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Social Work Research Methods: Qualitative and Quantitative Approaches Topic 6: Basic Social Work Research Designs View a Research and Evaluation Planning Site:
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2. Topic 6: Basic Social Work Research Designs
What are Quantitative Research Designs?
What are Qualitative Research Designs?
What is Triangulation?
Basic Terms
What are Causal hypotheses?
What is a Null hypothesis?
What are the basic logical errors in causal explanation?
How do you select a topic?
How does one narrow down a topic?
What are some examples of bad and good questions?
Chapter 6: Qualitative and Quantitative Research Designs
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3. What are Quantitative Research Designs?
Quantitative social work researchers often refer to their observations as ‘hard data’; that is, statistical tabulations of occurrences or events.
Quantitative social work researchers usually follow a linear path using variables and hypotheses, emphasizing precise measures, and linking findings to general causal explanations.
Quantitative social work researchers are more likely to use reconstructed logic - highly organized formal language.
Quantitative social work researchers use technocratic logic, engaging statistical design issues.
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4. What are Qualitative Research Designs?
Qualitative social work researchers are more likely to refer to their observations as ‘soft data’, these derive from heir impressions, statements, photos, maps or symbols.
Qualitative social work researchers usually follow a non-linear path, going wherever the setting takes them, emphasizing more imprecise measures, and using intuition or insight.
Qualitative social work researchers are more likely to use logic in practice, making informal judgment calls.
Qualitative social work researchers use transcendent logic about process and growth.
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What is Triangulation?
Triangulation involves multiple measures of the same phenomenon.
Triangulation of theory is multiple theoretical perspectives used during planning or analysis of the setting.
Triangulation of methods is the mixing of multiple styles that may be qualitative and quantitative.
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Basic Terms
Variables are measures of a concept that take two or more values, such as male or female.
Attributes are the values or categories of a variable. Male is an attribute of the variable gender.
The independent variable is the presumed cause, and the factor that precedes the effect in time.
The dependent variable is the effect or outcome that is presumed to be impacted, and follows the cause in time.
Intervening variables come between the independent and dependent variables.
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7. What are Causal Hypotheses?
The causal hypothesis has at least two variables.
It expresses a cause-effect relationship.
It is expressed as a prediction or expected future outcome.
It is logically linked to theories and the research question.
It is falsifiable, or capable of being tested against empirical evidence.
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8. What is a Null Hypothesis?
The null hypothesis normally states the negation of the relationship proposed in the research hypothesis.
If a research hypothesis stated: Males are more likely than females to repeat juvenile offenses.”, the null would state: “There is no relationship between the sex of the offender and number of repeat offenses.”
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9. What are the basic Logical Errors in Causal Explanation?
Tautology is a form of fallacious circular reasoning. Sally is conservative because she believes in less regulation. While this may be true, her conservativeness is not caused by her attitude toward regulation.
Teleology are causes that are associated with an ultimate purpose or goal. “Crime occurs because humans are destined to be evil…” is teleological. This violates the principle that the cause precedes the effect in time.
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10. Logical errors continued….
Ecological fallacy arises from a mismatch of units of analysis when moving from a larger to a smaller unit. Knowing the vote totals for a particular polling district does not allow one to conclude how any one person voted.
Reductionism is a mismatch in units of analysis when moving from smaller to larger. Knowing how some individuals in an organization behave does not allow one to conclude the entire organization behaves in a certain way.
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11. Logical errors continued…
Spuriousness occurs when two variables are associated but not causally related. The statistical association between air conditioning and ice cream cones sales is spurious, not causal.
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12. How do you Select a Topic?
Base it on your personal experience
How about curiosity based on current events?
What is the state of knowledge in field?
Are you trying to solve a problem?
Is there a Social premium?
Is it a personal value?
Do you have any everyday experience?
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13. How does one narrow down a Topic?
Examine the literature.
Talk with others.
Limit analysis to a specific context.
Define the aim and outcomes.
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14. What are some examples of bad and good questions?
Bad: Is child abuse a problem?
Good: Has the incidence of child abuse changed in the last three years in Missouri?
Bad: Do social workers affect delinquency?
Good: Has the incidence of delinquency changed among caseloads of MSW level social workers compared to BSW workers in Milwaukee?
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