What is Triangulation?
Definition: Triangulation is a research technique that involves the use of multiple methods or sources of data to increase the validity and reliability of findings.
When triangulated, data from different sources can be combined and analyzed to produce a more accurate understanding of the phenomenon being studied. Triangulation can be used in both quantitative and qualitative research and can be implemented at any stage of the research process.
Types of Triangulation
There are four types of Triangulation in research:
- Data triangulation
- Investigator triangulation
- Theory triangulation
- Methodological triangulation
Data triangulation is defined as the use of multiple methods to collect and analyze data in order to test the validity of the findings. This means that if the results of one method support the findings of another method, then the findings are more likely to be accurate.
Investigator triangulation is a method used by researchers to collect data from multiple sources in order to confirm the accuracy of their findings. This technique is often used in fields such as psychology and sociology, where researchers may rely on interviews, surveys, and observations to gather information about a particular subject. By collecting data from multiple investigators, or using multiple methods of data collection, researchers can increase the validity of their findings and improve the quality of their research.
Theory triangulation is the process of using multiple theories to explain a phenomenon. In other words, it is the use of multiple perspectives to understand a problem. Theory triangulation can be used in research to provide a more comprehensive understanding of a phenomenon. It can also be used in practice to help find solutions to problems that have been difficult to solve from a single perspective.
Methodological triangulation is an approach that uses multiple methods to collect and analyze data in order to increase the validity and reliability of the research. This approach can be used in quantitative, qualitative, or mixed-methods research designs. It can also help researchers identify problems with their research design or data collection methods.
Triangulation Data Collection Methods
There are several methods of triangulation data collection, including:
- Focus Groups
- Participant observation
- Document analysis
Example of Triangulation
Example: If a researcher wants to study the effects of a new educational program, they might use triangulation by collecting data from multiple sources such as surveys, interviews, and observations.
When to use Triangulation
There are times when triangulation can be an effective problem-solving technique.
- When two people are arguing and can’t seem to come to a resolution, triangulation may help. By getting a third person involved, the two people can share their sides of the story and come to a resolution.
- Triangulation can also be helpful in determining the truth in a situation. If there are conflicting stories, triangulation can help to determine what really happened.
Advantages of Triangulation
There are several advantages to triangulation:
- It increases accuracy: When you get feedback from multiple sources, you’re more likely to get an accurate picture of the situation.
- It builds consensus: When everyone has a say in the decision-making process, there is greater buy-in and less likelihood of resistance down the line.
- It encourages creativity: By hearing different viewpoints, you can come up with more innovative solutions to problems.
- It develops communication skills: Communicating with people from different backgrounds and cultures helps you understand more about the world.
- It expands your horizons: You can get to know new places, new cultures, and new people.
- It builds self-confidence: You get to know yourself better and become more confident in your abilities.
Also see Exploratory Research
Disadvantage of Triangulation
There are also disadvantages to using the Triangulation technique.
- Triangulation can be time-consuming and costly (especially if multiple methods are used).
- It can be difficult to find appropriate data sources and to develop a common understanding of the data among researchers.
- Triangulation can lead to data overload, which can make it difficult to draw conclusions from the data.
- It can increase the risk of bias, as researchers may be more likely to find evidence that supports their hypotheses.
Also see Explanatory Research