1. APPROACHES TO DATA COLLECTION & ANALYSIS
R. DANIEL SHAW

2. SCIENTIFIC RESEARCH CYCLE (Jim Nelson)
Data
—to be analyzed
How do you get it?
Hypothesis
—suggested by
the theory and data
Theory/model
—built on the data
Inductive Reasoning
Deductive Reasoning
DATA –How will you handle?
Use as a way do develop theory, or understand a model? (INDUCTIVE)
OR as a way to Test a Hypothesis? (DEDUCTIVE)
WHICH WAY SHOULD THE ARROWS GO FOR YOUR RESEARCH?
i.e. where to jump in?
Where do you jump into the cycle?
The answer depends on the nature of your research
R. D. SHAW
Fuller Graduate School of Intercultural Studies

3. Fuller Graduate School of Intercultural Studies
INDUCTIVE REASONING
Begin with the data
Asking what does this mean
Build or adopt and modify a theory (good idea) or model
Comes from a specific context
Inductive reasoning
A reasoning process of drawing conclusions from facts or circumstances. Reaching generalizable conclusions—often qualitative research to derive meaning from within a context
Begin with the data
Asking what does this mean?
Build or adopt and modify a theory or model
Specific to a context
Qualitative research
A reasoning process of drawing conclusions from facts or circumstances. Reaching generalizable conclusions—often qualitative, based on meaning.
R. D. SHAW
Fuller Graduate School of Intercultural Studies

4. Fuller Graduate School of Intercultural Studies
RESEARCH CYCLE (cont.)
Inductive Reasoning Recognizes . . .
The meaning of data in context = Validity (what’s going on here? A search for truth)
Focus is on understanding the perspective in a particular context
Effective Methods: Participant observation, interviews, focus groups = case studies
--Context dependent
Data can be trusted
Suggests Case studies = examples of the issue/problem being researched
3) Qualitative Research Methods
R. D. SHAW
Fuller Graduate School of Intercultural Studies

5. Fuller Graduate School of Intercultural Studies
DEDUCTIVE REASONING
State an hypothesis and test it
Does this work?
Can I predict or anticipate certain things as a result of what I know
Knowing x and y, can I predict z?
Hypothesis represents a viewpoint and you are controlling the data
A process of logical reasoning from stated propositions. Hypothesis testing—often quantitative research, based on numbers
R. D. SHAW
Fuller Graduate School of Intercultural Studies

6. Fuller Graduate School of Intercultural Studies
RESEARCH CYCLE (cont.)
Deductive Reasoning Requires
Quantification and measurement = Reliability (consistency).
Focus is on prediction and control
Effective Methods: survey, random sampling, means to verify hypothesis = quantification
--Researcher dependent
Is data truthful?
3) Viggo Sogaard’s course, etc.
R. D. SHAW
Fuller Graduate School of Intercultural Studies

7. USING A MIX OF METHODS FOR DATA AND ANALYSIS
Qualitative
Quantitative
On site research for validity (Participant Observation—collect data; Grounded theory—analyze data)
Meaning of #s and trends (Questionnaires –collect; Computer/
cognitive programs—analyze)
ANALYSIS
to Establish Findings and Achieve Goals
Discover INDICATORS
What/how #s support the data (Interviews that give you specific data; Content—analysis
How #s apply for reliability (Survey—collect; Statistics— analysis)
R. D. SHAW
Fuller Graduate School of Intercultural Studies

8. MISSIOLOGICAL RESEARCH
Missiological research tends to be phenomenological in nature—Focus is on “what’s going on.”
Research is generally concerned with:
Understanding people/issues in context
Developing theory/models from data
Applying understanding from one context to impact another (generalizability/universals)
R. D. SHAW
Fuller Graduate School of Intercultural Studies

9. MISSIOLOGICAL RESEARCH (Cont.)
Therefore, methods tend toward inductive approaches, but don’t ignore deduction
Collect data that provide understanding of a context which contributes to new theory/models and leads to testable hypotheses—theory derives from data!
Collect data to support the applicability of theory and hypotheses in a context other than the original—generalizability of data
INDUCTIVE DATA: (Inductive/Qualitative)—theory emerges from data (Grounded Theory/Case Studies)
Focus on Openness, Selective sampling, Subjective, Context issues (human diversity)
HARD TO QUANTIFY!
2) DEDUCTIVE DATA: (Deductive/Quantitative)—data supports theory (Surveys, Church Growth study)
Focus on Control, Random sampling, Objective, Universal issues (Human commonality)
R. D. SHAW
Fuller Graduate School of Intercultural Studies