Methods and Methodologies

Research helps us make sense of the world.  How we 'know' things and how we 'measure' these things will influence how we do social research.  While there are three basic approaches to research-qualitative, quantitative and mixed methods, it has been argued that these approaches are not mutually exclusive, rather they exist on a continuum.

Qualitative research strategies (a non-exhaustive list)

 

Explanatory

  • Studies that are conducted to explain social phenomenon

  • Objective: to build theories that can explain a phenomenon

 

Interpretive

  • A way to understand the actions of people in social circumstances

  • Objective: to provide a many layered description and interpretation of human action

 

Critical

  • Studies that are a social critique that exposes harmful or alienating social conditions

  • Objective: help people to change their beliefs and actions

The main steps of qualitative research 

 

 

 

 

 

Source  (Bryman 2008, p 370)

 

 

Qualitative approaches to research (a non-exhaustive list)

 

Narrative research:

  • Studying one or two individuals, collecting data from their stories, reporting individual experiences, and chronologically ordering the meaning of those experiences (a life history, for example)

Phenomenological research:

  • The meaning of an experience for a number of individuals, i.e. what all participants have in common as they experience a certain phenomenon

Grounded theory research:

  • Moving beyond description to generate or discover a theory. The researcher generates a general explanation of a process, action or interaction shaped by the views of a large number of participants (grounded in data from the field)

Ethnographic research:

  • The researcher describes and interprets the shared and learned patterns of values, behaviours, beliefs, and issues such as power, resistance, and dominance, of a culture-sharing group

Case-study research:

  • The study of an issue explored in one or more cases, bound by time and place, with detailed, in-depth data collection involving multiple sources of information (observations, interviews, documents, audio-visual material) – cases are selected to illustrate the issue

Discourse analysis:

  • Focusing on language as a social practice in its own right and looking at how individuals use language in specific contexts. It enables researchers to gain an understanding of how individuals use language to construct themselves and the world around them

 

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Quantitative research values (a non-exhaustive list)

Measurement:

  • To delineate fine differences between people, organizations, or any other unit of analysis

  • To provide a consistent device for gauging distinctions

  • To produce precise estimates of the degree of the relationship between concepts

 

Causality:

  • Explanation: why things are the way they are

  • Direction of causal influence:relationship between dependent & independent variables

  • Confidence :in the researcher's causal inferences

 

Generalisation:​

  • Can findings be generalised beyond the confines of the particular context?

  • Can findings be generalised from sample to population?

  • How representative are samples?

Replication:

  • Minimizing contamination from researcher biases or values

  • Explicit description of procedures

  • Control of conditions of study

  • Ability to replicate in differing contexts

 

The main steps of quantitative research 

 

   

Source  (Bryman 2008, p 141

Quantitative approaches to research (a non-exhaustive list)

 

Primary data gathering 

  • Surveys

    • Questionnaires

  • Observation

    • Structured

    • Covert and Overt 

  • Interviews

  • Unobtrusive measures

    • Physical measures

    • Running records

    • Digital Archives

    • The internet

 

Secondary data gathering

  • Data mining from:

  • Statistics websites

  • Development websites

    • e.g. World Health Organisation

    • OECD

  • Public Records data

  • Census web sites

  • Government statistical archives

    • e.g. Education Counts (NZ)

  • Digital data archive sites

    • NDAD

    • ICPSR

 

Data analysis (a very limited list) 

  • Descriptive analysis (Frequencies/proportions central tendencies)

  • More complex statistical testing dependent on data type (Nominal, Ordinal, or Categorical) and hypothesis to be tested

 

Common statistical packages used

  • SAS

  • SPSS

  • Excel

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