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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