Interobserver agreement (IOA) quantifies the extent to which independent observers’ data match. Computation of this metric involves comparing the recordings of two or more observers who have independently observed and recorded the same event or behavior. For example, if two observers are tracking the frequency of a specific student behavior in a classroom, a calculation of this type provides a numerical index of their consistency in identifying and recording those behaviors.
Establishing acceptable levels of agreement is crucial for research validity and the reliability of data collected in applied settings. High levels of agreement strengthen confidence that the data accurately reflect the phenomenon being observed, minimizing observer bias and measurement error. The use of this type of measurement has a long history in observational research, particularly in fields like psychology, education, and behavioral analysis, where direct observation is a primary method of data collection. Its adoption contributes to the scientific rigor of the research process.