Post on 26-Dec-2015
World views influence our research/assessment topic = EpistemologiesWorld views influence our research/assessment topic = Epistemologies
Qualitative = Meaning & UnderstandingQualitative = Meaning & Understanding
Chapter 2 – Literature ReviewWritten summary of journal articles, books, past and current state of info.
Chapter 2 – Literature ReviewWritten summary of journal articles, books, past and current state of info.
Defining Research- What is Research?- What is Assessment?- Why are Research/Assessment
important?- Similarities/Differences of
Research / Assessment?
Defining Research- What is Research?- What is Assessment?- Why are Research/Assessment
important?- Similarities/Differences of
Research / Assessment?
Chapter 1 – Introduction1. Research Topic (General area of
study)2. Research Problem (Particular
aspect of scholarly inquiry)3. Research Question (Succinct
statement or two; what do you want to know?)
Chapter 1 – Introduction1. Research Topic (General area of
study)2. Research Problem (Particular
aspect of scholarly inquiry)3. Research Question (Succinct
statement or two; what do you want to know?)
Chapter 3 – Methodological ProcessDescribes general way research/ assessment question will be approached.Methodological process is the way in which you are going to be conducting your research.
Chapter 3 – Methodological ProcessDescribes general way research/ assessment question will be approached.Methodological process is the way in which you are going to be conducting your research.
Ste
ps to
Researc
h S
tep
s to
Researc
h S
tep
s to
R
esearc
h
1st step in defining YOUR research/assessment = find your topic
so it can guide the process
Often lit. reviews help determine the research question
Lit. Review informs research topicObservations
*Simple = simply observing*Contrived = create a specific scenario
Observations*Simple = simply observing*Contrived = create a specific scenario
*Write Descriptively*Write w/ discipline
*Be validated*Make familiar
NEW!
How is
dat
a
colle
cted?
Document AnalysisDocument Analysis
Is the research credible (congruent with reality)?
Threats to trustworthiness:Credibility= unreliable
Transferability= short & specificDependability= bias unstable
Qualitative is
good if it is
trustworth
yQualitative is
good if it is
trustworth
y
How to determine participants
Interviews*Structured = universal questions* Semi structured = structured + free flow *Entirely Emergent = completely free-flow
Interviews*Structured = universal questions* Semi structured = structured + free flow *Entirely Emergent = completely free-flow
SamplingTypical
ExtremeHomogeneous
Maximum VariationCriterionSnowball
SamplingTypical
ExtremeHomogeneous
Maximum VariationCriterionSnowball
Types of DesignGrounded Theory - creation of theoryAction - gather research to improve problemCase Study - specific and bound (time, place, etc.)Ethnography - becomes part of community, Narrative - based on spoken/written word-retell Phenomenology -experience w/in a phenomenon
Types of DesignGrounded Theory - creation of theoryAction - gather research to improve problemCase Study - specific and bound (time, place, etc.)Ethnography - becomes part of community, Narrative - based on spoken/written word-retell Phenomenology -experience w/in a phenomenon
Focus GroupsOrganized group discussion with interaction among key
members*Structured*Semi-Structured*Entirely Emergent
When to use interviewsCannot observe a particular behavior or phenomenonA more controlled inquiry is desiredRich in depth data needed
When to use interviewsCannot observe a particular behavior or phenomenonA more controlled inquiry is desiredRich in depth data needed
When to use focus groupsMultiple perspectives = more or robust dataGroup interaction increases trustworthinessData collection time is limited
Successful Observations
Positivists (THE truth), Interpretive (many interpretations=truth), Postmodernism (individual truth), Critical Social Science (what we know is marred)
Positivists (THE truth), Interpretive (many interpretations=truth), Postmodernism (individual truth), Critical Social Science (what we know is marred)
Variables characteristics that are
measured
Independent - impacts dependent variable Dependent - depends on action of independent variable
Types of DesignExperimental - cause and effect using random samplingQuasi Experimental - cause and effect but can’t randomize sampleNon-Experimental - surveys and correlations
SurveyStrength• can be locally designed & made to
meet specific needs• easy to study large populations• can be updated, replicated• can be used as-is, with permission
from the authorLimitations• Non-response bias – those who don’t
respond may have a different opinion, those who do may be similar
Surveys that are not good• asking people to remember the
past• double barreled questions –
asking two questions at once• leading the respondents to a
particular answer• inaccessible language (ie. use
of jargon, slang, or highly technical terms)
• answers which are not mutually exclusive
• answers which are not exhaustive
Other Considerations• Survey organizations• Introduction / transitions• Time• Location
Quantitative = Statistical Relationship, causation, correlation
Quantitative = Statistical Relationship, causation, correlation
Sampling Simple
StratifiedSystematicClustering
ConvenienceSnowball
How is Data Collected?
What is measured
How to determine
participants
How
is D
ata
Colle
cted
?
Non-Experimental
Designing the survey
Validity relies on reliability Is research valid? Is it reliable?
