All statistical analyses are guided by a research question. Properly defining all variables and clearly stating a problem are the first steps in the data presentation process. This article discusses the operationalizing of variables.
Operationalization is the process of translating a research idea, (which may focus on an abstract theme), into something that can actually be researched in practice. This process can be subdivided into five stages:
This process of operationalisation can be subdivided into five stages:
Stage 1: starting from your central research focus, identify the factors that could have an impact on the focus you want to study within your education context.
Stage 2: begin to frame research questions to explore these factors.
Stage 3: develop an operational definition or indicator for each of the factors you want to study to enable you to identify this practically (particularly useful for factors that represent abstract concepts).
Stage 4: identify the kind of evidence you need to answer your research questions and select most appropriate research methods that will enable you to collect this evidence.
Stage 5: design the research tools that you will use to collect this evidence.
Creating operational definitions for the factors that are influencing your research focus involves identifying indicators that enable you to research these factors. Creating an operational definition for each of the factors which are important in your research enables the research question to be translated into a form that can be researched i.e. it becomes operational. Therefore the purpose of operational definitions is to create indicators which enable you "to tell when the thing you are researching happens". Also where terms in research questions describe complex ideas or processes or there is the possibility that different people may interpret terms differently, it is important to establish a working definition of key terms. Factors that are based on abstract concepts for which operational definitions need to be developed include: attitude to learnin'; creatitvity; resilience; curiosity. These abstract concepts need to operational definitions which provide indicators that translate them into a form which can be studied. Collecting data about these indicators will enable you to explore the impact of variables / factors within the context that you are researching. These indicators are measured or explored through the use of research tools such as questionnaires or interview schedules.
The development of indicators for the variables or factors you want to research is particularly important where these are not easy to represent. In the example below possible indicators have been identified for variables exploring differences in questions that can be investigated through a quantitative or qualitative approach:
|
Variable / Factor to be investigated |
Possible indicator for quantitative research (can be quantified) |
Possible indicator for qualitative research |
|
Attitudes to learning |
Amount of on-task behaviour determined through observation (time-sampling) |
Enthusiasm observed during a task Attitudes expressed for aspects of learning during semi-structured interview |
|
Effectiveness of teacher questioning |
Incidence of the use of open or closed questions (counting) |
Types of pupil response generated by open and closed questions Pupils' perceptions of the teacher's use of questioning explored during interview |
|
The level of cognitive demand in talk episodes |
N/A |
Framework for the analysis of talk based on indicators for three levels of talk: Disputational talk Cumulative talk Exploratory talk |
|
Creativity |
N/A |
Willingness to try out new things Engagement in risk taking Perseverance in response to challenges |
Source: Education Futures Collaboration, http://www.meshguides.org/guides/node/470
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