Published on May 6, 2022 by Pritha Bhandari. Revised on July 21, 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
variables that you want to study. Without transparent and specific operational definitions, researchers may measure irrelevant concepts or inconsistently apply methods. Operationalization reduces subjectivity 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.” How to operationalize conceptsThere are 3 main steps for operationalization:
1. Identify the main concepts you are interested in studying.Based on your research interests and goals, define your topic and come up with an initial research question. Research question exampleIs there a relation between sleep and social media behavior in teenagers?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 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. 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). Variablesare 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. Is this article helpful?You have already voted. Thanks :-) Your vote is saved :-) Processing your vote... What term is used to describe factors in a research that can be measured or manipulated?A variable is anything that can change or be changed. In other words, it is any factor that can be manipulated, controlled for, or measured in an experiment. Experiments contain different types of variables.
What is control and manipulation in research?Manipulation means that something is purposefully changed by the researcher in the environment. Control is used to prevent outside factors from influencing the study outcome. When something is manipulated and controlled and then the outcome happens, it makes us more confident that the manipulation "caused" the outcome.
What is it called when researchers manipulate a variable in a study?Experimental manipulation describes the process by which researchers purposefully change, alter, or influence the independent variables (IVs), which are also called treatment variables or factors, in an experimental research design.
What type of research involves manipulation and control of variables?An experiment is a type of empirical study that features the manipulation of an independent variable, the measurement of a dependent variable, and control of extraneous variables.
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