/view_unit/1/?letter=B&spage=3
Blind men and an elephant
- Indian fable
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Analysis
Begins before you start thequalitative research,Continues (during data collection)
throughout the effort, unlike manyquantitative studies(After data collection) develop ideasand test them against yourobservations,modify ideas as you gather morematerial and reflect on it
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The Analysis Continuum
Raw DataDescriptiveStatements Interpretation
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General Principles
Inductive patterns emerge fromdata
Cyclical analysis moves back andforth between collecting andmanaging data, and drawingconclusions
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Analysis Considerations
1 Words2 Context (tone and inflection)3 Internal consistency (opinion shifts during groups)4 Frequency and intensity of comments (counting,
content analysis)5 Specificity6 Trends/themes7 Iteration (data collection and analysis is an iterative
process moving back and forth)
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The Procedures
Content analysis steps:1. Transcribe data (if audio taped)2. Read transcripts3. Highlight quotes and note why important4. Code quotes according to margin notes5. Sort quotes into coded groups (themes)
6. Interpret patterns in quotes7. Describe these patterns
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The Procedures
1 Coding/indexing2 Categorisation3 Abstraction4 Comparison5 Dimensionalisation6 Integration7 Iteration8 Refutation (subjecting inferences to scrutiny)
9 Interpretation (grasp of meaning - difficult to describeprocedurally)
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THEMES
A N A L Y
S I S
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Analytic Methods
Data collection
Data reduction
Data display
Drawing & verifying conclusions
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Expanded Accounts
filling in the details of condensed fieldnotes.
Condensed account initial phrases, single words,unconnected sentences that are recorded
Expanded account details, things not initially writtendown are filled in
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Memos
notes written by a researchersuggesting explanations for thecontent of expanded accounts.
conceptual epiphanies
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Memo
is.. the theorizing write-up of ideas aboutcodes and relationship as they strikethe analyst while coding it can be a
sentence, a paragraph or a few pages..It exhausts the analysts momentaryideation based on the data withperhaps a little conceptual elaboration.(Glasers, 1978, p 83 -84)
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Codes
Codes (abbreviation or symbolapplied to a segment of words,or paragraph in order toclassify it)
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Codes are..
labels for assigning meaning attachedto phrases and/or paragraphs inexpanded account.
Devise start list of codes
Prepare a code book
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Open Coding
Initial classification and labeling ofconcepts in qualitative data analysis.Codes are suggested by researchers
examination and questioning of thedata.
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Hand codingqualitativedata
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Answer: D
The key process in the analysis ofqualitative social research data iscoding .
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Data Displays
visual chart that systematically presents information.
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Data Display Types
Matrix connections among meaningsof information
Network lines connecting events
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Strategies for MakingConclusions
ClusteringSubsuming particulars into the generalCountingSeeing plausibilityMaking metaphors
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Verifying Conclusions
Checking for data qualityRepresentativeness (memberchecking)Researcher effects
Testing explanationsReplication of findingsRival explanations
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Holistic Understanding
Constructs broaderapplications of data themes
Grounded theory conceptual rules that emergefrom the data
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THANK YOU