Which of the following explains why we use operational definitions in research?
Published on May 6, 2022 by Pritha Bhandari. Revised on December 2, 2022. Operationalization means turning abstract concepts into measurable observations. Although some concepts, like height or age, are easily measured, others, like spirituality or anxiety, are not. Through
operationalization, you can systematically collect data on processes and phenomena that aren’t directly observable. In quantitative research, it’s important to precisely define the
types of variables that you want to study. Without transparent and specific operational definitions, researchers may measure irrelevant concepts or inconsistently apply methods. Operationalization reduces subjectivity, minimizes the potential for research bias, and
increases the reliability of your study. Your choice of operational definition can sometimes affect your results. For example, an experimental intervention for social anxiety may reduce self-rating anxiety scores but not behavioral avoidance of crowded places.
This means that your results are context-specific, and may not generalize to different real-life settings. Generally, abstract concepts can be operationalized in many different ways. These differences mean that you may actually measure slightly different aspects of a concept, so it’s important to be specific about what you are measuring. If you test a hypothesis using multiple operationalizations of a concept, you can check whether your results depend on the type of measure that you use. If your results don’t vary when you use different measures, then they are said to be “robust.” There are 3 main steps for
operationalization: Based on your research interests and goals, define your topic and come up with an initial research
question. There are two main concepts in your research question:
2. Choose a variable to represent each of the concepts.Your main concepts may each have many variables, or properties, that you can measure. For instance, are you going to measure the amount of sleep or the quality of sleep? And are you going to measure how often teenagers use social media, which social media they use, or when they use it?
3. Select indicators for each of your variables.To measure your variables, decide on indicators that can represent them numerically. Sometimes these indicators will be obvious: for example, the amount of sleep is represented by the number of hours per night. But a variable like sleep quality is harder to measure. You can come up with practical ideas for how to measure variables based on previously published studies. These may include established scales (e.g., Likert scales) or questionnaires that you can distribute to your participants. If none are available that are appropriate for your sample, you can develop your own scales or questionnaires.
After operationalizing your concepts, it’s important to report your study variables and indicators when writing up your methodology section. You can evaluate how your choice of operationalization may have affected your results or interpretations in the discussion section. Strengths of operationalizationOperationalization makes it possible to consistently measure variables across different contexts.
Scientific research is based on observable and measurable findings. Operational definitions break down intangible concepts into recordable characteristics.
A standardized approach for collecting data leaves little room for subjective or biased personal interpretations of observations.
A good operationalization can be used consistently by other researchers (high replicability). If other people measure the same thing using your operational definition, they should all get the same results. Limitations of operationalizationOperational definitions of concepts can sometimes be problematic.
Many concepts vary across different time periods and social settings. For example, poverty is a worldwide phenomenon, but the exact income-level that determines poverty can differ significantly across countries.
Operational definitions can easily miss meaningful and subjective perceptions of concepts by trying to reduce complex concepts to numbers. For example, asking consumers to rate their satisfaction with a service on a 5-point scale will tell you nothing about why they felt that way.
Context-specific operationalizations help preserve real-life experiences, but make it hard to compare studies if the measures differ significantly. For example, corruption can be operationalized in a wide range of ways (e.g., perceptions of corrupt business practices, or frequency of bribe requests from public officials), but the measures may not consistently reflect the same concept. Frequently asked questions about operationalizationWhat is operationalization? Operationalization means turning abstract conceptual ideas into measurable observations. For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations. Before collecting data, it’s important to consider how you will operationalize the variables that you want to measure. What’s the difference between concepts, variables, and indicators? In scientific research, concepts are the abstract ideas or phenomena that are being studied (e.g., educational achievement). Variables are properties or characteristics of the concept (e.g., performance at school), while indicators are ways of measuring or quantifying variables (e.g., yearly grade reports). The process of turning abstract concepts into measurable variables and indicators is called operationalization. Cite this Scribbr articleIf you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.
Is this article helpful?You have already voted. Thanks :-) Your vote is saved :-) Processing your vote... What is the most important reason to use operational definitions?The need for operational definitions is fundamental when collecting all types of data. It is particularly important when a decision is being made about whether something is correct or incorrect, or when a visual check is being made where there is room for confusion.
Which of the following is the purpose of using an operational definition?Which of the following is the purpose of using an operational definition? Establishing an operational definition ensures that everyone agrees on what a variable means.
What is the purpose of an operational definition in a study quizlet?An operational definition specifies a measurement procedure (a set of operations) for measuring an external, observable behavior and uses the resulting measurements as a definition and a measurement of the hypothetical construct.
What is operational definition of terms in research?Operational definition of terms refers to a detailed explanation of the technical terms and measurements used during data collection. This is done to standardize the data. Whenever data is being collected, it is necessary to clearly define how to collect the data.
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