In the world of research, reliability and validity are used to analyze the quality of research. Before we dig deeper to learn about validity vs reliability, let's first understand what each of these terms means individually.
When it comes to the reliability vs validity definition, reliability is about the consistency of a measure, whereas validity refers to a measure's accuracy. Validity and reliability play a vital role in research work, especially for creating research design, planning research methods and writing quantitative research results.
In reliability, the accuracy is determined by stable and consistent results.
It is a measure obtained by conducting a test twice to evaluate the results' stability over time.
Example: Let's say a group of students took a class test twice. The results for individual students and the correlation of results indicate stability.
The measure determines if different people obtain the same result after conducting the measure. Such reliability is beneficial when observers don't necessarily interpret the answers, and raters may disagree on how a response demonstrates skills and knowledge.
Example: Interrater reliability is used when judgments are relatively subjective.
It evaluates if one gets the same results from different test items constructed to produce the same results. There are two subparts of internal consistency reliability:
While validity and reliability are closely related, the main argument concerning validity vs reliability is that reliability shows how consistent a particular measure is without considering its accuracy.
Validity refers to how well a method measures what it is supposed to measure. Reliability may be necessary but not sufficient. A test should be valid to be reliable.
For example, let’s say you are using a thermometer to measure your body temperature, but the scale is off by some degrees. It may consistently give you the same result after measuring your body temperature. Still, it may is not valid as it adds to your actual temperature and therefore is not valid.
It ensures the exact measure of the existing knowledge and theory. The panel of experts can evaluate the items and determine which one to measure.
Example: An examination can be used to evaluate a student's knowledge relevant to various concepts. The strong correlation between each concept score would indicate high construct validity.
It measures the results that correlate test results of other similar concepts.
Example: Before the elections, various surveys analyze the political opinions of different voters in a region. If the poll results accurately predict the future of the election results, it shows that the survey reports have high criterion validity.
It is applied to assess how a measure provides details to enhance the program of study.
Example: When designing a study program in history for students, the aim is to assess their knowledge of the subject. If the measure provides information on a student's lack of expertise in a specific area, it improves a student's course requirements.
It ensures to cover the measurement of all concepts under study.
Example: When drafting an assessment for film studies, you cannot only focus on the acting part. You must include the other areas such as sound, lighting, and other operational functions. Such assessment will help you measure the overall content area.
Validity is considered when you choose the way to collect data. For ensuring validity in research:
Reliability is considered during the data collection process. For ensuring reliability in research:
If you are wondering where to write about validity and reliability in a research paper, well, there are various sections.
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