Threats to Validity:(Internal)=*history *maturation *selection *mortality
(Treatment)= *diffusion *compensatory equalization/rivalry *demoralization
(Procedures)= *testing familiarity *demoralization
Extantexisting data, information &
observations previously collectedStrength • don’t have to do data collection• expanding, building, repurposingLimitations• risk of data being outdated• population may not fit your target (ie.
only subset)• since you don’t know the purpose of
the data collection previously conducted, there may be external forces you don’t know about
• don’t know the rigor of the data collection that was conducted
Ethical Considerations
Key Events1. Nuremberg Code
(1940)- Post World War II, running unethical experiments on humans, consent. Result was consent from people to have experiment performed.
2. Thaimaldohide- (1950s-1962)- Medicine/drug in Europe= deformities is babies. Informed consent violated/ FDA needed to regulate
3. Tuskegee Syphilis Study (1932-1972)- Violated African American participants by withholding cure of syphilis in order to understand progression
4. Declaration of Helsinki (1964)- With mounting pressure, this was like a “blown up Nuremberg Code”, research needs to be based on lab/animal experimentation
5. National Research Act & Belmont Report (1974)- Response to Tuskegee, protection of human subjects
6. Common Rule (1981-1991)- Put into law and is where we are now!
Belmont Report:Respect for persons: autonomous agents, diminished autonomy entitled to protectionBeneficence- Human subjects should not be harmed, research benefits maximizedJustice- benefits of research must be distributed fairlyCommon Rule:
Institutional compliance required, informed consent, requirement for IRB membership, record keeping, stipulate additional protectuoibs for certain vulnerable research subjects
Chapter 4 – Analyzing & Interpreting Data
Making meaning of the data that is collected
Chapter 4 – Analyzing & Interpreting Data
Making meaning of the data that is collected
Chapter 5 – Discussions
Summary of key finds, explanation of results, suggest limitations in the research and make recommendations for future inquiries.
Chapter 5 – Discussions
Summary of key finds, explanation of results, suggest limitations in the research and make recommendations for future inquiries.
Ste
ps to
Researc
h
Data Preparation1. Organize data 2. Transcribe data from audio recording/field notes to
data *by hand or computer using qualitative computer programs.
Data Preparation1. Organize data 2. Transcribe data from audio recording/field notes to
data *by hand or computer using qualitative computer programs.
Data Analysis - Coding1. Get a general sense of data (preliminary
exploratory) 2. Code the data (make sense out of text data using
labels of segments with codes) 3. Pick one document 4. code the document with brackets and text segment
5. Make a list of all code words 6. Take list and go back to data 7. Reduce lists finding themes and categories
The 3 C’s of AnalysisCodes = “storage bins” / general headingsCategories = consolidation of codesConcepts/Themes = categories as meaningful
statements (5-7 themes)
*Be sure to check work against original text
Effective Narrative Data Analysis• Revisit research question frequently• Develop a system, test it, then stick with it• Review all data again & again• Allow concepts to emerge organically• Synthesize information without loosing sight of main
focus• Honor participant voices• Use technology as appropriate
Data Analysis - Coding1. Get a general sense of data (preliminary
exploratory) 2. Code the data (make sense out of text data using
labels of segments with codes) 3. Pick one document 4. code the document with brackets and text segment
5. Make a list of all code words 6. Take list and go back to data 7. Reduce lists finding themes and categories
The 3 C’s of AnalysisCodes = “storage bins” / general headingsCategories = consolidation of codesConcepts/Themes = categories as meaningful
statements (5-7 themes)
*Be sure to check work against original text
Effective Narrative Data Analysis• Revisit research question frequently• Develop a system, test it, then stick with it• Review all data again & again• Allow concepts to emerge organically• Synthesize information without loosing sight of main
focus• Honor participant voices• Use technology as appropriate
Results1. Summarize findings 2. Convey personal reflections 3. Compare to literature 4. Limitations and suggestions
Results1. Summarize findings 2. Convey personal reflections 3. Compare to literature 4. Limitations and suggestions
Use Computer Software
for
• Text identification &
retrieval
• Text analysis
Nud*istNVivoAtlas.ti
Ethnograph
Data Preparation• Score the Data • Determine Types of Scores to Analyze • Select Statistical Program • Input Data• Clean & Account for Missing Data
Data Preparation• Score the Data • Determine Types of Scores to Analyze • Select Statistical Program • Input Data• Clean & Account for Missing Data
Data AnalysisDescriptive statistics describe response to
questions an determine overall trends and distribution of data.
Inferential statistics – draw conclusions, inferences, or generalizations from a sample to a population of participants.
Data AnalysisDescriptive statistics describe response to
questions an determine overall trends and distribution of data.
Inferential statistics – draw conclusions, inferences, or generalizations from a sample to a population of participants.
ResultsTables, Figures, Presentations – wordsResultsTables, Figures, Presentations – words
We still don’t quite understand