Post on 06-Apr-2017
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ByDr.Kanagaraj Easwaran
Associate Professor and HeadDepartment of Social WorkSchool of Social Sciences
Mizoram UniversityAizawl -796 004.
Natural Science Research Model Quantitative Approach/Strategy/ Paradigm Goal: Verify the predictions of a theory Quantification of concepts into variables Quantification of association Formal structured instruments in data
collection Application of Statistical Theory &
Techniques
Theory Hypotheses
◦ A set of organically connected propositions
◦ That are located at a higher level of abstraction and generalization than empirical reality,
◦ And which are derived from empirical patterns,
◦ And from which empirical forecasts can be derived.
◦ A proposition that implies a relationship between two or more concepts,
◦ Which is located on a lower scale of abstraction and generality than the theory,
◦ Which enables the theory to be transformed into terms that can be tested empirically.
Semantic content(meaning) of linguistic signs and mental images(Corbetta 2003)
" a mental image we use as summary device for bringing together observations and experiences that seem to have nothing in common [...] they do not exist in the real world, so they can't be measured directly" (Babbie, 1989)
"Conceptualization : Process of specifying the vague mental imagery of our concepts [by] sorting out the kinds of observations and measurements that will be appropriate for our research" (Babbie, 1989).
Operationalisation: development of specific research procedures (operations) that will result in empirical observations representing those concepts in the real world" Babbie (1989)
Translation of theoretical abstract concepts to concrete, observable variables
Steps in empirical transformation of concepts Applying the concepts to concrete objects
Making the concepts into attributes or property of the units of analysis.
Make concept-property operational Giving operational definition Establishing rules for transforming into empirical
operations: theoretical Application of rules on concrete cases: practical action
Measuring, Ordering, Counting, Classifying Passage from properties to variables
Dimension I Indicator 1 Variable 1Indicator 2 Variable 2
Concept Dimension II Indicator 3 Variable 3Indicator 4 Variable 4 IndexIndicator 5 Variable 5
Dimension III Indicator 6 Variable 6Indicator 7 Variable 7
Involves a set of Choices or Decision Making Units of Analysis
Individual, the aggregate of individuals Points of Focus :
Characteristics, Behaviour, Cognition, relations Treatment of the Dimension of Time
Cross Sectional or Time Series Nature of Measurement Nominal, Ordinal, Interval , or Ratio
Complex Concepts
Concept is broken into dimensions
Indicators are chosen
Indicators are operationalised
Indexes or scales or formed
Consistency of a measure of a concept◦ Stability over time◦ Internal reliability or consistency ◦ Inter-observed consistency
Validity: Whether an indicator or set of indicators that is devised to gauge a concept really measures the concept. – Truthfulness
Face Validity Concurrent Validity: Criterion Convergent: Other Measures of the same
concept
MeasurementCausalityGeneralization Replication
World of Nature vs Social World Phenomenological Self Reflection Consciousness Meaning
Measurement Process Artificial Connection Concepts and Measures not real Measurement by fiat Differences in respondents interpretation
No Connection between Research and Every Day Life: Instruments
Static view of Life: Analysis of Relationship between variables
◦ Ideal Typical Representation
◦ Variation or Differences
◦ Reverse operationalisation
◦ Inductive Conceptualisation: Factor Analysis
Questions Please
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